#connect SQL database

[palesquash]

I’ve worked in databases professionally for a number of years for companies large and small so there’s a few… notes here that make this hilarious to me:

First, If you honestly think that there’s “one” database that handles all this information for the most powerful country in the history of the world… I feel sorry for you buddy

Second, there can be a whole host of reasons why some field labeled “death” can be false, a few off the top of my head:

“DEATH�� just means death of the record, not the person

Old/outdated data

Are there entries of NULL anywhere?

Are there any duplicates?

Is this database following normalization rules?

Can you tie any of this data to actual payouts?

Is this table actually used for that purpose?

Is this a down-stream table that is for a different kind of processing/reporting?

Databases can be a mess to work with and context matters here. Of course, given his tweet about how “the government doesn’t use sql” I’m willing to bet he doesn’t know a lick of what he’s talking about here.

It just makes me so mad because… I do this exact kind of work for a living and I would not for the LIFE of me just prance around talking about how this data is bad without some sort of justication that it’s a) relevant to discussions and b) I’m at least fairly confident this is the case

I wouldn’t trust in any way, shape, or form

[thedbahub]

Common Issues with SQL Server Connections Over WAN vs. LAN: The Role of Compression

When applications connect to SQL Server over a Wide Area Network (WAN) instead of a Local Area Network (LAN), several challenges can arise. These challenges often revolve around latency, bandwidth limitations, and the overall reliability of the connection. Understanding these issues is crucial for database administrators and developers who aim to optimize application performance and reliability.…

[lazeecomet]

The Story of KLogs: What happens when an Mechanical Engineer codes

Since i no longer work at Wearhouse Automation Startup (WAS for short) and havnt for many years i feel as though i should recount the tale of the most bonkers program i ever wrote, but we need to establish some background

WAS has its HQ very far away from the big customer site and i worked as a Field Service Engineer (FSE) on site. so i learned early on that if a problem needed to be solved fast, WE had to do it. we never got many updates on what was coming down the pipeline for us or what issues were being worked on. this made us very independent

As such, we got good at reading the robot logs ourselves. it took too much time to send the logs off to HQ for analysis and get back what the problem was. we can read. now GETTING the logs is another thing.

the early robots we cut our teeth on used 2.4 gHz wifi to communicate with FSE's so dumping the logs was as simple as pushing a button in a little application and it would spit out a txt file

later on our robots were upgraded to use a 2.4 mHz xbee radio to communicate with us. which was FUCKING SLOW. and log dumping became a much more tedious process. you had to connect, go to logging mode, and then the robot would vomit all the logs in the past 2 min OR the entirety of its memory bank (only 2 options) into a terminal window. you would then save the terminal window and open it in a text editor to read them. it could take up to 5 min to dump the entire log file and if you didnt dump fast enough, the ACK messages from the control server would fill up the logs and erase the error as the memory overwrote itself.

this missing logs problem was a Big Deal for software who now weren't getting every log from every error so a NEW method of saving logs was devised: the robot would just vomit the log data in real time over a DIFFERENT radio and we would save it to a KQL server. Thanks Daddy Microsoft.

now whats KQL you may be asking. why, its Microsofts very own SQL clone! its Kusto Query Language. never mind that the system uses a SQL database for daily operations. lets use this proprietary Microsoft thing because they are paying us

so yay, problem solved. we now never miss the logs. so how do we read them if they are split up line by line in a database? why with a query of course!

select * from tbLogs where RobotUID = [64CharLongString] and timestamp > [UnixTimeCode]

if this makes no sense to you, CONGRATULATIONS! you found the problem with this setup. Most FSE's were BAD at SQL which meant they didnt read logs anymore. If you do understand what the query is, CONGRATULATIONS! you see why this is Very Stupid.

You could not search by robot name. each robot had some arbitrarily assigned 64 character long string as an identifier and the timestamps were not set to local time. so you had run a lookup query to find the right name and do some time zone math to figure out what part of the logs to read. oh yeah and you had to download KQL to view them. so now we had both SQL and KQL on our computers

NOBODY in the field like this.

