#data analytics vs data analysis

[iqlancecaus]

All digital marketing and search engine optimization agencies are conducting competitive and data analysis. Our Seo company halifax has experienced data analysts and Google Analytics experts and they are working on data analytics in detail.

[chatmetainr]

Best Big Data Hadoop Course: Unlocking the Power of Data Analytics

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[j0shm0]

Post Monza Rookie - Sophmore comparison

Been a moment since I posted these graphs with limited time event by event. But with Logans depature I will be comparing Franco/Alex vs Logan 2023 (Alex is there as their base), and continue just showing Oscar 23' vs 24'.

With that it was not a bad drive overall by Franco; he finished 1 place higher then Logan did in 2023 but was 3 seconds further back compared to 1st. Franco did keep pace with Alex in the 2nd sint, and they were both equal to logan last year on the 1st stint. However, this was not a new track to Franco so we can take this with cautious optimism for the rest of the races tell Abu Dhabi which is the only other track he has driven before.

Now on to Oscar, you can tell his stratgey team and McLarens overall is still knew to the idea of competing at the top and especially when you consider they havent really been since 2007 so none of there crew has. Giving up a 10sec lead in a car that is 4sec a lap quicker then 2023 to "cover the undercut" WAS INSANE. But still proves that not only the car but oscar himself is getting better in his 2nd year as is expected.

*reminder, the lower the line the faster the time*

[itsbansheebitch]

More thoughts

I get both sides, but I feel a little confused they couldn't find four people in their +25 employees

Data analyst (Are you seriously telling me you couldn't personally email or even just HIRE matpat's team who do data analytics as part of Theorist Media to help??? The man would be overjoyed to help???)

Editor (Put the first $6 towards a can of coffee grounds, dude)

PR Team (Even, like, a single person, please, for the love of god)

Business Major (Or literally anyone that has taken a home ec/budgeting/personal finance class)

First, the Dish Granted series was started when gold leaf burgers were novel, now it's seen as tone deaf (for obvious reasons) it should have shifted to something like interviews with people who make that kind of food or local businesses (like parmesan cheese shops in Parma, Italy) or the history of food (like talking about the history of modern Native American slavery on Californian wine vinyards). Not to mention the untapped potential of Food Fraud topics. Either shift it, or scrap it. Any data analyst or chronically online person could tell you that.

Second, why did you keep "anyone can afford $6 a month" in? Are the editors asleep at the wheel? Are they overworked? What is going on? You know damn well to not make generalizations about what people can afford. That's NEVER a good idea, especially when you KNOW (because YT gives you analytics) that most of your viewers are young (16/18-30/35 range, I'd guess) who probably, either 1, are still in school and either arent paid well/dont have jobs OR 2, arent paid well and tired of people's shit, like people who own businesses talking about "tough financial decisions." To them, Watcher isn't going to look different from the other people talking like that, because this was so sudden, with no input from fans, and in the video you hear shit like "anyone can afford [X]." To be frank, it wouldn't really matter what the amount is, because that generalization goes against the message they have stood by for years. THAT is a slap in the face.

Third, what are yall doing with the budgeting? Every artist has a right to make art that they are proud of. Every artist deserves to have their work seen if they so choose. Every artist deserves to make a living. HOWEVER, there are MANY options online when it comes to making money, especially on YT. You could get into marketing, data analysis, expanding your demographic, looking at what people are interested in right now VS what will stand the test of time (not gold leaf burgers), etc.

You have to either have these skills, develop these skills, or hire someone to do it for you. It's understandable that you would want a team behind the production, but I find +25 employees to be WAY too many people, especially in LA. Bailey Sarian has a Dark History section on her YT (and Spotify podcast) where she has hired historians to help make sure her episodes are as accurate as possible. You've caught heat before from Puppet History's missing & incorrect info, you should do the same. She has about three (3) "intermissions" per episode for ad breaks. I never see anyone complain. People WOULD listen to yall talk for that long (+1 hour videos), tbh, though that's not necessary.

