#SQL Query Building

[giridhar78]

While AI can generate SQL queries, it can’t replace the power of human intelligence. At Global Teq, we help you master SQL by teaching how to apply real-world business logic, context, and error-checking skills that AI can't match. Our SQL course is designed for beginners and professionals alike, with hands-on practice, expert guidance, and job-oriented learning. Learn SQL, master it, and stay in demand in today’s data-driven world. Enroll now and future-proof your tech career!

📞 Contact: +1 (516) 974-6662 📧 Email: globalteq.info@gmail.com 🌐 Website: www.global-teq.com

[smaller-comfort]

thinking about something @ocelly said a while back about writing and editing using different parts of the brain/serving different parts of the creative process- and fundamentally that mindset has been invaluable to me.

unfortunately, my brain has been coasting in editing/refining/polishing mode for a while now and I really need it to shift gears into creative/generative/productive mode. don't get me wrong, I genuinely love the editing process! I'd forgotten how much fun it can be to tease out the right words/meaning from something. I really would have been a very happy copyeditor in another universe.

But there's a whole laundry list of shit that I need done, not polished, and the problem with engaging Editing Brain is that it's hard to convince it that I can live without absolute perfection for a while. You can't polish an empty document, asshole! Get the words on the page first and then worry about the details later.

[codingquill]

SQL Fundamentals #1: SQL Data Definition

Last year in college , I had the opportunity to dive deep into SQL. The course was made even more exciting by an amazing instructor . Fast forward to today, and I regularly use SQL in my backend development work with PHP. Today, I felt the need to refresh my SQL knowledge a bit, and that's why I've put together three posts aimed at helping beginners grasp the fundamentals of SQL.

Understanding Relational Databases

Let's Begin with the Basics: What Is a Database?

Simply put, a database is like a digital warehouse where you store large amounts of data. When you work on projects that involve data, you need a place to keep that data organized and accessible, and that's where databases come into play.

Exploring Different Types of Databases

When it comes to databases, there are two primary types to consider: relational and non-relational.

Relational Databases: Structured Like Tables

Think of a relational database as a collection of neatly organized tables, somewhat like rows and columns in an Excel spreadsheet. Each table represents a specific type of information, and these tables are interconnected through shared attributes. It's similar to a well-organized library catalog where you can find books by author, title, or genre.

Key Points:

Tables with rows and columns.

Data is neatly structured, much like a library catalog.

You use a structured query language (SQL) to interact with it.

Ideal for handling structured data with complex relationships.

Non-Relational Databases: Flexibility in Containers

Now, imagine a non-relational database as a collection of flexible containers, more like bins or boxes. Each container holds data, but they don't have to adhere to a fixed format. It's like managing a diverse collection of items in various boxes without strict rules. This flexibility is incredibly useful when dealing with unstructured or rapidly changing data, like social media posts or sensor readings.

Key Points:

Data can be stored in diverse formats.

There's no rigid structure; adaptability is the name of the game.

Non-relational databases (often called NoSQL databases) are commonly used.

Ideal for handling unstructured or dynamic data.

Now, Let's Dive into SQL:

SQL is a :

Data Definition language ( what todays post is all about )

Data Manipulation language

Data Query language

Task: Building and Interacting with a Bookstore Database

Setting Up the Database

Our first step in creating a bookstore database is to establish it. You can achieve this with a straightforward SQL command:

CREATE DATABASE bookstoreDB;

SQL Data Definition

As the name suggests, this step is all about defining your tables. By the end of this phase, your database and the tables within it are created and ready for action.

1 - Introducing the 'Books' Table

A bookstore is all about its collection of books, so our 'bookstoreDB' needs a place to store them. We'll call this place the 'books' table. Here's how you create it:

CREATE TABLE books ( -- Don't worry, we'll fill this in soon! );

Now, each book has its own set of unique details, including titles, authors, genres, publication years, and prices. These details will become the columns in our 'books' table, ensuring that every book can be fully described.

Now that we have the plan, let's create our 'books' table with all these attributes:

CREATE TABLE books ( title VARCHAR(40), author VARCHAR(40), genre VARCHAR(40), publishedYear DATE, price INT(10) );

With this structure in place, our bookstore database is ready to house a world of books.

2 - Making Changes to the Table

Sometimes, you might need to modify a table you've created in your database. Whether it's correcting an error during table creation, renaming the table, or adding/removing columns, these changes are made using the 'ALTER TABLE' command.

For instance, if you want to rename your 'books' table:

ALTER TABLE books RENAME TO books_table;

If you want to add a new column:

ALTER TABLE books ADD COLUMN description VARCHAR(100);

Or, if you need to delete a column:

ALTER TABLE books DROP COLUMN title;

3 - Dropping the Table

Finally, if you ever want to remove a table you've created in your database, you can do so using the 'DROP TABLE' command:

DROP TABLE books;

To keep this post concise, our next post will delve into the second step, which involves data manipulation. Once our bookstore database is up and running with its tables, we'll explore how to modify and enrich it with new information and data. Stay tuned ...

Part2

[xaltius]

Unlocking the Power of Data: Essential Skills to Become a Data Scientist

In today's data-driven world, the demand for skilled data scientists is skyrocketing. These professionals are the key to transforming raw information into actionable insights, driving innovation and shaping business strategies. But what exactly does it take to become a data scientist? It's a multidisciplinary field, requiring a unique blend of technical prowess and analytical thinking. Let's break down the essential skills you'll need to embark on this exciting career path.

1. Strong Mathematical and Statistical Foundation:

At the heart of data science lies a deep understanding of mathematics and statistics. You'll need to grasp concepts like:

Linear Algebra and Calculus: Essential for understanding machine learning algorithms and optimizing models.

Probability and Statistics: Crucial for data analysis, hypothesis testing, and drawing meaningful conclusions from data.

2. Programming Proficiency (Python and/or R):

Data scientists are fluent in at least one, if not both, of the dominant programming languages in the field:

Python: Known for its readability and extensive libraries like Pandas, NumPy, Scikit-learn, and TensorFlow, making it ideal for data manipulation, analysis, and machine learning.

R: Specifically designed for statistical computing and graphics, R offers a rich ecosystem of packages for statistical modeling and visualization.

3. Data Wrangling and Preprocessing Skills:

Raw data is rarely clean and ready for analysis. A significant portion of a data scientist's time is spent on:

Data Cleaning: Handling missing values, outliers, and inconsistencies.

Data Transformation: Reshaping, merging, and aggregating data.

Feature Engineering: Creating new features from existing data to improve model performance.

4. Expertise in Databases and SQL:

Data often resides in databases. Proficiency in SQL (Structured Query Language) is essential for:

Extracting Data: Querying and retrieving data from various database systems.

Data Manipulation: Filtering, joining, and aggregating data within databases.

5. Machine Learning Mastery:

Machine learning is a core component of data science, enabling you to build models that learn from data and make predictions or classifications. Key areas include:

Supervised Learning: Regression, classification algorithms.

Unsupervised Learning: Clustering, dimensionality reduction.

Model Selection and Evaluation: Choosing the right algorithms and assessing their performance.

6. Data Visualization and Communication Skills:

Being able to effectively communicate your findings is just as important as the analysis itself. You'll need to:

Visualize Data: Create compelling charts and graphs to explore patterns and insights using libraries like Matplotlib, Seaborn (Python), or ggplot2 (R).

Tell Data Stories: Present your findings in a clear and concise manner that resonates with both technical and non-technical audiences.

7. Critical Thinking and Problem-Solving Abilities:

Data scientists are essentially problem solvers. You need to be able to:

Define Business Problems: Translate business challenges into data science questions.

Develop Analytical Frameworks: Structure your approach to solve complex problems.

Interpret Results: Draw meaningful conclusions and translate them into actionable recommendations.

8. Domain Knowledge (Optional but Highly Beneficial):

Having expertise in the specific industry or domain you're working in can give you a significant advantage. It helps you understand the context of the data and formulate more relevant questions.

9. Curiosity and a Growth Mindset:

The field of data science is constantly evolving. A genuine curiosity and a willingness to learn new technologies and techniques are crucial for long-term success.

10. Strong Communication and Collaboration Skills:

Data scientists often work in teams and need to collaborate effectively with engineers, business stakeholders, and other experts.

Kickstart Your Data Science Journey with Xaltius Academy's Data Science and AI Program:

Acquiring these skills can seem like a daunting task, but structured learning programs can provide a clear and effective path. Xaltius Academy's Data Science and AI Program is designed to equip you with the essential knowledge and practical experience to become a successful data scientist.

Key benefits of the program:

Comprehensive Curriculum: Covers all the core skills mentioned above, from foundational mathematics to advanced machine learning techniques.

Hands-on Projects: Provides practical experience working with real-world datasets and building a strong portfolio.

Expert Instructors: Learn from industry professionals with years of experience in data science and AI.

Career Support: Offers guidance and resources to help you launch your data science career.

Becoming a data scientist is a rewarding journey that blends technical expertise with analytical thinking. By focusing on developing these key skills and leveraging resources like Xaltius Academy's program, you can position yourself for a successful and impactful career in this in-demand field. The power of data is waiting to be unlocked – are you ready to take the challenge?

[nixcraft]

lnav: Awesome terminal log file viewer for Linux and Unix

lnav is a terminal-based log file viewer (TUI) for Linux, FreeBSD, macOS, and other Unix-like systems. It combines the functionality of tools like tail, grep, awk, sed, and cat into a single interface. It also allows you to run SQL queries against your log files to build reports and offers basic support for Linux containers like Docker

[sonadukane]

How to Become a Data Scientist in 2025 (Roadmap for Absolute Beginners)

Want to become a data scientist in 2025 but don’t know where to start? You’re not alone. With job roles, tech stacks, and buzzwords changing rapidly, it’s easy to feel lost.

But here’s the good news: you don’t need a PhD or years of coding experience to get started. You just need the right roadmap.

Let’s break down the beginner-friendly path to becoming a data scientist in 2025.

✈️ Step 1: Get Comfortable with Python

Python is the most beginner-friendly programming language in data science.

What to learn:

Variables, loops, functions

Libraries like NumPy, Pandas, and Matplotlib

Why: It’s the backbone of everything you’ll do in data analysis and machine learning.