But Daddy Microsoft comes to the rescue

see we didnt JUST get KQL with part of that deal. we got the entire Microsoft cloud suite. and some people (like me) had been automating emails and stuff with Power Automate

This is Microsoft Power Automate. its Microsoft's version of Scratch but it has hooks into everything Microsoft. SharePoint, Teams, Outlook, Excel, it can integrate with all of it. i had been using it to send an email once a day with a list of all the robots in maintenance.

this gave me an idea

and i checked

and Power Automate had hooks for KQL

KLogs is actually short for Kusto Logs

I did not know how to program in Power Automate but damn it anything is better then writing KQL queries. so i got to work. and about 2 months later i had a BEHEMOTH of a Power Automate program. it lagged the webpage and many times when i tried to edit something my changes wouldn't take and i would have to click in very specific ways to ensure none of my variables were getting nuked. i dont think this was the intended purpose of Power Automate but this is what it did

the KLogger would watch a list of Teams chats and when someone typed "klogs" or pasted a copy of an ERROR mesage, it would spring into action.

it extracted the robot name from the message and timestamp from teams

it would lookup the name in the database to find the 64 long string UID and the location that robot was assigned too

it would reply to the message in teams saying it found a robot name and was getting logs

it would run a KQL query for the database and get the control system logs then export then into a CSV

it would save the CSV with the a .xls extension into a folder in ShairPoint (it would make a new folder for each day and location if it didnt have one already)

it would send ANOTHER message in teams with a LINK to the file in SharePoint

it would then enter a loop and scour the robot logs looking for the keyword ESTOP to find the error. (it did this because Kusto was SLOWER then the xbee radio and had up to a 10 min delay on syncing)

if it found the error, it would adjust its start and end timestamps to capture it and export the robot logs book-ended from the event by ~ 1 min. if it didnt, it would use the timestamp from when it was triggered +/- 5 min

it saved THOSE logs to SharePoint the same way as before

it would send ANOTHER message in teams with a link to the files

it would then check if the error was 1 of 3 very specific type of error with the camera. if it was it extracted the base64 jpg image saved in KQL as a byte array, do the math to convert it, and save that as a jpg in SharePoint (and link it of course)

and then it would terminate. and if it encountered an error anywhere in all of this, i had logic where it would spit back an error message in Teams as plaintext explaining what step failed and the program would close gracefully

I deployed it without asking anyone at one of the sites that was struggling. i just pointed it at their chat and turned it on. it had a bit of a rocky start (spammed chat) but man did the FSE's LOVE IT.

about 6 months later software deployed their answer to reading the logs: a webpage that acted as a nice GUI to the KQL database. much better then an CSV file

it still needed you to scroll though a big drop-down of robot names and enter a timestamp, but i noticed something. all that did was just change part of the URL and refresh the webpage

SO I MADE KLOGS 2 AND HAD IT GENERATE THE URL FOR YOU AND REPLY TO YOUR MESSAGE WITH IT. (it also still did the control server and jpg stuff). Theres a non-zero chance that klogs was still in use long after i left that job

now i dont recommend anyone use power automate like this. its clunky and weird. i had to make a variable called "Carrage Return" which was a blank text box that i pressed enter one time in because it was incapable of understanding /n or generating a new line in any capacity OTHER then this (thanks support forum).

im also sure this probably is giving the actual programmer people anxiety. imagine working at a company and then some rando you've never seen but only heard about as "the FSE whos really good at root causing stuff", in a department that does not do any coding, managed to, in their spare time, build and release and entire workflow piggybacking on your work without any oversight, code review, or permission.....and everyone liked it

[womaneng]

View this post on Instagram

A post shared by Zeynep Küçük Woman Engineer (@woman.engineer)

Hey there! 🚀 Becoming a data analyst is an awesome journey! Here’s a roadmap for you:

1. Start with the Basics 📚:

- Dive into the basics of data analysis and statistics. 📊

- Platforms like Learnbay (Data Analytics Certification Program For Non-Tech Professionals), Edx, and Intellipaat offer fantastic courses. Check them out! 🎓

2. Master Excel 📈:

- Excel is your best friend! Learn to crunch numbers and create killer spreadsheets. 📊🔢

3. Get Hands-on with Tools 🛠️:

- Familiarize yourself with data analysis tools like SQL, Python, and R. Pluralsight has some great courses to level up your skills! 🐍📊

4. Data Visualization 📊:

- Learn to tell a story with your data. Tools like Tableau and Power BI can be game-changers! 📈📉