Why are yall out here with Teslas, expensive food, new gear, scripts (where there weren't scripts before, PH is different, that makes sense), and "better than TV" level sets??? I need to put your accountant in this week's church prayer list what the actual hell??? Ya'll, this video is literally the meme:

Guys help me budget:

LA Rent: 2K per month

Videos: 100K per vid

+25 Employees: God only knows

New stuff for videos: Don't get me started

Like, are you serious?

You have a right to do whatever you want with your art. You have a right to charge whatever you'd like for that art. You have a right to make a living from your art and you have a right to ask your fans for money.

Your fans have a right to be angry when they've been supporting yall for, what, almost 10 years? They have a right to choose when and where to spend their money even when you've made an impact. They have a right to feel betrayed, especially when there are better options (like Nebula or consulting with Theorist Media).

Fans DO NOT have a right to be racist to any members of Watcher, now that they have made a decision they do not agree with.

I personally, think this is a really silly decision and could have been solved (haha solved) with a simple YT poll, but apparently we had to get... this. I respect their decision, I just don't think it was a smart one. I wish them the best, and I hope they find a better solution. Any further comment from me will depend on what steps they take next.

[educationmore]

Python for Beginners: Launch Your Tech Career with Coding Skills

Are you ready to launch your tech career but don’t know where to start? Learning Python is one of the best ways to break into the world of technology—even if you have zero coding experience.

In this guide, we’ll explore how Python for beginners can be your gateway to a rewarding career in software development, data science, automation, and more.

Why Python Is the Perfect Language for Beginners

Python has become the go-to programming language for beginners and professionals alike—and for good reason:

Simple syntax: Python reads like plain English, making it easy to learn.

High demand: Industries spanning the spectrum are actively seeking Python developers to fuel their technological advancements.

Versatile applications: Python's versatility shines as it powers everything from crafting websites to driving artificial intelligence and dissecting data.

Whether you want to become a software developer, data analyst, or AI engineer, Python lays the foundation.

What Can You Do With Python?

Python is not just a beginner language—it’s a career-building tool. Here are just a few career paths where Python is essential:

Web Development: Frameworks like Django and Flask make it easy to build powerful web applications. You can even enroll in a Python Course in Kochi to gain hands-on experience with real-world web projects.

Data Science & Analytics: For professionals tackling data analysis and visualization, the Python ecosystem, featuring powerhouses like Pandas, NumPy, and Matplotlib, sets the benchmark.

Machine Learning & AI: Spearheading advancements in artificial intelligence development, Python boasts powerful tools such as TensorFlow and scikit-learn.

Automation & Scripting: Simple yet effective Python scripts offer a pathway to amplified efficiency by automating routine workflows.

Cybersecurity & Networking: The application of Python is expanding into crucial domains such as ethical hacking, penetration testing, and the automation of network processes.

How to Get Started with Python

Starting your Python journey doesn't require a computer science degree. Success hinges on a focused commitment combined with a thoughtfully structured educational approach.

Step 1: Install Python

Download and install Python from python.org. It's free and available for all platforms.

Step 2: Choose an IDE

Use beginner-friendly tools like Thonny, PyCharm, or VS Code to write your code.

Step 3: Learn the Basics

Focus on:

Variables and data types

Conditional statements

Loops

Functions

Lists and dictionaries

If you prefer guided learning, a reputable Python Institute in Kochi can offer structured programs and mentorship to help you grasp core concepts efficiently.

Step 4: Build Projects

Learning by doing is key. Start small:

Build a calculator

Automate file organization

Create a to-do list app

As your skills grow, you can tackle more complex projects like data dashboards or web apps.

How Python Skills Can Boost Your Career

Adding Python to your resume instantly opens up new opportunities. Here's how it helps:

Higher employability: Python is one of the top 3 most in-demand programming languages.

Better salaries: Python developers earn competitive salaries across the globe.

Remote job opportunities: Many Python-related jobs are available remotely, offering flexibility.

Even if you're not aiming to be a full-time developer, Python skills can enhance careers in marketing, finance, research, and product management.