🔢 Step 2: Learn Basic Math & Stats

You don’t need to be a math genius. But you do need to understand:

Descriptive statistics

Probability

Linear algebra basics

Hypothesis testing

These concepts help you interpret data and build reliable models.

📊 Step 3: Master Data Handling

You’ll spend 70% of your time cleaning and preparing data.

Skills to focus on:

Working with CSV/Excel files

Cleaning missing data

Data transformation with Pandas

Visualizing data with Seaborn/Matplotlib

This is the “real work” most data scientists do daily.

🧬 Step 4: Learn Machine Learning (ML)

Once you’re solid with data handling, dive into ML.

Start with:

Supervised learning (Linear Regression, Decision Trees, KNN)

Unsupervised learning (Clustering)

Model evaluation metrics (accuracy, recall, precision)

Toolkits: Scikit-learn, XGBoost

🚀 Step 5: Work on Real Projects

Projects are what make your resume pop.

Try solving:

Customer churn

Sales forecasting

Sentiment analysis

Fraud detection

Pro tip: Document everything on GitHub and write blogs about your process.

✏️ Step 6: Learn SQL and Databases

Data lives in databases. Knowing how to query it with SQL is a must-have skill.

Focus on:

SELECT, JOIN, GROUP BY

Creating and updating tables

Writing nested queries

🌍 Step 7: Understand the Business Side

Data science isn’t just tech. You need to translate insights into decisions.

Learn to:

Tell stories with data (data storytelling)

Build dashboards with tools like Power BI or Tableau

Align your analysis with business goals

🎥 Want a Structured Way to Learn All This?

Instead of guessing what to learn next, check out Intellipaat’s full Data Science course on YouTube. It covers Python, ML, real projects, and everything you need to build job-ready skills.

https://www.youtube.com/watch?v=rxNDw68XcE4

🔄 Final Thoughts

Becoming a data scientist in 2025 is 100% possible — even for beginners. All you need is consistency, a good learning path, and a little curiosity.

Start simple. Build as you go. And let your projects speak louder than your resume.

Drop a comment if you’re starting your journey. And don’t forget to check out the free Intellipaat course to speed up your progress!

[pancakeke]

does anyone have experience confronting their employer about your responsibilities getting wildly out of sync with your job title? my title is supply chain analyst but more than 50% of my work is not supply chain related at all anymore. I'm being treated mostly as a data analyst. data analyst salaries are 10% higher than supply chain analysts salaries in my area plus there are many more job opportunities for data analysts. I want a title change.

also does anyone have experience writing a resume when your responsibilities are not related to your title? should I just say I'm a data analyst because that's the work I'm doing or is there some special section I can add noting secondary work as an unofficial data analyst. there is other shit I do very often too that is barely related to either role.

anyone who has been following me for a while is gonna think I'm sooo late to this realization but it's getting pretty clear to me that my workplace is not going to stop pushing me into roles that I'm not appropriately compensated for, and because these roles are not official I will never receive any support, even when I explicitly request it. I have already been denied support multiple times.

this isn't just random people asking me to do one-time odd jobs either. our COO, CFO, and multiple directors ask me directly to do shit like investigate errors in our website and its tools to uncover what is causing data to display incorrectly. this is to shift labor off our web dev team and onto me, why us paid way less than a developer. I do NOT know ANY programming, I just know the database. this has happened five or six times now.

I also manage customer issues directly with the customers because our sales team does not appropriately train anyone in their department. I create orders for them too because they can not be trusted to enter them (not because they're untrained, but because they were not entering these intentionally). I provide records and reporting for accounting audits. I build weird calculators and generators in Excel for every department except two (IT and web dev) because those two can't justify devoting time to those projects and integrating them into our site. I create extremely weird queries to trace information that out database does not track appropriately (and this will never be fixed).

there are zero docs for anything I do except the ones I personally wrote, and only very limited notes scattered around. I was never trained and only picked sql and stuff up cause when I was a buyer digging into data helped me solve problems more efficiently. I have been begging web dev to tell me when they update anything because they keep breaking extremely serious tools but they have been ghosting me entirely. literally all they have to do is CC me on update emails but they won't do it.

also there isn't anyone else in the company who is proficient in sql and stuff (outside dev, and they're miles above me) to back me up so if I'm overloaded or need other help I'm shit out of luck. this makes taking PTO a fucking nightmare too because I'm always in the middle of helping someone out of a fucking fire and everyone does that shit where they say I can take PTO any time I want without worrying but then constantly assign me with critical tasks and demand results asap.

It is beyond time for me to be realistic about this job and what I want to do with myself 40 hours a week until I die, so I need to start working toward either making my current situation more tolerable or going elsewhere.

[adhdnursegoat]

Episode 2

Word Count: 9.2k

Content Warning: none right now

Pairing: Edward Nashton X OC Romy Winslow

Setting: Pre-Arkham Origins; 2013

─── [ sequence: loading ] ───

Tuesday, December 18th, 2012

Something isn’t right.

Edward narrowed his eyes at the screen, the onyx and emerald glow casting hard shadows across his face, deepening the lines of ever-present ire. The dataset sprawled before him, tangled, disorganized, and inefficient—a perfect mirror of the Gotham City Police Department itself. 

For years, the GCPD’s reputation for sloppy documentation had been almost impressive in its own way, as if this endless mess were some grand tradition they upheld out of sheer spite for change. Crime logs scrawled hastily, half-formed incident reports lost in the shuffle of physical files, a scattering of disjointed data without a semblance of order or care. And now, all of it had fallen to him.

The so-called “cybercrime division” was practically a joke before he arrived, a name slapped on an old, cluttered storage room. Its single, flickering fluorescent light buzzed overhead like a dying insect; its lone, wheezing computer, so ancient it sounded like it was about to take off the first time he powered it on. It had taken him months to convince the precinct to let him install even basic equipment, months of tolerating the grinding fan and a monitor that crackled whenever he turned it on. He had even bought and collected his own equipment to help do their job for them.

But now, he had slowly, painstakingly transformed the place, pulling it from the brink of irrelevance.

He was the GCPD’s cybercrime division. And, if he were honest, he’d rather it be this way.

The first task had been nothing short of brutal, a punishment only someone as patient—or as obsessively thorough—as him could withstand. He had spent weeks, months even, combing through stacks of paper files that had yellowed with age, pulling arrest records, crime logs, and incident reports from years past, each entry a piece of Gotham’s history filed with indifference and half-hearted effort.

But that was just the beginning.

Once the data had been extracted and uploaded into a digital system, Edward moved to the next step: cleaning it. He combed through each entry, scrubbing it clean of mistakes, standardizing formats, deleting duplicates, and filling in the blanks left by years of neglect. It was an endless process, every correction a small battle against the chaos that had festered there long before his arrival. The work had been like sculpting—he chipped away at it, day by day, until the rough edges began to take shape.

With the groundwork set, he had turned his attention to the architecture itself. The system he was building would become Gotham’s digital skeleton, a structure capable of supporting and, eventually, predicting the city’s crimes. He designed SQL databases from the ground up, creating logical tables for every critical piece of data: incident types, time of day, locations, affiliations, every detail that could build a comprehensive picture of Gotham’s criminal underworld. Each table was linked, connected, and cross-referenced in ways that only he fully understood.

He wrote queries that could pull up crime histories, correlate locations, and flag patterns—all in the blink of an eye. Every inch of it had been optimized, refined, and customized, honed to be faster, sharper, and more intuitive than anything the department had ever seen. It was a framework only he knew how to navigate, the kind of code that would baffle even the most tech-savvy officer.

But this was Gotham.

Data alone wasn’t enough; the system needed security—a wall strong enough to withstand the city’s relentless forces. He had spent countless nights implementing layer upon layer of protection, configuring firewalls, building encryption protocols so complex that even he would struggle to undo them. Each file, each report, each encrypted string had become a piece of his fortress. He was transforming this forgotten room into a stronghold, its walls fortified against any threat that dared to infiltrate. Only he held the keys, and only he knew which locks he’d installed.

Then the real work had begun.

Once he had established a patent data flow in the system, he had started layering in more complex tools—predictive algorithms and crime prediction models that mapped Gotham’s streets like veins, arteries pulsing with the city’s crime. He had used regression analysis to find trends, drawing connections between crimes that no one else had even considered. He mapped crime incidents to temporal and spatial data, forming a pattern that gave him a lens into Gotham’s soul. 

But the GCPD couldn’t understand raw numbers—not the way he did. They needed visuals, pretty pictures, something digestible for their mushy minds. So he had built dashboards and reports, simple yet elegant, that displayed his work in colorful heat maps, time-series analyses, and relational charts. Even Gotham’s least tech-savvy officers could click through the data now, though they hardly knew what they were looking at. But Edward did. He could track hotspots, watch the swell of crime ebbing and flowing unlike anyone else.

Each day, as the system grew, he had refined it further. He ran diagnostics, tweaked scripts, and checked logs to ensure there were no breaches, no unexpected bugs. Every piece of data was backed up, replicated on secure servers, ready to be restored at a moment’s notice if Gotham’s chaos took a swipe at his work. And if it did, he would be prepared. Because this was more than a job; this was his creation, his legacy.

With every keystroke, every security protocol, every predictive model, he built a machine that made Gotham’s chaos readable, its patterns decipherable, and its secrets… well, not so secret.

Until a few days ago, his work had seemed routine—a necessary but unglamorous role. But then something unusual had caught his attention: a pattern in the officer response logs.

Every month, he reviewed the logs. It was a habit, part of his meticulous nature. Until recently, there had been nothing unexpected. But now, a repeated anomaly had begun to emerge. Certain neighborhoods showed response times that were curiously high, particularly in cases involving specific types of violent crimes—kidnappings, assaults, even homicides. In other areas, responses to similar crimes were fast, efficient, predictable. Yet, in these particular zones, it was as if time slowed.

He had noticed response times of fifteen, even twenty minutes, where they would typically average around five.

It was subtle, barely noticeable at first. Most people would have brushed it off as a glitch or user error. But Edward Nashton was not most people—and “user error” was not in his personal vocabulary.

“What if…” he muttered, pulling up a fresh SQL query and setting filters for crimes tagged as high-priority in those specific neighborhoods. His fingers flew across the keyboard as he added parameters, refining the search.