5. Build a Solid Foundation 🏗️:

- Understand databases, data cleaning, and data wrangling. It’s the backbone of effective analysis! 💪🔍

6. Machine Learning Basics 🤖:

- Get a taste of machine learning concepts. It’s not mandatory but can be a huge plus! 🤓🤖

7. Projects, Projects, Projects! 🚀:

- Apply your skills to real-world projects. It’s the best way to learn and showcase your abilities! 🌐💻

8. Networking is Key 👥:

- Connect with fellow data enthusiasts on LinkedIn, attend meetups, and join relevant communities. Networking opens doors! 🌐👋

9. Certifications 📜:

- Consider getting certified. It adds credibility to your profile. 🎓💼

10. Stay Updated 🔄:

- The data world evolves fast. Keep learning and stay up-to-date with the latest trends and technologies. 📆🚀

. . .

[pythonfullstackmasters]

🚀 Python Full Stack Knowledge Post! 🖥️🔥

✅ Backend – Django/Flask for secure apps

✅ Frontend – React.js/Vue.js for dynamic UIs

✅ APIs – Connect frontend & backend with JSON

✅ Databases – SQL (PostgreSQL, MySQL) & NoSQL (MongoDB)

✅ Deployment – Git, Docker, AWS for project management

🎯 Enroll Now!

📞 +91 9704944 488 | 🌐 pythonfullstackmasters.in

[uegub]

Why Tableau is Essential in Data Science: Transforming Raw Data into Insights

Data science is all about turning raw data into valuable insights. But numbers and statistics alone don’t tell the full story—they need to be visualized to make sense. That’s where Tableau comes in.

Tableau is a powerful tool that helps data scientists, analysts, and businesses see and understand data better. It simplifies complex datasets, making them interactive and easy to interpret. But with so many tools available, why is Tableau a must-have for data science? Let’s explore.

1. The Importance of Data Visualization in Data Science

Imagine you’re working with millions of data points from customer purchases, social media interactions, or financial transactions. Analyzing raw numbers manually would be overwhelming.

That’s why visualization is crucial in data science:

Identifies trends and patterns – Instead of sifting through spreadsheets, you can quickly spot trends in a visual format.

Makes complex data understandable – Graphs, heatmaps, and dashboards simplify the interpretation of large datasets.

Enhances decision-making – Stakeholders can easily grasp insights and make data-driven decisions faster.

Saves time and effort – Instead of writing lengthy reports, an interactive dashboard tells the story in seconds.

Without tools like Tableau, data science would be limited to experts who can code and run statistical models. With Tableau, insights become accessible to everyone—from data scientists to business executives.

2. Why Tableau Stands Out in Data Science

A. User-Friendly and Requires No Coding

One of the biggest advantages of Tableau is its drag-and-drop interface. Unlike Python or R, which require programming skills, Tableau allows users to create visualizations without writing a single line of code.

Even if you’re a beginner, you can:

✅ Upload data from multiple sources

✅ Create interactive dashboards in minutes

✅ Share insights with teams easily

This no-code approach makes Tableau ideal for both technical and non-technical professionals in data science.

B. Handles Large Datasets Efficiently

Data scientists often work with massive datasets—whether it’s financial transactions, customer behavior, or healthcare records. Traditional tools like Excel struggle with large volumes of data.

Tableau, on the other hand:

Can process millions of rows without slowing down

Optimizes performance using advanced data engine technology

Supports real-time data streaming for up-to-date analysis

This makes it a go-to tool for businesses that need fast, data-driven insights.

C. Connects with Multiple Data Sources

A major challenge in data science is bringing together data from different platforms. Tableau seamlessly integrates with a variety of sources, including:

Databases: MySQL, PostgreSQL, Microsoft SQL Server

Cloud platforms: AWS, Google BigQuery, Snowflake

Spreadsheets and APIs: Excel, Google Sheets, web-based data sources

This flexibility allows data scientists to combine datasets from multiple sources without needing complex SQL queries or scripts.

D. Real-Time Data Analysis

Industries like finance, healthcare, and e-commerce rely on real-time data to make quick decisions. Tableau’s live data connection allows users to:

Track stock market trends as they happen

Monitor website traffic and customer interactions in real time

Detect fraudulent transactions instantly

Instead of waiting for reports to be generated manually, Tableau delivers insights as events unfold.