If you're serious about starting a career in tech, learning Python is the smartest first step you can take. It’s beginner-friendly, powerful, and widely used across industries.

Whether you're a student, job switcher, or just curious about programming, Python for beginners can unlock countless career opportunities. Invest time in learning today—and start building the future you want in tech.

Globally recognized as a premier educational hub, DataMites Institute delivers in-depth training programs across the pivotal fields of data science, artificial intelligence, and machine learning. They provide expert-led courses designed for both beginners and professionals aiming to boost their careers.

Python Modules Explained - Different Types and Functions - Python Tutorial

[ohfuckohfucknoplease]

So let's talk about Ukraine vs Palestine. While generally I hate when people bring it up, cuz I lost people in the Ukraine war and I lost my home, I STILL GET IT. Fuck, I really do. The glaring and blatant racism that exists even in the humanitarian sector is CRAZY. I work in humanitarian aid, and in case you didn't know, the humanitarian sector has 4 humanitarian principles that everyone in the sector has to adhere to, one of them being NEUTRALITY.

Well, wouldn't you know, one of humanitarian organizations I had the displeasure of working with has signed an open letter that dismissed the notion of being neutral in the Ukrainian war. They signed a letter that urged people to stop being neutral on the issue. And when this was brought up to higher ups (not some no name local organization, but an INTERNATIONAL COMPANY), they said IT'S FINE. It's their choice to not be neutral and we have to respect that.

Which is fucking crazy, because imagine if something like this was discussed in literally any other context? Like right now, Palestinian speakers are getting invited on TV only for the interviewer to jump on the person that was grieving just a moment ago about their lost family, asking if they condone Hamas. Holy shit, isn't it fucking crazy?

Ukrainians had a big platform to advocate for their cause, they had loud voices tell it as it was instead of what the propaganda said. That's just true. A lot of Ukrainians are proud of that. It's only possible because, YES UKRAINIANS (mostly) ARE WHITE. Geopolitically there's more to that but that's not the point of the post at all. The blue eyed blonde Ukrainian stereotype isn't true in reality but it's true in minds of westerners. And that's really all that matters to them.

Are Palestinians asked the same questions Ukrainians were? Why not? What is the difference? Ask yourself that question, and know that the right answer is that Ukrainians are (mostly) white and more palpable for the western audiences.

Anyway, I urge all Ukrainians to actually read about this issue from Palestinians, stop falling for stupid propaganda, stop trying to whitewash Israel as well. Same goes to every Ukraine sympathiser. And before anyone comes here and tells me I don't know anything about Ukrainian situation and war... I work in a humanitarian field in crisis analytics and data analysis, I am Ukrainian, I am from Donbas, I lost relatives and friends in the war and my home, so maybe I even know more than some of y'all.

[allaboutkeyingo]

What is the most awesome Microsoft product? Why?

The “most awesome” Microsoft product depends on your needs, but here are some top contenders and why they stand out:

Top Microsoft Products and Their Awesome Features

1. Microsoft Excel

Why? It’s the ultimate tool for data analysis, automation (with Power Query & VBA), and visualization (Power Pivot, PivotTables).

Game-changer feature: Excel’s Power Query and dynamic arrays revolutionized how users clean and analyze data.

2. Visual Studio Code (VS Code)

Why? A lightweight, free, and extensible code editor loved by developers.

Game-changer feature: Its extensions marketplace (e.g., GitHub Copilot, Docker, Python support) makes it indispensable for devs.

3. Windows Subsystem for Linux (WSL)

Why? Lets you run a full Linux kernel inside Windows—perfect for developers.

Game-changer feature: WSL 2 with GPU acceleration and Docker support bridges the gap between Windows and Linux.

4. Azure (Microsoft Cloud)

Why? A powerhouse for AI, cloud computing, and enterprise solutions.

Game-changer feature: Azure OpenAI Service (GPT-4 integration) and AI-driven analytics make it a leader in cloud tech.