SELECT Neighborhood, AVG(Response_Time) AS Avg_Response 

FROM Incident_Reports 

WHERE Crime_Type = 'High-Priority' 

GROUP BY Neighborhood;

The query ran, and Edward leaned forward, his glasses catching the glow of the screen as rows of data populated in rapid succession. A comparison of average response times across all The data stared back at him, validating his suspicions. The averages for these neighborhoods were well outside the norm. Frowning, he created a quick bar chart to visualize the data, and there it was—a spike in response times, glaringly obvious, almost like a neon sign begging for someone to notice.

What’s more, the pattern seemed to correlate with the involvement of certain officers. He drilled down further, narrowing the logs to responses where these outlier times were recorded, and sure enough, the same handful of officers’ IDs kept appearing. At least three officers, in particular, showed up again and again, logged as the responding parties in incidents with suspiciously delayed responses:

Edison, James

Hartley, Jack

Murphy, Curtis

Edward leaned back, his lips twitching to the side in a faint sneer. Gotham’s filth didn’t just rest on its streets—it was deeply embedded within the very department meant to protect it. This pattern wasn’t accidental. The slow responses weren’t random errors; they were deliberate, selectively applied.

For the first time in months, Edward felt the rush of excitement he’d been craving since joining the GCPD. This wasn’t just data compilation or trend analysis anymore. He had uncovered something substantial, something buried, waiting to be unearthed. It wasn’t just about numbers; this was a deeper, darker game involving the very people entrusted with Gotham’s safety.

This wasn’t merely an inconsistency. It was corruption, plain and simple, hiding in the numbers. And if there was one thing Edward Nashton excelled at, it was peeling back layers to expose the truth lurking beneath.

The screen flickered faintly, his cursor hovering over rows of data as his mind picked apart the patterns, noticing every inconsistency, every shred of deception. This wasn’t an error or some accidental miscalculation. No, what he saw here was intentional—something deliberate and dark slipping under the radar, a clear thread of corruption woven into the fabric of Gotham’s police force.

If anyone could expose it, could tug at the threads until it unraveled into undeniable truth, it was him. The thought sent a thrill down his spine, a familiar surge of satisfaction that came with knowing he was on the verge of something significant.

Bing!

The sharp notification broke his concentration, dragging his attention to the corner of his monitor where an email preview appeared. Edward’s expression shifted, his lips pressing tight as he read the sender’s name: Commissioner Gillian B. Loeb. A scowl formed before he could stop it, his eyes narrowing behind his glasses. 

“come 2 my office”

The words glared at him. No punctuation, no capitalization—shorthand, as if Loeb couldn’t be bothered with even a semblance of respect. The sheer laziness grated on Edward, adding another layer to his already simmering disdain. Commissioner Loeb might as well have stomped down to his desk and demanded his presence with the same lack of decorum, and Edward doubted he would have been as irked. His lip curled, the faintest twitch of irritation betraying his thoughts.

Edward didn’t have friends here—never had. He didn’t linger by the watercooler, didn’t care for small talk, and had no interest in the routine camaraderie his coworkers indulged in. Loeb, however, wasn’t just a minor irritant like the rest. No, Loeb sat proudly at the top of a list of people Edward preferred to avoid—a list with its own special level of contempt reserved just for him. Loeb’s greed, his smug superiority, the way he flaunted his power as though it were untouchable—it all disgusted Edward. But he wasn’t foolish enough to ignore him.

He drew in a slow breath, pushing back the annoyance as he removed his glasses, his thumb and forefinger pressing firmly against the bridge of his nose. The tightness settling behind his eyes was familiar, a strain born from hours spent at the monitor. He rubbed at it, hoping to ease the creeping fatigue. Forcing himself to release a sigh, he closed his eyes briefly, letting the weight of the task at hand wash over him, clearing his thoughts.

Edward’s eyes flicked back to the fresh data on his screen, teeming with unspoken implications. He could go now, take this to Loeb, drop the details in his lap, and watch the Commissioner squirm. But… no. Not yet. If there was anything he’d learned, it was that timing was everything, and he wanted this case to be “pretty” and clean—undeniable.

With a quiet sigh, he finally pushed back from the desk, his legs and back groaning in protest. The human body wasn’t built for this kind of work, not the endless hours hunched over monitors and squinting at screens. He stretched, lifting his arms until he felt the crack in his shoulders, then rolled his neck, savoring the sharp pop that released some of the tension.

After a final look around his cramped, shadow-filled corner of the storage room, he made his way to the door. The space was dark and dank, with stacks of old case files and barely-functioning equipment shoved into every corner. He’d been asking for more space since the day he arrived, but as long as he remained the sole member of the “cybercrime division,” there was no point—not according to the people holding the budget. He could already imagine their dismissive words, the laughter as they shrugged him off. Why upgrade the closet for one man?

When he opened the door, a different kind of darkness hit him. GCPD’s main floor was lit by the harsh hue of fluorescent lights, casting an unnatural pallor over everything. The grime felt omnipresent, tinging every surface with a layer of wear that no amount of scrubbing could erase. The entire precinct pulsed like a spastic nerve, alive with chaotic energy.

He stepped out, crossing to the bustling bullpen. The layout was predictable—three levels stacked atop one another like a fortress of bureaucracy. A sublevel housed the detained. The main level, where he stood now, held the bullpen at its center, filled with two rows of desks paired off in clusters. Corridors stretched out on the east and west sides of the building, leading to file and evidence rooms, interrogation suites, and break areas.

Officers strolled by with coffee in hand, their conversations blending into the background noise. Detectives leaned against desks, swapping stories and laughing loud enough to be heard across the room. Secretaries rushed from one end of the bullpen to the other, arms stacked with paperwork or balancing phones against their shoulders. Above, the second and third levels housed offices for secretaries and various divisions, their windows glowing faintly in the overhead light.

And above it all, perched on the second-level landing like a throne, was the Commissioner’s office. It loomed over the precinct, a constant reminder of who held power there.

Edward shoved his hands into his pockets, his stride unfaltering, gaze fixed straight ahead. As he wove through the bustling bullpen, the familiar hum of GCPD’s endless chatter faded into a low buzz, a background noise he had long since learned to ignore. He didn’t belong here—not with these people, not with their idle gossip and endless banter. He was here to work, nothing more. And most of the time, they respected that, leaving him alone, unnoticed in the corners of the precinct.

“Dracula has risen!”

Most of the time.

Edward gritted his teeth, his jaw tightening as he caught the grating laughter ringing from behind him. He didn’t break stride, didn’t turn—just kept moving, his hands shoved deep into his pockets, shoulders hunched slightly as if to shield himself from the attention. Just keep moving. He had mastered the art of appearing unbothered, of letting these low-effort taunts roll off him. But Hartley’s voice, dripping with smug familiarity, broke through, just loud enough to draw the attention of a few nearby officers who exchanged knowing looks.

“Naaaashton!” the voice called, drawing out the syllables with exaggerated cheer, as if addressing an old friend. Edward could practically feel the man’s self-satisfied smirk boring into the back of his head. “I’m always surprised to see you out in the sun. More surprised when you don’t burn.”

It was the kind of comment he had grown used to, the small digs Hartley loved to throw his way whenever he passed by. Hartley, with his false bravado and ignorance parading as wit, never missed a chance to turn Edward into the precinct’s punchline.

Officer Jack Hartley—the poster boy of stereotypical “All-American” masculinity, with cobalt eyes and sandy hair, tall and built like he was carved out of an idealized gym catalog, complete with a bulky torso that fanned out into broad shoulders and arms that tapered down in a ‘V’ like an oversized Dorito. A man who would be lost without his badge to wave around and his flexed biceps, displaying that questionable tribal tattoo spiraling down one arm.

Edward kept moving, eyes trained straight ahead, but he allowed himself a sidelong glance, just enough to see Hartley’s smirk and the dumb faces around him. He could feel the heat of their attention, their eyes eagerly watching for his reaction. This time, he didn’t stay silent.

“Hartley,” he replied, his voice sharp and controlled. “I’m always surprised to see you haven’t been fired for your incompetence.”

There was a beat of silence. Edward didn’t stop to savor it, but he caught the reaction—the flicker of embarrassment in Hartley’s expression, the slight widening of his eyes before the scowl settled in. A few snickers rippled through the nearby officers, a sound that only deepened Hartley’s frown. His cheeks flushed slightly, the kind of reaction that Hartley, a man who considered himself untouchable, never expected to feel.

“Oh, you’re a real comedian, aren’t you, Nashton?” Hartley muttered, his voice barely audible now, laced with a gruff edge, the forced comeback of someone unprepared for a response.

Edward didn’t dignify it with another verbal reply. But, to answer the question— no. He wasn’t a comedian. He hated jokes. He only spoke truth. The words, the tiny prick of retaliation, had already done their work, striking just the right note to unsettle Hartley without so much as breaking his stride. He allowed himself to savor it for only a second, a brief and private victory that curled ever so slightly at the corner of his mouth. He knew it was minor, a passing exchange that no one would remember by the end of the day—but that small reminder, that assertion of his own superiority, was more than enough. For Edward, it wasn’t about showing off; it was about reminding himself, and everyone around him, that he was sharper, quicker, and not someone who could be so easily dismissed.

As he steadied his pace toward Loeb’s office, his thoughts drifted to the people around him, each one of them blending into the other like dumb lumps of flesh. Idiots—all of them. The entire precinct was an echo chamber of mediocrity, swollen with officers who took pride in their badges but lacked even a shred of real intellect. They sat at their desks, shuffling papers, swapping jokes, indulging in the hollow camaraderie of shared ignorance. They had no ambition, no hunger for knowledge, no desire to see past the routines they repeated day after day. They were just bodies filling space, a backdrop against which his mind and his skills blazed brighter by contrast.

Each step up the stairs only solidified his distaste. Every click of his shoes against the metal felt like a declaration, a rhythm that reminded him he was alone in a sea of self-satisfied drones. None of them measured up. None of them could measure up. Hartley’s lazy jeers, the way he flexed as if it made him someone important, the way he reveled in the pointless antics of the bullpen—these were the people tasked with keeping Gotham safe. It would have been laughable if it weren’t so tragic.

His eyes stayed fixed ahead, not sparing a single glance back at the bullpen. He had no reason to look, no interest in indulging the officers’ empty stares or their shared smirks. They were beneath him, irrelevant to his purpose, and the thought only strengthened his resolve as he approached Loeb’s office.