E. Advanced Analytics Without Complexity

While Tableau is known for its visualizations, it also supports advanced analytics. You can:

Forecast trends based on historical data

Perform clustering and segmentation to identify patterns

Integrate with Python and R for machine learning and predictive modeling

This means data scientists can combine deep analytics with intuitive visualization, making Tableau a versatile tool.

3. How Tableau Helps Data Scientists in Real Life

Tableau has been adopted by the majority of industries to make data science more impactful and accessible. This is applied in the following real-life scenarios:

A. Analytics for Health Care

Tableau is deployed by hospitals and research institutions for the following purposes:

Monitor patient recovery rates and predict outbreaks of diseases

Analyze hospital occupancy and resource allocation

Identify trends in patient demographics and treatment results

B. Finance and Banking

Banks and investment firms rely on Tableau for the following purposes:

✅ Detect fraud by analyzing transaction patterns

✅ Track stock market fluctuations and make informed investment decisions

✅ Assess credit risk and loan performance

C. Marketing and Customer Insights

Companies use Tableau to:

✅ Track customer buying behavior and personalize recommendations

✅ Analyze social media engagement and campaign effectiveness

✅ Optimize ad spend by identifying high-performing channels

D. Retail and Supply Chain Management

Retailers leverage Tableau to:

✅ Forecast product demand and adjust inventory levels

✅ Identify regional sales trends and adjust marketing strategies

✅ Optimize supply chain logistics and reduce delivery delays

These applications show why Tableau is a must-have for data-driven decision-making.

4. Tableau vs. Other Data Visualization Tools

There are many visualization tools available, but Tableau consistently ranks as one of the best. Here’s why:

Tableau vs. Excel – Excel struggles with big data and lacks interactivity; Tableau handles large datasets effortlessly.

Tableau vs. Power BI – Power BI is great for Microsoft users, but Tableau offers more flexibility across different data sources.

Tableau vs. Python (Matplotlib, Seaborn) – Python libraries require coding skills, while Tableau simplifies visualization for all users.

This makes Tableau the go-to tool for both beginners and experienced professionals in data science.

5. Conclusion

Tableau has become an essential tool in data science because it simplifies data visualization, handles large datasets, and integrates seamlessly with various data sources. It enables professionals to analyze, interpret, and present data interactively, making insights accessible to everyone—from data scientists to business leaders.

If you’re looking to build a strong foundation in data science, learning Tableau is a smart career move. Many data science courses now include Tableau as a key skill, as companies increasingly demand professionals who can transform raw data into meaningful insights.

In a world where data is the driving force behind decision-making, Tableau ensures that the insights you uncover are not just accurate—but also clear, impactful, and easy to act upon.

[itcareerblogs]

Top 10 In- Demand Tech Jobs in 2025

Technology is growing faster than ever, and so is the need for skilled professionals in the field. From artificial intelligence to cloud computing, businesses are looking for experts who can keep up with the latest advancements. These tech jobs not only pay well but also offer great career growth and exciting challenges.

In this blog, we’ll look at the top 10 tech jobs that are in high demand today. Whether you’re starting your career or thinking of learning new skills, these jobs can help you plan a bright future in the tech world.

1. AI and Machine Learning Specialists

Artificial Intelligence (AI)  and Machine Learning are changing the game by helping machines learn and improve on their own without needing step-by-step instructions. They’re being used in many areas, like chatbots, spotting fraud, and predicting trends.

Key Skills: Python, TensorFlow, PyTorch, data analysis, deep learning, and natural language processing (NLP).

Industries Hiring: Healthcare, finance, retail, and manufacturing.

Career Tip: Keep up with AI and machine learning by working on projects and getting an AI certification. Joining AI hackathons helps you learn and meet others in the field.

2. Data Scientists

Data scientists work with large sets of data to find patterns, trends, and useful insights that help businesses make smart decisions. They play a key role in everything from personalized marketing to predicting health outcomes.

Key Skills: Data visualization, statistical analysis, R, Python, SQL, and data mining.

Industries Hiring: E-commerce, telecommunications, and pharmaceuticals.

Career Tip: Work with real-world data and build a strong portfolio to showcase your skills. Earning certifications in data science tools can help you stand out.

3. Cloud Computing Engineers: These professionals create and manage cloud systems that allow businesses to store data and run apps without needing physical servers, making operations more efficient.