5. Microsoft Power BI

Why? Dominates business intelligence with intuitive dashboards and AI insights.

Game-changer feature: Natural language Q&A lets users ask data questions in plain English.

Honorable Mentions:

GitHub (owned by Microsoft) – The #1 platform for developers.

Microsoft Teams – Revolutionized remote work with deep Office 365 integration.

Xbox Game Pass – Netflix-style gaming with cloud streaming.

Final Verdict?

If you’re a developer, VS Code or WSL is unbeatable. If you’re into data, Excel or Power BI wins. For cutting-edge cloud/AI, Azure is king.

What’s your favorite?

If you need any Microsoft products, such as Windows , Office , Visual Studio, or Server , you can go and get it from our online store keyingo.com

[innovatexblog]

How Large Language Models (LLMs) are Transforming Data Cleaning in 2024

Data is the new oil, and just like crude oil, it needs refining before it can be utilized effectively. Data cleaning, a crucial part of data preprocessing, is one of the most time-consuming and tedious tasks in data analytics. With the advent of Artificial Intelligence, particularly Large Language Models (LLMs), the landscape of data cleaning has started to shift dramatically. This blog delves into how LLMs are revolutionizing data cleaning in 2024 and what this means for businesses and data scientists.

The Growing Importance of Data Cleaning

Data cleaning involves identifying and rectifying errors, missing values, outliers, duplicates, and inconsistencies within datasets to ensure that data is accurate and usable. This step can take up to 80% of a data scientist's time. Inaccurate data can lead to flawed analysis, costing businesses both time and money. Hence, automating the data cleaning process without compromising data quality is essential. This is where LLMs come into play.

What are Large Language Models (LLMs)?

LLMs, like OpenAI's GPT-4 and Google's BERT, are deep learning models that have been trained on vast amounts of text data. These models are capable of understanding and generating human-like text, answering complex queries, and even writing code. With millions (sometimes billions) of parameters, LLMs can capture context, semantics, and nuances from data, making them ideal candidates for tasks beyond text generation—such as data cleaning.

To see how LLMs are also transforming other domains, like Business Intelligence (BI) and Analytics, check out our blog How LLMs are Transforming Business Intelligence (BI) and Analytics.

Traditional Data Cleaning Methods vs. LLM-Driven Approaches

Traditionally, data cleaning has relied heavily on rule-based systems and manual intervention. Common methods include:

Handling missing values: Methods like mean imputation or simply removing rows with missing data are used.

Detecting outliers: Outliers are identified using statistical methods, such as standard deviation or the Interquartile Range (IQR).

Deduplication: Exact or fuzzy matching algorithms identify and remove duplicates in datasets.

However, these traditional approaches come with significant limitations. For instance, rule-based systems often fail when dealing with unstructured data or context-specific errors. They also require constant updates to account for new data patterns.

LLM-driven approaches offer a more dynamic, context-aware solution to these problems.

How LLMs are Transforming Data Cleaning

1. Understanding Contextual Data Anomalies

LLMs excel in natural language understanding, which allows them to detect context-specific anomalies that rule-based systems might overlook. For example, an LLM can be trained to recognize that “N/A” in a field might mean "Not Available" in some contexts and "Not Applicable" in others. This contextual awareness ensures that data anomalies are corrected more accurately.

2. Data Imputation Using Natural Language Understanding

Missing data is one of the most common issues in data cleaning. LLMs, thanks to their vast training on text data, can fill in missing data points intelligently. For example, if a dataset contains customer reviews with missing ratings, an LLM could predict the likely rating based on the review's sentiment and content.

A recent study conducted by researchers at MIT (2023) demonstrated that LLMs could improve imputation accuracy by up to 30% compared to traditional statistical methods. These models were trained to understand patterns in missing data and generate contextually accurate predictions, which proved to be especially useful in cases where human oversight was traditionally required.