When he reached the landing, Edward straightened, pulling himself up to his full height, his fingers brushing over the door handle. He spared no glances to the bullpen below as he entered the Commissioner’s office and shut the door behind him with a soft click. 

The room was a display of power—ornate but garish, every detail chosen for intimidation rather than taste. Heavy mahogany furniture dominated the space, the Commissioner’s oversized desk an imposing centerpiece cluttered with papers and a gleaming nameplate. The walls were lined with plaques and framed commendations, their polished surfaces reflecting the faint light from a brass floor lamp in the corner. A thick, dark green carpet muffled Edward’s steps as he moved further inside, the smell of old leather and cigar smoke lingering in the air like a stain. Behind Loeb, floor-to-ceiling windows framed the grimy skyline of Gotham, their blinds half-drawn, letting in just enough gray light to make the space feel oppressive rather than bright. The office was a monument to its occupant’s ego—a fortress designed to remind anyone who entered exactly who held the power here.

The old man, standing at the windows, barely glanced over his shoulder to see Edward enter. “Sit.”

Edward frowned but did as he was told. Then he waited. And waited. And waited some more. Loeb’s stance, hands clasped firmly behind his back, suggested authority—or, more precisely, a performance of it. Edward couldn’t tell if the Commissioner was actually observing anything down on the street or merely pretending to do so, basking in his own bloated sense of importance. The stance, the imperious tone, the refusal to even acknowledge him face-to-face—every detail screamed a carefully curated aura of authority. Loeb stood as if by habit, a fossil of bureaucratic pomposity, clinging to a legacy of hollow power.

The man himself was almost a caricature, the embodiment of the department’s rot. His body strained against his uniform, seams puckered and pulled tight around his frame. The cap on his head dug visibly into his pallid skin, leaving an indentation along his brow, a mark of fluid retention only emphasized by the puffiness of his jowls. Loeb was thick-necked, with sagging skin that folded around his face in a way that resembled a bulldog’s. The clubbed fingers clasped at his back gave away years of heart strain, his slow circulation, and unchecked lifestyle, further evident in the labored rise and fall of his shoulders. He was an uncomfortable-looking man, like a worn-out relic forced into a role it no longer fit.

Edward glanced at his watch.

At last, the coot deigned to speak.

“Nashton,” the Commissioner quipped, “you’ll be getting a student.” His tone brooked no argument.

Gillian Loeb finally turned from the window, taking heavy, unhurried steps toward the desk, his movements sluggish, a body too tired to fully lift its feet from the floor. The scuffing of his shoes against the linoleum was maddeningly loud in the otherwise silent office, each step punctuated by his labored breath—a rasping sound that filled the room, making his presence that much harder to ignore. He reached his desk, his eyes narrowing just enough to convey irritation, perhaps at the exertion of moving across the room. With a relieved huff, he lowered himself into the worn red leather chair behind his desk, and it groaned under his weight, the sound of old leather and strained springs filling the air.

Edward resented being voluntold for anything, especially by a man who likely couldn’t navigate a basic search engine. But what choice did he have? Loeb’s words, dripping with condescension, only served to deepen Edward’s frown. He shifted in the stiff wooden chair opposite the Commissioner’s desk. He crossed his arms, fingers digging into his elbows as he suppressed the urge to roll his eyes. The impatience was barely masked—an edge to his expression that spoke volumes to anyone perceptive enough to notice. Loeb, of course, was not.

Then, the Commissioner began his speech, one that had likely been rehearsed, perhaps at his morning mirror. His voice rolled through the room, slow and full, each word dragging as he introduced the “exciting new work-study program.” Edward’s eyes flickered, resisting the urge to visibly wince as Loeb stressed the importance of “investing in someone’s future with the GCPD.” It was predictable, even painfully so, and Edward could practically see through Loeb’s words to the core of it: this so-called initiative was just a thinly veiled scheme, some tax break or budget cut disguised as a benefit to the community.

He was not naïve. He didn’t need the specifics to understand how the department operated. The GCPD’s funding, already stretched thin, had likely prompted this decision. The idea of a “program” that would cost them next to nothing while earning them goodwill with Gotham’s public was probably irresistible to the old bureaucrat. With students desperate for experience, the department could add another set of hands—hands they wouldn’t even have to pay. To Loeb, it was a flawless plan.

Edward’s leg bounced lightly as Loeb continued, the man oblivious to his impatience. Loeb droned on about the value of “real-world experience,” his words as empty as the promises they contained. Edward had read enough department memos and budget drafts to know the truth. This wasn’t about nurturing young talent or providing mentorship. It was about creating a self-serving “opportunity” that the GCPD could tout in press releases.

Loeb, meanwhile, was fully immersed in his monologue, clasping his hands as he expounded upon the program’s “benefits.” There was a look of smug satisfaction on his face, as if he were certain Edward should be grateful for the “honor” of mentoring this student. Edward could feel his jaw clenching, the tension in his arms building as he listened to the Commissioner pontificate about the duty of guiding someone who “could be the future of Gotham’s finest.”

Finally, Loeb paused, and Edward seized the chance to speak., his voice level, measured. “And this ‘student’ is supposed to assist me?”

“Yes, precisely.”

“I highly doubt they would be of any assistance, Commissioner.” Edward had a difficult time barring the condescension in his voice.

“You should be thankful.” Loeb narrowed his beady brown eyes at him. “Think of it as… additional help. Someone who can shoulder some of the workload.”

The Commissioner said it as if he were doing him a favor. Pfft. Edward knew better. He wasn’t being given a protégé; he was being saddled with an amateur who would inevitably fumble through tasks, leaving him to clean up the mess. More work—that’s what this was. The idea of a student trying to “help” in his field felt like a bad joke. He had spent a year refining his division—every system, every dataset was his creation. The thought of letting some kid handle even a fraction of it filled him with a quiet dread, like watching someone try to operate a complex machine without understanding a single gear.

Loeb shifted in his chair, taking Edward’s silence as agreement. “The youth these days, Nashton. They’re the future, and we have a duty to mold them. The department sees this as an investment. Someone to eventually join your endeavors full time.”

Edward’s jaw tightened. Investment? He couldn’t help but smirk slightly at the absurdity. Loeb had no real idea what Edward did, no real grasp of the complexity his work required. In Loeb’s mind, a student could simply step in and soak up skills like a sponge. But Edward knew better. To him, this wasn’t an investment; it was a hindrance, a risk of inefficiency, and the last thing he needed.

But with Loeb’s expectant gaze bearing down on him, he understood the futility of voicing his concerns. The decision had been made, probably long before he was even called into this office. He wasn’t being given a choice—he was being told to fall in line.

“We’ve got some candidates lined up. You narrow it down, and we’ll finalize it.”

Loeb pushed a stack of russet-colored folders toward him, and Edward suppressed a sigh as he unfurled his arms, grabbed the stack, and flipped open the first file. The pages were full of redacted lines—names, ages, and even genders all neatly blacked out. He rolled his eyes. There were pages of transcripts, an accompanying essay (which he was not going to read), academic achievements, extracurriculars, and sanitized letters of recommendation, none of which told him anything interesting.

Edward felt the familiar dull boredom creep in.

He eyed the first profile, scanning each line with a growing sense of irritation. Harvard, it read in bold letters, as if the word alone signified worth. Straight As, a laundry list of commendations from professors who probably barely knew this student beyond the name printed on their assignments. It was the kind of profile built from legacy admissions, expensive prep schools, and connections more valuable than skill. Every accolade, every honor felt manufactured, the result of privilege rather than grit or true intelligence. This was the sort of person whose future had been paid for, gift-wrapped, and delivered to them on a silver platter. A pawn that had been moved through life’s chessboard with no actual understanding of the game.

Edward flipped to the next file, another profile reeking of the same glossy, untarnished perfection: a prestigious background, impeccable grades, extracurriculars that spoke more to showmanship than substance. His lip curled, an almost imperceptible twist of disdain. What use was someone like this to him? He didn’t need another pre-packaged prodigy, the type who had been endlessly praised but never challenged, the kind who breezed through academia without ever truly understanding what it meant to think, to analyze, to push limits. He needed someone who had actually had to work for something, who had seen struggle, who understood what it meant to build something from scratch—someone with the kind of determination that couldn’t be bought.

These files in front of him represented everything he despised about the world: the hollow merit of titles, the pretense of excellence. It was the kind of privilege that relied on appearances rather than substance, and it left a sour taste in his mouth. He flipped through each one with growing impatience, each page a carbon copy of the last, all polished to an empty sheen that hid any real substance.

His gaze sharpened as he closed another file. What he wanted, if he was to have an assistant, was someone with actual mettle. Someone with grit, someone who hadn’t had everything handed to them. The kind of candidate who could be taught something beyond the regurgitated lessons of privilege. Edward’s jaw tightened as he tossed the files back onto the desk before grabbing another file near the bottom of the stack.

When he opened this one, he cocked a brow. Something caught his eye.

There was an entry—a two-month juvenile record attached to a high school transcript from their junior year. Edward’s interest piqued immediately. He leaned back in the chair, letting the file rest in his fingers as he read the details. The record noted a hacking incident: unauthorized access to school servers to alter grades. He almost chuckled, finding this much more intriguing than the immaculate résumés of Ivy League candidates.

The report stated they had felt their grades were given unfairly and decided to take matters into their own hands. It was an act of rebellion, yes, but also one of precision and calculation. They hadn’t sabotaged the system—they had simply revised their grades without damaging any other records or erasing traces of the hack. There was a comment from a principal decrying the act as undermining the school’s “integrity” and a record of a lengthy expulsion hearing. Yet, despite this incident, there were a handful of letters from teachers who seemed reluctant to give up on them.

He read further, finding notes on their turnaround at their senior year and at Gotham City Community College. After high school, it seemed no other institution had wanted to take a chance on them, except for this one. But instead of coasting through, they had thrived—joining the debate team, earning honors, and eventually transferring to Gotham University. Now they were a college senior majoring in computer science with a minor in criminal justice.