Key Skills: AWS, Azure, Google Cloud Platform (GCP), DevOps, and containerization (Docker, Kubernetes).

Industries Hiring: IT services, startups, and enterprises undergoing digital transformation.

Career Tip: Get certified in cloud platforms like AWS (e.g., AWS Certified Solutions Architect).

4. Cybersecurity Experts

Cybersecurity professionals protect companies from data breaches, malware, and other online threats. As remote work grows, keeping digital information safe is more crucial than ever.

Key Skills: Ethical hacking, penetration testing, risk management, and cybersecurity tools.

Industries Hiring: Banking, IT, and government agencies.

Career Tip: Stay updated on new cybersecurity threats and trends. Certifications like CEH (Certified Ethical Hacker) or CISSP (Certified Information Systems Security Professional) can help you advance in your career.

5. Full-Stack Developers

Full-stack developers are skilled programmers who can work on both the front-end (what users see) and the back-end (server and database) of web applications.

Key Skills: JavaScript, React, Node.js, HTML/CSS, and APIs.

Industries Hiring: Tech startups, e-commerce, and digital media.

Career Tip: Create a strong GitHub profile with projects that highlight your full-stack skills. Learn popular frameworks like React Native to expand into mobile app development.

6. DevOps Engineers

DevOps engineers help make software faster and more reliable by connecting development and operations teams. They streamline the process for quicker deployments.

Key Skills: CI/CD pipelines, automation tools, scripting, and system administration.

Industries Hiring: SaaS companies, cloud service providers, and enterprise IT.

Career Tip: Earn key tools like Jenkins, Ansible, and Kubernetes, and develop scripting skills in languages like Bash or Python. Earning a DevOps certification is a plus and can enhance your expertise in the field.

7. Blockchain Developers

They build secure, transparent, and unchangeable systems. Blockchain is not just for cryptocurrencies; it’s also used in tracking supply chains, managing healthcare records, and even in voting systems.

Key Skills: Solidity, Ethereum, smart contracts, cryptography, and DApp development.

Industries Hiring: Fintech, logistics, and healthcare.

Career Tip: Create and share your own blockchain projects to show your skills. Joining blockchain communities can help you learn more and connect with others in the field.

8. Robotics Engineers

Robotics engineers design, build, and program robots to do tasks faster or safer than humans. Their work is especially important in industries like manufacturing and healthcare.

Key Skills: Programming (C++, Python), robotics process automation (RPA), and mechanical engineering.

Industries Hiring: Automotive, healthcare, and logistics.

Career Tip: Stay updated on new trends like self-driving cars and AI in robotics.

9. Internet of Things (IoT) Specialists

IoT specialists work on systems that connect devices to the internet, allowing them to communicate and be controlled easily. This is crucial for creating smart cities, homes, and industries.

Key Skills: Embedded systems, wireless communication protocols, data analytics, and IoT platforms.

Industries Hiring: Consumer electronics, automotive, and smart city projects.

Career Tip: Create IoT prototypes and learn to use platforms like AWS IoT or Microsoft Azure IoT. Stay updated on 5G technology and edge computing trends.

10. Product Managers

Product managers oversee the development of products, from idea to launch, making sure they are both technically possible and meet market demands. They connect technical teams with business stakeholders.

Key Skills: Agile methodologies, market research, UX design, and project management.

Industries Hiring: Software development, e-commerce, and SaaS companies.

Career Tip: Work on improving your communication and leadership skills. Getting certifications like PMP (Project Management Professional) or CSPO (Certified Scrum Product Owner) can help you advance.

Importance of Upskilling in the Tech Industry

Stay Up-to-Date: Technology changes fast, and learning new skills helps you keep up with the latest trends and tools.

Grow in Your Career: By learning new skills, you open doors to better job opportunities and promotions.

Earn a Higher Salary: The more skills you have, the more valuable you are to employers, which can lead to higher-paying jobs.

Feel More Confident: Learning new things makes you feel more prepared and ready to take on tougher tasks.

Adapt to Changes: Technology keeps evolving, and upskilling helps you stay flexible and ready for any new changes in the industry.

Top Companies Hiring for These Roles

Global Tech Giants: Google, Microsoft, Amazon, and IBM.

Startups: Fintech, health tech, and AI-based startups are often at the forefront of innovation.