3. Automating Deduplication and Data Normalization

LLMs can handle text-based duplication much more effectively than traditional fuzzy matching algorithms. Since these models understand the nuances of language, they can identify duplicate entries even when the text is not an exact match. For example, consider two entries: "Apple Inc." and "Apple Incorporated." Traditional algorithms might not catch this as a duplicate, but an LLM can easily detect that both refer to the same entity.

Similarly, data normalization—ensuring that data is formatted uniformly across a dataset—can be automated with LLMs. These models can normalize everything from addresses to company names based on their understanding of common patterns and formats.

4. Handling Unstructured Data

One of the greatest strengths of LLMs is their ability to work with unstructured data, which is often neglected in traditional data cleaning processes. While rule-based systems struggle to clean unstructured text, such as customer feedback or social media comments, LLMs excel in this domain. For instance, they can classify, summarize, and extract insights from large volumes of unstructured text, converting it into a more analyzable format.

For businesses dealing with social media data, LLMs can be used to clean and organize comments by detecting sentiment, identifying spam or irrelevant information, and removing outliers from the dataset. This is an area where LLMs offer significant advantages over traditional data cleaning methods.

For those interested in leveraging both LLMs and DevOps for data cleaning, see our blog Leveraging LLMs and DevOps for Effective Data Cleaning: A Modern Approach.

Real-World Applications

1. Healthcare Sector

Data quality in healthcare is critical for effective treatment, patient safety, and research. LLMs have proven useful in cleaning messy medical data such as patient records, diagnostic reports, and treatment plans. For example, the use of LLMs has enabled hospitals to automate the cleaning of Electronic Health Records (EHRs) by understanding the medical context of missing or inconsistent information.

2. Financial Services

Financial institutions deal with massive datasets, ranging from customer transactions to market data. In the past, cleaning this data required extensive manual work and rule-based algorithms that often missed nuances. LLMs can assist in identifying fraudulent transactions, cleaning duplicate financial records, and even predicting market movements by analyzing unstructured market reports or news articles.

3. E-commerce

In e-commerce, product listings often contain inconsistent data due to manual entry or differing data formats across platforms. LLMs are helping e-commerce giants like Amazon clean and standardize product data more efficiently by detecting duplicates and filling in missing information based on customer reviews or product descriptions.

Challenges and Limitations

While LLMs have shown significant potential in data cleaning, they are not without challenges.

Training Data Quality: The effectiveness of an LLM depends on the quality of the data it was trained on. Poorly trained models might perpetuate errors in data cleaning.

Resource-Intensive: LLMs require substantial computational resources to function, which can be a limitation for small to medium-sized enterprises.

Data Privacy: Since LLMs are often cloud-based, using them to clean sensitive datasets, such as financial or healthcare data, raises concerns about data privacy and security.

The Future of Data Cleaning with LLMs

The advancements in LLMs represent a paradigm shift in how data cleaning will be conducted moving forward. As these models become more efficient and accessible, businesses will increasingly rely on them to automate data preprocessing tasks. We can expect further improvements in imputation techniques, anomaly detection, and the handling of unstructured data, all driven by the power of LLMs.

By integrating LLMs into data pipelines, organizations can not only save time but also improve the accuracy and reliability of their data, resulting in more informed decision-making and enhanced business outcomes. As we move further into 2024, the role of LLMs in data cleaning is set to expand, making this an exciting space to watch.

Large Language Models are poised to revolutionize the field of data cleaning by automating and enhancing key processes. Their ability to understand context, handle unstructured data, and perform intelligent imputation offers a glimpse into the future of data preprocessing. While challenges remain, the potential benefits of LLMs in transforming data cleaning processes are undeniable, and businesses that harness this technology are likely to gain a competitive edge in the era of big data.

[mostafizux24]

Crypto trading mobile app

Designing a Crypto Trading Mobile App involves a balance of usability, security, and aesthetic appeal, tailored to meet the needs of a fast-paced, data-driven audience. Below is an overview of key components and considerations to craft a seamless and user-centric experience for crypto traders.

Key Elements of a Crypto Trading Mobile App Design

1. Intuitive Onboarding

First Impressions: The onboarding process should be simple, guiding users smoothly from downloading the app to making their first trade.