As he skimmed through the final notes, Edward smirked. This work-study tied directly into their capstone project—a predictive AI programmed to determine when and where crimes were more likely to occur. It was a smart move, one that showed ambition and resilience. They were not another cookie-cutter success story from an Ivy League—they were someone who had clawed their way out of a mess, took risks, and kept climbing. Whoever they were, they were far more intriguing than the other candidates. He didn’t need some entitled, bougie fraternity brat who would think they were smarter than him.

He closed the file with a soft pat, already deciding. He flicked it onto the desk with an air of indifference and slid to a stop in front of Loeb. “This one,” he said flatly.

The Commissioner picked up the folder, his thick fingers fumbling with the dry edges as he peeled it open. His brow furrowed deeper as he read, and he shot Edward a wary look over the papers. “This one? The one with the juvie record? Are you sure?”

Edward’s expression remained cool, detached. “It’s either this one or none at all,” he replied without missing a beat.

Loeb stared at him for a moment, rubbing his jaw, clearly weighing his options. After a long pause, he sighed and tossed the file back on the desk with a resigned grunt. “Fine,” he muttered. “They’ll be here after the holidays.”

─── [ sequence: loading ] ───

In under a month’s time, Edward Nashton found himself caught off guard.

It was not often he was caught off guard, and he did not like it.

He was hunched over his workstation, eyes narrowed as he sifted through lines of encrypted data. It was after lunch, during which he had remained in his space, still working, forgoing eating as he normally did. His office, if one could call it that, was a windowless space in a back corner of the GCPD headquarters, dimly lit and reeking of stale coffee and burnt-out ambition. It was crammed with outdated computers and stacks of scattered papers, the sort of place where Edward thrived in isolation. He was so absorbed in his task that when the door opened and a knock sounded on the doorframe, he muttered, “Yes?” without looking up, already bracing himself for another mundane IT request—misguided souls thinking that the "computer guy" could fix the printer.

But then an unfamiliar voice responded.

“Excuse me? Are you Mr. Edward Nashton?”

It was not the tone he expected—there was no hint of impatience or condescension, which he had grown accustomed to when people sought him out. The voice was feminine, with an even pitch, its calm, smokey cadence infiltrating the monotony of his work. It was an unobtrusive sound, yet so unusual to his ears that he was compelled to see who it belonged to. He looked up. He froze.

A girl was standing at the doorway, her fingers resting lightly on the doorframe as if unsure whether to fully step inside. He had not even heard the door open.

Edward frowned.

His first impression of her was one of dissonance—a sharp, almost unsettling contrast between her and the office she had just entered. The grimy, worn-down precinct felt even darker with her in it, as if the dingy fluorescent lights themselves were suddenly more aware of their inadequacy.

She was beautiful—irritatingly so. Her long, sleek dark hair fell like silk curtains, parted perfectly down the middle, framing her face with an effortless elegance that didn’t belong anywhere near the GCPD. Her eyes, lined meticulously with dark, precise wings, were fixed on him with a hint of amusement. There was a different energy to her, one that felt deliberate, almost as though she knew exactly how out of place she looked and was inviting him to react. He barely realized how long he held her gaze.

With a faint scowl, he forced himself to look away, taking in the rest of her with a detached, analytical eye. Her lavender blazer dress caught what little light there was, gold buttons glinting as they drew a subtle line down her figure. The hem stopped just short of professional modesty, skirting the edge of propriety with a cut that was as tailored as it was daring. She had a designer bag slung over her shoulder, a fuzzy purple notebook and a gray-and-pink plaid winter coat clutched in the same hand, and she was only one chihuahua short of being GCPD’s own Elle Woods.

This office hadn’t seen anything like her, and by the looks of it, she was fully aware of that fact. For a moment, he wondered if she was mocking the precinct in her own way, challenging the drab confines of the facility with something so polished, so perfectly styled. 

His thoughts were cut short by the sound of her clearing her throat, and his eyes snapped back to hers. He realized with sudden embarrassment that she had caught him staring. Worse, she was smirking—her lips shiny and curved in an almost mocking acknowledgment of his mistake.

“Yes,” he said stiffly, clearing his own throat in a failed attempt to reestablish control. “And who might you be?”

“I’m your student, Romy. Romy Winslow.”  Her half-lidded eyes seemed to smolder in the low lighting.

“Student?” Edward repeated, the word coming out more as a question than he intended.

“Yeah,” she nodded. “Like, they told you, right?”

“Of course,” Edward grumbled, scrambling to regain some semblance of authority. He wasn’t used to feeling unprepared, especially not in his own domain.

He did not like when Romy pursed her shiny lips and narrowed her eyes. “You forgot, didn’t you?” she pressed, a teasing lilt to her voice.

Edward’s back straightened, jaw tightening. “You will soon find that I forget nothing, girl,” he quipped. “I’m merely intrigued by your—” he gestured vaguely at her—“appearance. Are you sure your silly little head didn’t get confused? Got lost on your way to a sorority luncheon?”

Romy blinked. She checked her smartwatch, then looked back at him and tilted her head, the innocent confusion in her eyes seeming a little too thoughtful to be genuine. “No… The Greek Meet isn’t until Saturday.”

He frowned.

Oh, she was definitely fucking with him.

Soon, her pink lips pursed in a slight pout, and she glanced down at herself. “Is it too much?”

As she turned to the side, Romy casually modeled her silhouette, the lavender fabric clinging to her form in a way that was both tasteful and tantalizing. The movement drew Edward’s attention, his gaze instinctively tracing her figure. He couldn’t help but follow the curve of her form, from her shoulders that tapered elegantly down to the delicate arch of her spine, and finally to her shapely backside, perfectly showcased by the tailored fit of the dress. He resented that his gaze followed the lines of her legs, made even longer by the gray knee-high, heeled boots she had chosen.  Each line was accentuated with precision.

She caught his eye again, her expression playful yet somehow earnest. “I thought it was just the right amount of business meets pleasure.”

Edward cleared his throat. “Not quite what I was talking about,” he muttered, his gaze darting away in an attempt to collect his thoughts.

“What did you mean then?” Romy asked as she stepped further into the room. She glanced around, her nose wrinkling slightly at the sight of the meticulously stacked boxes of files, outdated monitors, and blinking fluorescent lights. “This is the GCPD Cybercrime Division?” she asked in an offhand manner. “This looks very—” she wriggled her fingers at the general space “—humble.” Though she smiled, it was clear she was struggling to be polite.

“I mean that I did not expect someone so— soft.” He glanced around the area, grimacing at the— as she called it—‘humble’ surroundings. “It is what it is.”

“You mean you didn’t expect a girl?”

“Yes,” he admitted, refusing to dance around it.

“Well,” she said with a shrug, “guess we both had false expectations of the situation, Mr. Nashton.”

Edward felt the frustration building, both at himself and at Romy’s unsettling confidence. “And what exactly did you expect?” he retorted, his eyebrow cocking. “Quantico?”

She smirked, but the movement was subtle, a brief twitch at the corner of her lips. “No.” Her fingers traced over the edge of a dusty computer monitor, her almond-shaped nails—a soft mint green—making the action seem delicate. “But, like,  maybe I expected something a little more contemporary than this, I suppose.”

He bristled at the unintentional insult to his sanctuary of cobbled-together tech that he had spent the better part of a year collecting to upgrade this dump. He found himself oddly off-balance, grappling with the realization that he had expected someone completely different. Someone less refined, more—unpolished. But here she was, her demeanor perfectly maintained in a lavender blazer dress, with the confidence of someone used to catching others off guard.

He did not like it. He did not like how she acted. He did not like how she talked. He did not like what she said. He did not like how she looked. He did not like her.

Edward sat behind his uncluttered desk, arms folded as he leaned back in his creaky chair, eyes narrowing at her. “The GCPD still does not see the full benefit of a cybercrime division,” he said, his voice laced with a bitterness that hinted at more than just professional frustration. He was used to his work being sidelined, his expertise disregarded by those who should know better. Her arrival was yet another inconvenience in a long line of offenses. “These bald apes are content to remain in the twentieth century.”

Trailing closer, she soon sat in a nearby chair, setting her belongings on a table crowded with equipment. “Quite the shame,” she replied, crossing one leg over the other as she settled into the seat he did not offer her to sit in. “I was hoping to gain some valuable expertise before graduating. I wanted to work here in fact.” There’s a glimmer of amusement in her eyes and her voice holds a polite, measured tone.  “My professors said you are brilliant.”

Smug satisfaction settled in his chest. 

“I am.” Edward’s lip curled ever so slightly, and he straightened, giving her a half-lidded look. 

Romy looked at him for a moment before speaking. “They said you were difficult too.”

“Who’s they?’”

“Duncan and Hadley.”

Edward’s eyes narrowed at the mention of his old professors, the faint smugness that had crept into his expression now sharpening into something colder, more cutting. He studied her with a slow, deliberate gaze. This close, he can finally see her eyes—a moss green

“Duncan and Hadley,” he repeated, his tone laced with disdain. “Duncan—let me guess—still regurgitating decades-old theories as if they’re groundbreaking revelations? And Hadley…” He sneered faintly, his lip curling. “Hadley’s what happens when tenure protects the incompetent. Is he still using Windows XP?”

“Unfortunately… They had strong opinions about you as well,” Romy remarked lightly, looking at her nails in an absent minded manner.

“I’m sure they did,” Edward replied smoothly, sitting forward now, his elbows resting on his desk as he leveled her with a pointed look. “Professors like them always do when confronted with someone who doesn’t just color outside their precious lines but redraws the entire picture. Of course, to them, that’s ‘difficult.’”

Her lips quirked at one side and she rested her chin on her hand, watching him with an amused air. “Then it seems I made the right decision to come to you.”

“While it would undoubtedly be an honor for you to work with someone of my genius firsthand,” Edward continued, his voice dripping with confidence as he narrowed his gaze at her, “you won’t stand a chance.”

Romy merely tilted her head, watching him with an expression of calm intrigue, seemingly unbothered by the sharp bite of his words. It unnerved him more than he cared to admit. He wasn’t used to this feeling, least of all in his own space.

“I’m used to people underestimating me, Mr. Nashton.”

“My estimations are always accurate,” he continued, his voice sharper now. He sighed giving her a bored look. “Let’s cut to it, I suppose.” He let one of his hands rest on the desk. “You will only get in my way. I don’t want to waste my time or my breath educating you on something that will likely go in one ear and out the other.” He tapped his fingers against the tabletop in a measured way, his voice cold. “You are to sit, stay, and not move. Don’t touch anything else. You can watch, and maybe, just maybe , you might be graced with a touch of my intellect... One would only be so lucky to have someone of my caliber rub off on them.”