Consulting Firms: Companies like Accenture, Deloitte, and PwC increasingly seek tech talent.

In conclusion,  the tech world is constantly changing, and staying updated is key to having a successful career. In 2025, jobs in fields like AI, cybersecurity, data science, and software development will be in high demand. By learning the right skills and keeping up with new trends, you can prepare yourself for these exciting roles. Whether you're just starting or looking to improve your skills, the tech industry offers many opportunities for growth and success.

[rahul-odoo-data-analyst]

Connect or integrate Odoo ERP database with Microsoft Excel

Techfinna's Odoo Excel Connector is a powerful tool that integrates Odoo data with Microsoft Excel. It enables users to pull real-time data, perform advanced analysis, and create dynamic reports directly in Excel. With its user-friendly interface and robust functionality, it simplifies complex workflows, saving time and enhancing productivity.

#odoo #odooerp #odoosoftware #odoomodule #crm #accounting #salesforce #connector #integration #odoo18 #odoo17 #erpsoftware #odoodevelopers #odoocustomization #erpimplementation #lookerstudio #odoo18 #odoo17

[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.

[lunarsilkscreen]

Government OS Whitepaper

I didn't know what else to call it; maybe they'll call it "MelinWare" and then somebody will invent a scam under that name for which I will inevitably be blamed.

We have a demand for systems Government and Corporate alike that are essentially "Hack Proof". And while we cannot ensure complete unhackability...

Cuz people are smart and mischievous sometimes;

There is growing need to be as hack safe as possible at a hardware and OS level. Which would create a third computer tech sector for specialized software and hardware.

The problem is; it's not profitable from an everyday user perspective. We want to be able to use *our* devices in ways that *we* see fit.

And this has created an environment where virtually everyone is using the same three operating systems with loads of security overhead installed to simply monitor what is happening on a device.

Which is kind of wasted power and effort.

My line of thinking goes like this;

SQL databases are vulnerable to a type of hack called "SQL Injection" which basically means If you pass on any text to the server (like username and password) you can add SQL to the text to change what the database might do.

What this looks like on the backend is several algorithms working to filter the strings out to ensure nothing bad gets in there.

So what we need are Systems that are like an SQL database that doesn't have that "Injection" flaw.

And it needs to be available to the Government and Corporate environments.

However; in real-world environments; this looks like throttled bandwidth, less resources available at any one time, and a lot less freedom.

Which is what we want for our secure connections anyway.

I have the inkling suspicion that tech companies will try to convert this to a front end for their customers as well, because it's easier to maintain one code backend than it is for two.

And they want as much control over their devices and environment as possible;which is fine for some users, but not others.

So we need to figure out a way to make this a valuable endeavor. And give companies the freedom to understand how these systems work, and in ways that the government can use their own systems against them.

This would probably look like more users going to customized Linux solutions as Windows and Apple try to gobbleup government contracts.

Which honestly; I think a lot of users and start-up businesses could come up from this.

But it also has the ability to go awry in a miriad of ways.

However; I do believe I have planted a good seed with this post to inspire the kind of thinking we need to develop these systems.

[pentesttestingcorp]

SQL Injection in RESTful APIs: Identify and Prevent Vulnerabilities

SQL Injection (SQLi) in RESTful APIs: What You Need to Know

RESTful APIs are crucial for modern applications, enabling seamless communication between systems. However, this convenience comes with risks, one of the most common being SQL Injection (SQLi). In this blog, we’ll explore what SQLi is, its impact on APIs, and how to prevent it, complete with a practical coding example to bolster your understanding.

What Is SQL Injection?

SQL Injection is a cyberattack where an attacker injects malicious SQL statements into input fields, exploiting vulnerabilities in an application's database query execution. When it comes to RESTful APIs, SQLi typically targets endpoints that interact with databases.

How Does SQL Injection Affect RESTful APIs?

RESTful APIs are often exposed to public networks, making them prime targets. Attackers exploit insecure endpoints to:

Access or manipulate sensitive data.

Delete or corrupt databases.

Bypass authentication mechanisms.