Account Creation: Offer multiple sign-up options (email, phone number, Google/Apple login) and include KYC (Know Your Customer) verification seamlessly.

Interactive Tutorials: For new traders, provide interactive walkthroughs to explain key features like trading pairs, order placement, and wallet setup.

2. Dashboard & Home Screen

Clean Layout: Display an overview of the user's portfolio, including current balances, market trends, and quick access to popular trading pairs.

Market Overview: Real-time market data should be clearly visible. Include options for users to view coin performance, historical charts, and news snippets.

Customization: Let users customize their dashboard by adding favorite assets or widgets like price alerts, trading volumes, and news feeds.

3. Trading Interface

Simple vs. Advanced Modes: Provide two versions of the trading interface. A simple mode for beginners with basic buy/sell options, and an advanced mode with tools like limit orders, stop losses, and technical indicators.

Charting Tools: Integrate interactive, real-time charts powered by TradingView or similar APIs, allowing users to analyze market movements with tools like candlestick patterns, RSI, and moving averages.

Order Placement: Streamline the process of placing market, limit, and stop orders. Use clear buttons and a concise form layout to minimize errors.

Real-Time Data: Update market prices, balances, and order statuses in real-time. Include a status bar that shows successful or pending trades.

4. Wallet & Portfolio Management

Asset Overview: Provide an easy-to-read portfolio page where users can view all their holdings, including balances, performance (gains/losses), and allocation percentages.

Multi-Currency Support: Display a comprehensive list of supported cryptocurrencies. Enable users to transfer between wallets, send/receive assets, and generate QR codes for transactions.

Transaction History: Offer a detailed transaction history, including dates, amounts, and transaction IDs for transparency and record-keeping.

5. Security Features

Biometric Authentication: Use fingerprint, facial recognition, or PIN codes for secure logins and transaction confirmations.

Two-Factor Authentication (2FA): Strong security protocols like 2FA with Google Authenticator or SMS verification should be mandatory for withdrawals and sensitive actions.

Push Notifications for Security Alerts: Keep users informed about logins from new devices, suspicious activities, or price movements via push notifications.

6. User-Friendly Navigation

Bottom Navigation Bar: Include key sections like Home, Markets, Wallet, Trade, and Settings. The icons should be simple, recognizable, and easily accessible with one hand.

Search Bar: A prominent search feature to quickly locate specific coins, trading pairs, or help topics.

7. Analytics & Insights

Market Trends: Display comprehensive analytics including top gainers, losers, and market sentiment indicators.

Push Alerts for Price Movements: Offer customizable price alert notifications to help users react quickly to market changes.

Educational Content: Include sections with tips on technical analysis, crypto market basics, or new coin listings.

8. Social and Community Features

Live Chat: Provide a feature for users to chat with customer support or engage with other traders in a community setting.

News Feed: Integrate crypto news from trusted sources to keep users updated with the latest market-moving events.

9. Light and Dark Mode

Themes: Offer both light and dark mode to cater to users who trade at different times of day. The dark mode is especially important for night traders to reduce eye strain.

10. Settings and Customization

Personalization Options: Allow users to choose preferred currencies, set trading limits, and configure alerts based on their personal preferences.

Language and Regional Settings: Provide multilingual support and regional settings for global users.

Visual Design Considerations

Modern, Minimalist Design: A clean, minimal UI is essential for avoiding clutter, especially when dealing with complex data like market trends and charts.

Color Scheme: Use a professional color palette with accents for call-to-action buttons. Green and red are typically used for indicating gains and losses, respectively.

Animations & Micro-interactions: Subtle animations can enhance the experience by providing feedback on button presses or transitions between screens. However, keep these minimal to avoid slowing down performance.

Conclusion

Designing a crypto trading mobile app requires focusing on accessibility, performance, and security. By blending these elements with a modern, intuitive interface and robust features, your app can empower users to navigate the fast-paced world of crypto trading with confidence and ease.