Before Romy responded, there was a slight twitch of her perfectly plucked brow. “... Do you like to rub off on people, Mr. Nashton?”

He blinked, absorbing what she had just said. Rub off, he thought dryly. Clever, very clever. But what really stopped him wasn’t the phrasing; it was the look in her eyes—a knowing, steady gaze that held him longer than it should. There was a flicker of challenge there, of cool confidence, that made him shift in his seat, uncomfortable under the weight of that steady, unflinching stare.

“You know exactly what I mean, girl,” Edward snapped. He fixed Romy with a squint. “I can see you are going to be quite the pain in my ass, aren’t you?”

Romy’s lips twitched as she considered him with sharp eyes. “Oh, no, not at all,” she lilted. “I’m actually trying to make a good impression.”

He watched as she relaxed her slender hands on the arms of the chair, mint green nails clicking once on the wood. Then, when she crossed her legs, it was a slow movement. His attention flicked to her shapely thighs, noting how the lavender hem of her dress raised slightly with the movement. His frown deepened, brows knitting together, and then he looked back at her easy gaze.

“And how do you plan on doing that?” he asked.

Her eyes flicked across his face, and she hummed thoughtfully, obviously thinking about her answer. Then, a slow smirk stretched across her shiny, plush lips, and those young eyes of hers glittered with amusement. She clicked her tongue. “By being quiet, submissive, and obedient…”

Immediately, Edward felt the heat rise, an unbidden flush creeping up his neck and settling under his collar. He resented it, and his jaw tightened in frustration. She leaned back in the chair, her lips curling into that slow, deliberate smirk, and something glittered in her gaze. The subtle bite to her lip—did she even realize she was doing it?—and the way she settled back, so at ease, as if she were testing him, watching to see how he’d react. It was maddening. There was no reason to let a stranger, much less a student, get under his skin.

He kept his tone even, measured. “I have a hard time believing that,” he said with forced calm. “You are already disrupting my workflow by being here. I don’t have the time or interest to indulge anyone’s… antics.”

“Antics?” Romy repeated. “So, like, you assume I’m here to waste your time? That I won’t take this seriously?”

Edward smirked. “Well, if it looks like a duck and talks like a duck,” he chided, not at all masking the disdain in his voice.

Her smile sharpened. “Except when it’s a unicorn,” she simpered, lashes fluttering as she peered at him through half-lidded eyes. “Is that it, Mr. Nashton? Is it because I’m not some acne-riddled, snot-nose, basement incel?” She tilted her head to the side, her long black hair shifting with the movement, and she narrowed her gaze. “Is it because I’m pretty… ?”

The question struck him off balance. He realized he’d been observing every inch of her carefully put-together appearance, struggling to reconcile it with the notion that Commissioner Loeb thought it fit to place her here with him. But Loeb had been unaware of the candidates as well. The disconnect irritated him, the softness of her expression and the sharpness of her words stirring something hot in his chest.

“Listen, little girl,” he sneered, mustering every ounce of cold detachment, “I don’t know what game you’re trying to play, but I’m not the one to challenge.”

Romy’s smile widened, the look in her eyes unmistakably daring. “Oh, I don’t know about that,” she said, letting her voice dip playfully. “You seem like exactly the kind of man to enjoy a good challenge.” She tapped a nail thoughtfully on the wooden chair arm. “Or am I wrong?”

“Challenges are acceptable,” Edward said, his lips twitching as though considering a smile, though his gaze remained guarded. “But only those that actually require intellect. Challenges that flex the mind… not distractions.”

“So, that’s what you see me as? A distraction?” Romy tilted her chin up, looking at him with that gaze that made her look so cool. It only grated on his nerves. “I’ll make sure to cover my shoulders and hide my bra straps then.”

Edward’s eyes narrowed. He opened his mouth to retort, but she was faster, leaning in with a look that was half-sweet, half-mischievous. “Unless, of course…” she purred, “a little distraction is exactly what you need. Maybe it would loosen you up.”

“Loosen up?” he echoed, his voice edged with forced calm. “I don’t need to loosen up. I need focus and productivity, two qualities I have a hard time believing you possess.”

“I have plenty of focus.” She settled back in her chair, unabashedly grinning at his obvious discomfort. “I’m sure we’ll make a… productive team, Mr. Nashton.”

He exhaled slowly, trying to maintain his composure. “You’re insufferably confident, aren’t you?”

“Pot meet kettle,” she replied breezily, gesturing in a casual manner, clearly unbothered by his barbs. “So… are you ready to be impressed, or are we going to keep up the foreplay?”

Edward rolled his eyes then shifted and spun back to his computer. “ Fine,” he said tightly. “You want to prove yourself? Then start by doing exactly what I tell you, without the smart commentary, Ms. Winslow.” He made movements to bring up his work, his fingers tapping away at the keyboard.

She shifted to the side, her eyes gleaming with a playful challenge as she retrieved a sleek laptop from her purse. “Yes, Mr. Nashton, sir.”

His fingers stalled over the keyboard, his usual fluidity momentarily broken. A shiver ran down his spine, slithering low. It made him grit his teeth.

With a deep inhale and an exasperated sigh, he settled into his work, typing with the familiar, precise rhythm he was known for. While he maintained perfect focus, he couldn’t shake the uncomfortable feeling of having someone in his space. He worked alone. He had never had to precept anyone. He was not a teacher. He didn’t have the patience nor the desire for it. Professors had tried setting him up to tutor during his time in college—it hadn’t worked out as they thought it would. It had taken only one time to make someone cry for them to decide teamwork might not be something for him.

He felt it inevitable: Romy would say something completely idiotic; he would correct her; it would hurt her puny little feelings; she would cry; she would quit; and he would never have to hear from her again.

All he had to do was bide his time. He could be patient… when he wanted to be.

But, as much as it stung to admit, Romy surprised him. She was quiet—perfectly quiet, almost too quiet—and she seemed wholly absorbed in what he was doing. It was almost like she didn’t exist.

The minutes stretched, long and quiet, with nothing but the soft hum of computers and the steady beat of typing filling the air. Twenty minutes slipped into thirty, and then an hour, and still, she remained there, intently focused. The steadiness of her gaze as it flickered between her screen, his screen, and his hands—the unwavering attention she devoted to each click, each keystroke—was almost unnerving. There was something in the way she was present, so completely engaged, that felt oddly invasive. And yet, she wasn’t disruptive. She didn’t give any more snarky quips. She didn’t sigh in boredom. She didn’t ask questions or interrupt with idle conversation, simply watching, occasionally typing, the rhythm of her own keystrokes echoing his in a strange, synchronized cadence.

But it was the sound of her nails that really got to him. Each click of the keys under her fingers was punctuated by the sharper snap of those mint-colored acrylics atop them, a sound somehow distinct from the natural clack of a keyboard. It wasn’t irritating—not yet—but he sensed the potential. It was the kind of sound that, over time, could likely chip away at his concentration, like Chinese water torture, each click burrowing into his awareness with grating persistence.

Every now and then, Edward risked a glance at Romy, expecting to catch her on her phone or zoned out, ready to dismiss the task at hand. But she stayed. She was observant, her posture straight, fingers poised and ready, and she took in every word, every glance he spared her, without saying a thing—only a simple nod here and there in respectful acknowledgment. 

The hours slipped by faster than usual, her silence still unbroken. Edward leaned back, cracking his knuckles and flexing his fingers, savoring the temporary reprieve. But as he shifted, his eyes caught movement—Romy, standing right in front of his desk.

He jolted, a sharp intake of breath betraying his surprise. He hadn’t even heard her move.

“ What?” he snapped, his voice tight. “What do you want, girl?”

She blinked, glancing at her watch with maddening calm. “Time to go home.”

It was only then that he noticed the bag slung over her arm and the paper she was holding out. He scowled, snatching it briskly, his lips pulling into a tight, displeased line. A time log. Of course. With a resigned sigh, he grabbed his pen and scribbled his name and initials before shoving it back at her.

She glanced down at the sheet and grimaced. “You have terrible handwriting.”

“Get out,” he gritted, his flat look doing nothing to mask his irritation. He didn’t need her critique on top of everything else.

“Alright. See you tomorrow, Mr. Nashton,” she chuckled, her tone airy, carrying that infuriating undercurrent of amusement, as though his opinion of her couldn’t matter less. Then she spun on her heel and tossed a languid wave over her shoulder, twiddling her mint-colored acrylics.

“Unfortunately.”

Then, the door clicked shut behind her, leaving the office mercifully quiet and empty. Edward leaned back in his chair. Finally, he had his silence. But it wasn’t the victory he’d hoped for.

His gaze flicked toward the empty chair she’d occupied, a faint scowl tugging at the corners of his mouth. This was only the beginning. She’d be back tomorrow, and the day after that, and every Wednesday, Thursday, and Friday after that until the semester ended.

Edward’s jaw tightened at the thought, the weight of it pressing down on him like a slowly closing trap. She wasn’t just a nuisance; she was a disruption, a thorn in his side he couldn’t pull out, no matter how much he wanted.

Fifteen weeks and two days of this. Of her.

With a sharp exhale, he turned back to his monitors, forcing his attention onto the scrolling lines of data. He didn’t have time to dwell on irritations. He had work to do, and she was gone for the day. That was enough.

It would have to be.

[matrixmasterassembly]

A Beginner’s Guide to Data Science: Skills and Tools You Need

Data science is transforming industries, offering tools and insights to solve complex problems. As a beginner, understanding the essential skills and tools can set you on the right path to success.

Key Skills to Start Your Journey To excel in data science, begin with foundational skills like:

Programming Languages: Python and R are essential for data manipulation and analysis.

Data Visualization: Tools like Tableau and matplotlib simplify the presentation of insights.

Machine Learning Basics: Learning algorithms such as regression and clustering is a great starting point.

Tools Every Beginner Should Know Starting with the right tools can make your learning process smoother:

Python and Jupyter Notebooks: Ideal for coding and data visualization.

SQL: Essential for querying and managing data stored in databases.

Tableau: A powerful tool for creating interactive and engaging dashboards.