Example of a Vulnerable API Endpoint

Consider an API endpoint for retrieving user details based on their ID:

from flask import Flask, request import sqlite3

app = Flask(name)

@app.route('/user', methods=['GET']) def get_user(): user_id = request.args.get('id') conn = sqlite3.connect('database.db') cursor = conn.cursor() query = f"SELECT * FROM users WHERE id = {user_id}" # Vulnerable to SQLi cursor.execute(query) result = cursor.fetchone() return {'user': result}, 200

if name == 'main': app.run(debug=True)

Here, the endpoint directly embeds user input (user_id) into the SQL query without validation, making it vulnerable to SQL Injection.

Secure API Endpoint Against SQLi

To prevent SQLi, always use parameterized queries:

@app.route('/user', methods=['GET']) def get_user(): user_id = request.args.get('id') conn = sqlite3.connect('database.db') cursor = conn.cursor() query = "SELECT * FROM users WHERE id = ?" cursor.execute(query, (user_id,)) result = cursor.fetchone() return {'user': result}, 200

In this approach, the user input is sanitized, eliminating the risk of malicious SQL execution.

How Our Free Tool Can Help

Our free Website Security Checker your web application for vulnerabilities, including SQL Injection risks. Below is a screenshot of the tool's homepage:

Upload your website details to receive a comprehensive vulnerability assessment report, as shown below:

These tools help identify potential weaknesses in your APIs and provide actionable insights to secure your system.

Preventing SQLi in RESTful APIs

Here are some tips to secure your APIs:

Use Prepared Statements: Always parameterize your queries.

Implement Input Validation: Sanitize and validate user input.

Regularly Test Your APIs: Use tools like ours to detect vulnerabilities.

Least Privilege Principle: Restrict database permissions to minimize potential damage.

Final Thoughts

SQL Injection is a pervasive threat, especially in RESTful APIs. By understanding the vulnerabilities and implementing best practices, you can significantly reduce the risks. Leverage tools like our free Website Security Checker to stay ahead of potential threats and secure your systems effectively.

Explore our tool now for a quick Website Security Check.

[sqlinjection]

How to test app for the SQL injection

During code review

Check for any queries to the database are not done via prepared statements.

If dynamic statements are being made please check if the data is sanitized before used as part of the statement.

Auditors should always look for uses of sp_execute, execute or exec within SQL Server stored procedures. Similar audit guidelines are necessary for similar functions for other vendors.

Automated Exploitation

Most of the situation and techniques on testing an app for SQLi can be performed in a automated way using some tools (e.g. perform an automated auditing using SQLMap)

Equally Static Code Analysis Data flow rules can detect of unsanitised user controlled input can change the SQL query.

Stored Procedure Injection

When using dynamic SQL within a stored procedure, the application must properly sanitise the user input to eliminate the risk of code injection. If not sanitised, the user could enter malicious SQL that will be executed within the stored procedure.

Time delay Exploitation technique

The time delay exploitation technique is very useful when the tester find a Blind SQL Injection situation, in which nothing is known on the outcome of an operation. This technique consists in sending an injected query and in case the conditional is true, the tester can monitor the time taken to for the server to respond. If there is a delay, the tester can assume the result of the conditional query is true. This exploitation technique can be different from DBMS to DBMS.

http://www.example.com/product.php?id=10 AND IF(version() like '5%', sleep(10), 'false'))--

In this example the tester is checking whether the MySql version is 5.x or not, making the server delay the answer by 10 seconds. The tester can increase the delay time and monitor the responses. The tester also doesn't need to wait for the response. Sometimes they can set a very high value (e.g. 100) and cancel the request after some seconds.

Out-of-band Exploitation technique

This technique is very useful when the tester find a Blind SQL Injection situation, in which nothing is known on the outcome of an operation. The technique consists of the use of DBMS functions to perform an out of band connection and deliver the results of the injected query as part of the request to the tester's server. Like the error based techniques, each DBMS has its own functions. Check for specific DBMS section.

[vbeyound]

Maximizing Business Insights with Power BI: A Comprehensive Guide for Small Businesses

Maximizing Business Insights Small businesses often face the challenge of making data-driven decisions without the resources of larger enterprises. Power BI, Microsoft's powerful analytics tool, can transform how small businesses use data, turning raw numbers into actionable insights. Here's a comprehensive guide to maximizing business insights with Power BI.

Introduction to Power BI

Power BI is a business analytics service by Microsoft that provides interactive visualizations and business intelligence capabilities. With an interface simple enough for end users to create their own reports and dashboards, it connects to a wide range of data sources.