Explore more about the essential skills and tools for data science beginners on Matrix Masters Assembly.

If you're ready to build your first data science project, learn how data visualization tools like Tableau and coding in Python can simplify complex data analysis. Discover practical steps to get started at Matrix Masters Assembly’s comprehensive guide.

[queencryo]

Wi did a pretty good job at work today! Finally got started on a few tickets wi have been putting off for like a month, went into the server room and documented some cable traces that I needed to make the network change that was assigned to me, AND I also messed around with our data gathering tool to generate a report of a goodly portion of the switch ports in my building and what's connected to them.

Said report tool is REALLY strong, really cool!! It allows SQL-esque queries of a huge amount of tables, and link them in custom ways to build a report. Genuinely the best data-representation tool I've ever seen in a tool like this. Lansweeper is pretty good, if any of my followers on the transgender fangirl website want a network info-gathering tool.

[sqlinjection]

LDAP testing & defense

LDAP Injection is an attack used to exploit web based applications that construct LDAP statements based on user input. When an application fails to properly sanitize user input, it's possible to modify LDAP statements through techniques similar to SQL Injection. 

LDAP injection attacks are common due to two factors:

The lack of safer, parameterized LDAP query interfaces

The widespread use of LDAP to authenticate users to systems.

How to test for the issue

During code review

Please check for any queries to the LDAP escape special characters, see here.

Automated Exploitation

Scanner module of tool like OWASP ZAP have module to detect LDAP injection issue.

Remediation

Escape all variables using the right LDAP encoding function

The main way LDAP stores names is based on DN (distinguished name). You can think of this like a unique identifier. These are sometimes used to access resources, like a username.

A DN might look like this

cn=Richard Feynman, ou=Physics Department, dc=Caltech, dc=edu

or

uid=inewton, ou=Mathematics Department, dc=Cambridge, dc=com

There are certain characters that are considered special characters in a DN. The exhaustive list is the following: \ # + < > , ; " = and leading or trailing spaces

Each DN points to exactly 1 entry, which can be thought of sort of like a row in a RDBMS. For each entry, there will be 1 or more attributes which are analogous to RDBMS columns. If you are interested in searching through LDAP for users will certain attributes, you may do so with search filters. In a search filter, you can use standard boolean logic to get a list of users matching an arbitrary constraint. Search filters are written in Polish notation AKA prefix notation.

Example:

(&(ou=Physics)(| (manager=cn=Freeman Dyson,ou=Physics,dc=Caltech,dc=edu) (manager=cn=Albert Einstein,ou=Physics,dc=Princeton,dc=edu) ))

When building LDAP queries in application code, you MUST escape any untrusted data that is added to any LDAP query. There are two forms of LDAP escaping. Encoding for LDAP Search and Encoding for LDAP DN (distinguished name). The proper escaping depends on whether you are sanitising input for a search filter, or you are using a DN as a username-like credential for accessing some resource.

Safe Java for LDAP escaping Example:

public String escapeDN (String name) {

//From RFC 2253 and the / character for JNDI

final char[] META_CHARS = {'+', '"', '<', '>', ';', '/'};

String escapedStr = new String(name);

//Backslash is both a Java and an LDAP escape character,

//so escape it first escapedStr = escapedStr.replaceAll("\\\\\\\\","\\\\\\\\");

//Positional characters - see RFC 2253

escapedStr = escapedStr.replaceAll("\^#","\\\\\\\\#");

escapedStr = escapedStr.replaceAll("\^ | $","\\\\\\\\ ");

for (int i=0 ; i < META_CHARS.length ; i++) {

escapedStr = escapedStr.replaceAll("\\\\" + META_CHARS[i],"\\\\\\\\" + META_CHARS[i]);

}

return escapedStr;

}

[uthra-krish]

The Skills I Acquired on My Path to Becoming a Data Scientist

Data science has emerged as one of the most sought-after fields in recent years, and my journey into this exciting discipline has been nothing short of transformative. As someone with a deep curiosity for extracting insights from data, I was naturally drawn to the world of data science. In this blog post, I will share the skills I acquired on my path to becoming a data scientist, highlighting the importance of a diverse skill set in this field.

The Foundation — Mathematics and Statistics

At the core of data science lies a strong foundation in mathematics and statistics. Concepts such as probability, linear algebra, and statistical inference form the building blocks of data analysis and modeling. Understanding these principles is crucial for making informed decisions and drawing meaningful conclusions from data. Throughout my learning journey, I immersed myself in these mathematical concepts, applying them to real-world problems and honing my analytical skills.

Programming Proficiency

Proficiency in programming languages like Python or R is indispensable for a data scientist. These languages provide the tools and frameworks necessary for data manipulation, analysis, and modeling. I embarked on a journey to learn these languages, starting with the basics and gradually advancing to more complex concepts. Writing efficient and elegant code became second nature to me, enabling me to tackle large datasets and build sophisticated models.

Data Handling and Preprocessing

Working with real-world data is often messy and requires careful handling and preprocessing. This involves techniques such as data cleaning, transformation, and feature engineering. I gained valuable experience in navigating the intricacies of data preprocessing, learning how to deal with missing values, outliers, and inconsistent data formats. These skills allowed me to extract valuable insights from raw data and lay the groundwork for subsequent analysis.

Data Visualization and Communication

Data visualization plays a pivotal role in conveying insights to stakeholders and decision-makers. I realized the power of effective visualizations in telling compelling stories and making complex information accessible. I explored various tools and libraries, such as Matplotlib and Tableau, to create visually appealing and informative visualizations. Sharing these visualizations with others enhanced my ability to communicate data-driven insights effectively.

Machine Learning and Predictive Modeling

Machine learning is a cornerstone of data science, enabling us to build predictive models and make data-driven predictions. I delved into the realm of supervised and unsupervised learning, exploring algorithms such as linear regression, decision trees, and clustering techniques. Through hands-on projects, I gained practical experience in building models, fine-tuning their parameters, and evaluating their performance.

Database Management and SQL

Data science often involves working with large datasets stored in databases. Understanding database management and SQL (Structured Query Language) is essential for extracting valuable information from these repositories. I embarked on a journey to learn SQL, mastering the art of querying databases, joining tables, and aggregating data. These skills allowed me to harness the power of databases and efficiently retrieve the data required for analysis.

Domain Knowledge and Specialization

While technical skills are crucial, domain knowledge adds a unique dimension to data science projects. By specializing in specific industries or domains, data scientists can better understand the context and nuances of the problems they are solving. I explored various domains and acquired specialized knowledge, whether it be healthcare, finance, or marketing. This expertise complemented my technical skills, enabling me to provide insights that were not only data-driven but also tailored to the specific industry.

Soft Skills — Communication and Problem-Solving

In addition to technical skills, soft skills play a vital role in the success of a data scientist. Effective communication allows us to articulate complex ideas and findings to non-technical stakeholders, bridging the gap between data science and business. Problem-solving skills help us navigate challenges and find innovative solutions in a rapidly evolving field. Throughout my journey, I honed these skills, collaborating with teams, presenting findings, and adapting my approach to different audiences.

Continuous Learning and Adaptation

Data science is a field that is constantly evolving, with new tools, technologies, and trends emerging regularly. To stay at the forefront of this ever-changing landscape, continuous learning is essential. I dedicated myself to staying updated by following industry blogs, attending conferences, and participating in courses. This commitment to lifelong learning allowed me to adapt to new challenges, acquire new skills, and remain competitive in the field.

In conclusion, the journey to becoming a data scientist is an exciting and dynamic one, requiring a diverse set of skills. From mathematics and programming to data handling and communication, each skill plays a crucial role in unlocking the potential of data. Aspiring data scientists should embrace this multidimensional nature of the field and embark on their own learning journey. If you want to learn more about Data science, I highly recommend that you contact ACTE Technologies because they offer Data Science courses and job placement opportunities. Experienced teachers can help you learn better. You can find these services both online and offline. Take things step by step and consider enrolling in a course if you’re interested. By acquiring these skills and continuously adapting to new developments, they can make a meaningful impact in the world of data science.

[shieldfoss]

>be me >a web developer >wanting to find a side project for some time, to not get rusty >guy from uni is looking for a person who knows [framework I know] for a minor job >how serendipitous >talk to him, arrange a call, send in CV >brought in to the project >the job involves picking up some tasks that were supposed to be delivered by a junior dev but weren't >main branch, as currently exists, won't build locally without fixing it first >one of the tasks has an existing PR with 40 commits and was created 3 months ago >my first task involves rawdogging SQL, despite the framework having ORM >a query similar to the one I have to write has 330 lines >mfw

Time to sql like no one has ever sqled before

[techfinna]

Top 5 Selling Odoo Modules.

In the dynamic world of business, having the right tools can make all the difference. For Odoo users, certain modules stand out for their ability to enhance data management and operations. To optimize your Odoo implementation and leverage its full potential. 

That's where Odoo ERP can be a life savior for your business. This comprehensive solution integrates various functions into one centralized platform, tailor-made for the digital economy. 

Let’s drive into 5 top selling module that can revolutionize your Odoo experience:

Dashboard Ninja with AI, Odoo Power BI connector, Looker studio connector, Google sheets connector, and Odoo data model.

1. Dashboard Ninja with AI: 

Using this module, Create amazing reports with the powerful and smart Odoo Dashboard ninja app for Odoo. See your business from a 360-degree angle with an interactive, and beautiful dashboard.

Some Key Features:

Real-time streaming Dashboard

Advanced data filter

Create charts from Excel and CSV file

Fluid and flexible layout

Download Dashboards items

This module gives you AI suggestions for improving your operational efficiencies.

2. Odoo Power BI Connector:

This module provides a direct connection between Odoo and Power BI Desktop, a Powerful data visualization tool.

Some Key features:

Secure token-based connection.

Proper schema and data type handling.

Fetch custom tables from Odoo.

Real-time data updates.

With Power BI, you can make informed decisions based on real-time data analysis and visualization.

3. Odoo Data Model: 

The Odoo Data Model is the backbone of the entire system. It defines how your data is stored, structured, and related within the application.

Key Features:

Relations & fields: Developers can easily find relations ( one-to-many, many-to-many and many-to-one) and defining fields (columns) between data tables. 

Object Relational mapping: Odoo ORM allows developers to define models (classes) that map to database tables.

The module allows you to use SQL query extensions and download data in Excel  Sheets.

4. Google Sheet Connector:

This connector bridges the gap between Odoo and Google Sheets.

Some Key features:

Real-time data synchronization and transfer between Odoo and Spreadsheet.

One-time setup, No need to wrestle with API’s.

Transfer multiple tables swiftly.

Helped your team’s workflow by making Odoo data accessible in a sheet format.

5.  Odoo Looker Studio Connector:

Looker studio connector by Techfinna easily integrates Odoo data with Looker, a powerful data analytics and visualization platform.

Some Key Features:

Directly integrate Odoo data to Looker Studio with just a few clicks.

The connector automatically retrieves and maps Odoo table schemas in their native data types.

Manual and scheduled data refresh.

Execute custom SQL queries for selective data fetching.

The Module helped you build detailed reports, and provide deeper business intelligence.

 These  Modules will improve analytics, customization, and reporting. Module setup can significantly enhance your operational efficiency. Let’s embrace these modules and take your Odoo experience to the next level. 

Need Help?

I hope you find the blog helpful. Please share your feedback and suggestions.

For flawless Odoo Connectors, implementation, and services contact us at 

info@techfinna.com Or www.techneith.com  

[zabeelinstitutes-blog]

The Ultimate Guide to Mastering Power BI: A Comprehensive Course by Zabeel Institute

In today's data-driven world, businesses are constantly seeking ways to leverage data for better decision-making. One of the most powerful tools to achieve this is Microsoft Power BI, a business analytics solution that empowers organizations to visualize their data, share insights, and make data-driven decisions in real time. If you're looking to gain expertise in this powerful tool, Zabeel Institute's Power BI course in Dubai is the perfect starting point.

What is Power BI?

Power BI is a suite of business analytics tools that allows users to analyze data and share insights. With its user-friendly interface and robust capabilities, Power BI enables both beginners and seasoned professionals to create interactive dashboards and reports. Whether you're dealing with simple data sets or complex analytics, Power BI makes data visualization intuitive and accessible.

Why Learn Power BI?

Learning Power BI opens up a world of opportunities. As businesses increasingly rely on data to drive their decisions, professionals skilled in Power BI are in high demand. Here are some compelling reasons why you should consider enrolling in a Power BI course:

High Demand for Power BI Skills: With the rise of data-driven decision-making, there is a growing demand for professionals who can interpret and visualize data effectively.

Career Advancement: Mastering Power BI can significantly enhance your career prospects, especially in fields such as data analysis, business intelligence, and management.

Versatility: Power BI is versatile and can be applied across various industries, including finance, healthcare, marketing, and more.

Improved Decision-Making: By learning how to create detailed and interactive reports, you can help your organization make informed decisions based on real-time data.

Course Overview: Analyzing Data with Microsoft Power BI

At Zabeel Institute, the Analyzing Data with Microsoft Power BI course is designed to equip you with the skills needed to harness the full potential of Power BI. This comprehensive course covers everything from the basics to advanced data visualization techniques.

1. Introduction to Power BI

The course begins with an introduction to the Power BI environment. You'll learn about the Power BI service, Power BI Desktop, and how to navigate through these tools efficiently. Understanding the interface is crucial for leveraging the full capabilities of Power BI.

2. Connecting to Data Sources

Power BI allows you to connect to a wide range of data sources, including Excel, SQL Server, Azure, and many more. In this module, you'll learn how to import data from various sources and prepare it for analysis.

3. Data Transformation and Cleaning

Before you can visualize your data, it often needs to be cleaned and transformed. This section of the course will teach you how to use Power Query to shape and clean your data, ensuring it's ready for analysis.

4. Creating Data Models

Data modeling is a crucial step in the data analysis process. In this module, you'll learn how to create relationships between different data sets and build a robust data model that supports your analysis.

5. Building Interactive Dashboards

One of Power BI's strengths is its ability to create interactive dashboards. You'll learn how to design visually appealing dashboards that provide meaningful insights at a glance.

6. Advanced Data Visualizations

Once you're comfortable with the basics, the course delves into more advanced visualizations. You'll explore custom visuals, R and Python integration, and how to create sophisticated reports that stand out.

7. DAX (Data Analysis Expressions)

DAX is a powerful formula language in Power BI. This section covers the fundamentals of DAX, enabling you to perform complex calculations and create dynamic reports.

8. Power BI Service and Collaboration

Power BI is not just about creating reports—it's also about sharing and collaborating on those reports. You'll learn how to publish your reports to the Power BI service, set up security, and collaborate with your team.

9. Power BI Mobile App

In today's mobile world, being able to access your reports on the go is essential. The course will show you how to use the Power BI Mobile App to view and interact with your dashboards from anywhere.

10. Best Practices for Power BI

To ensure you're getting the most out of Power BI, the course concludes with a module on best practices. This includes tips on performance optimization, report design, and maintaining data security.

Why Choose Zabeel Institute?

When it comes to learning Power BI, choosing the right institute is crucial. Zabeel Institute stands out for several reasons:

Experienced Instructors: Zabeel Institute's instructors are industry experts with years of experience in data analysis and business intelligence.

Hands-On Training: The course is designed to be highly practical, with plenty of hands-on exercises to reinforce your learning.

Industry-Recognized Certification: Upon completion, you'll receive a certification that is recognized by employers globally, giving you an edge in the job market.

Flexible Learning Options: Whether you prefer in-person classes or online learning, Zabeel Institute offers flexible options to suit your schedule.

Real-World Applications of Power BI

Understanding Power BI is one thing, but knowing how to apply it in the real world is what truly matters. Here are some examples of how Power BI can be used across various industries:

Finance: Create detailed financial reports and dashboards that track key metrics such as revenue, expenses, and profitability.

Healthcare: Analyze patient data to improve healthcare delivery and outcomes.

Retail: Track sales data, customer trends, and inventory levels in real time.

Marketing: Measure the effectiveness of marketing campaigns by analyzing data from multiple channels.

Human Resources: Monitor employee performance, track recruitment metrics, and analyze workforce trends.

Success Stories: How Power BI Transformed Businesses

To illustrate the impact of Power BI, let's look at a few success stories:

Company A: This retail giant used Power BI to analyze customer purchasing behavior, resulting in a 15% increase in sales.

Company B: A financial services firm leveraged Power BI to streamline its reporting process, reducing the time spent on report generation by 50%.

Company C: A healthcare provider used Power BI to track patient outcomes, leading to improved patient care and reduced readmission rates.

Mastering Power BI is not just about learning a tool—it's about acquiring a skill that can transform the way you work with data. Whether you're looking to advance your career, enhance your business's decision-making capabilities, or simply stay ahead in today's data-driven world, Zabeel Institute's Power BI course is the perfect choice.

Don't miss out on the opportunity to learn from the best. Enroll in Zabeel Institute's Power BI course today and take the first step towards becoming a Power BI expert.

Ready to transform your career with Power BI? Enroll in Zabeel Institute's Power BI course now and start your journey towards mastering data analysis and visualization. Visit Zabeel Institut for more information.

[amparol12]

Breaking Homework Barriers: Journey to Database Brilliance

In the fast-paced world of academia, students often find themselves grappling with the intricacies of database management and SQL homework. The challenges posed by these assignments can be daunting, leaving many seeking a guiding light to navigate the complexities of database design, queries, and optimization. If you're one of those students desperately searching for "help with mySQL homework," you've come to the right place. This blog will serve as your roadmap, guiding you through the journey to unlock the secrets of database brilliance.

Unraveling the Mysteries of mySQL Homework

Help with mySQL homework is more than just a search query; it's a plea for assistance in unraveling the mysteries of structured query language and database management systems. As you embark on your academic quest, you'll encounter challenges that test your understanding of data modeling, SQL syntax, and the nuances of optimizing database performance. Fear not, for every hurdle you face is an opportunity to grow and master the art of database design.

Navigating the Database Landscape

To embark on this journey, it's crucial to understand the landscape you're navigating. Databases are the backbone of modern applications, storing and managing vast amounts of information. SQL, or Structured Query Language, serves as the key to interacting with these databases, allowing you to retrieve, insert, update, and delete data seamlessly. However, the road to becoming proficient in SQL can be winding, filled with challenges that demand attention to detail and a deep understanding of database concepts.

The Role of Expert Guidance

In your quest for database brilliance, seeking expert guidance is akin to having a seasoned navigator on your journey. Platforms like DatabaseHomeworkHelp.com are designed to provide comprehensive help with mySQL homework. These services offer a lifeline for students drowning in assignments, providing expert assistance that goes beyond mere completion to ensure understanding and mastery of database principles.

Tailored Solutions for Individual Needs

One size does not fit all, especially when it comes to mastering database concepts. Help with mySQL homework should be tailored to your individual needs and learning style. A reliable service will not only assist with assignment completion but also provide detailed explanations, clarifying doubts and reinforcing your understanding of SQL. This personalized approach is the key to breaking down barriers and fostering true brilliance in database management.

Overcoming Common Challenges

As you delve into the world of databases, you'll likely encounter common challenges that can be stumbling blocks in your academic journey. Whether it's understanding normalization, crafting complex queries, or optimizing database performance, expert assistance can make all the difference. These challenges, when conquered with the right guidance, become stepping stones to a deeper understanding of database management.

Building a Foundation for Future Success

The journey to database brilliance is not just about completing assignments; it's about building a solid foundation for future success. The skills you acquire in navigating SQL and database design will prove invaluable in real-world scenarios. As industries increasingly rely on data-driven decision-making, your proficiency in database management will set you apart in the job market.

Embracing the Learning Process

Every stumble, every challenge, and every "help with mySQL homework" query is an integral part of your learning process. Embrace the journey, knowing that each assignment is an opportunity to enhance your skills. Don't shy away from seeking assistance when needed, as it's a sign of strength to recognize your limitations and actively work towards overcoming them.

Conclusion: Your Path to Database Brilliance

In conclusion, the journey to database brilliance is not a solitary one; it's a collaborative effort that involves seeking guidance, overcoming challenges, and embracing the learning process. When faced with the complexities of SQL homework, remember that help with mySQL homework is readily available. Take advantage of the resources at your disposal, and soon you'll find yourself not just completing assignments but mastering the art of database management. Your path to brilliance starts now.