Benefits for Small Businesses

1. User-Friendly Interface: Power BI's drag-and-drop functionality makes it accessible for users without technical expertise.

2. Cost-Effective: Power BI offers a free version with substantial features and a scalable pricing model for additional needs.

3. Real-Time Data: Businesses can monitor their operations with real-time data, enabling quicker and more informed decision-making.

Setting Up Power BI

1. Data Sources: Power BI can connect to various data sources such as Excel, SQL databases, and cloud services like Azure.

2. Data Modeling: Use Power BI to clean and transform data, creating a cohesive data model that forms the foundation of your reports.

3. Visualizations: Choose from a wide array of visualizations to represent your data. Customize these visuals to highlight the most critical insights.

Customizing Dashboards

1. Tailor to Needs: Customize dashboards to reflect the unique needs of your business, focusing on key performance indicators (KPIs) relevant to your goals.

2. Interactive Reports:Create interactive reports that allow users to explore data more deeply, providing a clearer understanding of underlying trends.

Real-World Examples

Several small businesses have successfully implemented Power BI to gain a competitive edge:

1. Retail: A small retail store used Power BI to track sales trends, optimize inventory, and identify peak shopping times.

2. Finance:A small financial advisory firm employed Power BI to analyze client portfolios, improving investment strategies and client satisfaction.

Integration with Existing Tools

Power BI seamlessly integrates with other Microsoft products such as Excel and Azure, as well as third-party applications, ensuring a smooth workflow and enhanced productivity.

Best Practices

1. Data Accuracy: Ensure data accuracy by regularly updating your data sources.

2. Training: Invest in training your team to use Power BI effectively.

3. Security: Implement robust security measures to protect sensitive data.

Future Trends

Power BI continues to evolve, with future updates likely to include more advanced AI features and enhanced data processing capabilities, keeping businesses at the forefront of technology.

Conclusion

Power BI offers small businesses a powerful tool to transform their data into meaningful insights. By adopting Power BI, businesses can improve decision-making, enhance operational efficiency, and gain a competitive advantage. Partnering with Vbeyond Digital ensures a smooth and successful implementation, maximizing the benefits of Power BI for your business. with Power BI: A Comprehensive Guide for Small Businesses

[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  

[mvishnukumar]

Can I use Python for big data analysis?

Yes, Python is a powerful tool for big data analysis. Here’s how Python handles large-scale data analysis:

Libraries for Big Data:

Pandas: 

While primarily designed for smaller datasets, Pandas can handle larger datasets efficiently when used with tools like Dask or by optimizing memory usage..

NumPy: 

Provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays.

Dask:

 A parallel computing library that extends Pandas and NumPy to larger datasets. It allows you to scale Python code from a single machine to a distributed cluster

Distributed Computing:

PySpark: 

The Python API for Apache Spark, which is designed for large-scale data processing. PySpark can handle big data by distributing tasks across a cluster of machines, making it suitable for large datasets and complex computations.

Dask: 

Also provides distributed computing capabilities, allowing you to perform parallel computations on large datasets across multiple cores or nodes.

Data Storage and Access:

HDF5: 

A file format and set of tools for managing complex data. Python’s h5py library provides an interface to read and write HDF5 files, which are suitable for large datasets.

Databases: 

Python can interface with various big data databases like Apache Cassandra, MongoDB, and SQL-based systems. Libraries such as SQLAlchemy facilitate connections to relational databases.

Data Visualization:

Matplotlib, Seaborn, and Plotly: These libraries allow you to create visualizations of large datasets, though for extremely large datasets, tools designed for distributed environments might be more appropriate.

Machine Learning:

Scikit-learn: 

While not specifically designed for big data, Scikit-learn can be used with tools like Dask to handle larger datasets.

TensorFlow and PyTorch: 

These frameworks support large-scale machine learning and can be integrated with big data processing tools for training and deploying models on large datasets.

Python’s ecosystem includes a variety of tools and libraries that make it well-suited for big data analysis, providing flexibility and scalability to handle large volumes of data.

Drop the message to learn more….!

[pancakeke]

Why are you up working at 2am?

the only person in my company who knows how to work as my backup was given a new laptop by our corporate office that is considered an "outside device" by my branch so it cant connect to our branch's sql database, which means he literally could not do anything for me while I was on PTO this past week. Monday is going to be a shitshow if I don't get a jump on some things :(