[sethshead]

"'One of the most significant differences between the images of the two sides was presence of analytical vs. emotional propaganda frame. While the majority of Israeli images featured the analytical propaganda frame, a significantly high proportion of Hamas images included the emotional propaganda frame (Table 2).

"'Most Israeli images focused on factual elements regarding damages Israel sustained during the confrontation as well as military capabilities of and threats from Hamas. Infographics that visually presented data frequently appeared on Israeli tweets with some infographics showingHamas’ missile launch sites.

"'Images posted by Hamas often resorted to the emotional propaganda frame to increase effects of their messages. Hamas frequently tweeted images of sobbing parents or relatives in front of babies or children killed or injured by Israeli airstrikes (Figure 4). Hamas also posted an image contrasting a Caucasian girl sleeping on a comfortable bed holding a teddy bear with Palestinian children killed and laid in a hospital bed. The caption for the image read, 'That’s the way children all over the world sleep. That’s the way our children sleep forever.''"

h/t Malaika Mrtn

The early postwar French theorists, deconstructionists and poststructuralists, sought to understand how it was that totalitarian propaganda could be so persuasive, or at least successful at creating false equivalencies. Fast forward to today, and those warnings have instead become a playbook for extremists, media, and academia alike.

[riyakakria]

Digital marketing online course in Mohali and Chandigarh | Param digital marketing

Digital Marketing Course – Learn Online and Save Money

Below is an outline of an online digital marketing course content. This content is a general guideline and can be adapted and expanded based on the specific needs of the course and the level of expertise of the learners. Learn Advanced Digital Marketing with DKI and DSA Ads only in 29999/– now – Join Now

Digital marketing online course in Mohali and Chandigarh.

Understanding digital marketing and its importance

Evolution of digital marketing

Digital marketing vs. traditional marketing

Key concepts and terminology

Book Class Now

Module 2: Website Planning and Development

Importance of a website in digital marketing

Domain registration and hosting

Website design principles and best practices

User experience (UX) and user interface (UI)

Mobile responsiveness and optimization

Introduction to Content Management Systems (CMS) like WordPress

Module 3: Search Engine Optimization (SEO)

Want to join click here

Understanding search engines and how they work

On-page SEO: Keyword research, Density and Proximity, meta tags and Description, headings, content and image optimization

Off-page SEO: Link building, backlinks, and domain authority, DA/PA Checking

Technical SEO: Website speed, site structure, and crawlability, Mobile Friendly, Security

Local SEO and Google My Business Page Optimization

Module 4: Content Marketing

Importance of quality content writing in the digital landscape

Creating a content writing strategy

Types of content: blog posts, articles, infographics, videos, etc.

Content promotion and distribution

Content analytics and measuring success

Module 5: Social Media Marketing

Overview of major social media platforms (Facebook, Twitter, LinkedIn, Instagram, Pinterest, Tumblr etc.)

Creating a social media strategy

Social media advertising and sponsored posts, Event Creating

Building and engaging with an online community

Social media analytics and performance tracking

Module 6: Email Marketing

Building an email marketing list

Creating effective email campaigns

Email marketing tools and platforms

Personalization and segmentation

Analyzing email marketing performance

Module 7: Pay-Per-Click (PPC) Advertising

Introduction to PPC Advertising and Google Ads

Creating PPC campaigns and ad groups

Keyword research and selection

Ad copywriting and A/B testing

Bid strategies and budget management

Module 8: Display and Banner Advertising

Understanding display advertising and its formats

Display advertising platforms (Google Display Network, etc.)

Targeting options for display ads

Designing effective banner ads

Display ad performance tracking and optimization

Module 9: Video Marketing

The rise of video content in digital marketing

Creating engaging video content

Video SEO and optimizing for platforms like YouTube

Video advertising and sponsored content

Analyzing video marketing metrics

Module 10: Analytics and Data-driven Marketing

Introduction to marketing analytics

Setting up Google Analytics and understanding key metrics

Data analysis for decision-making

A/B testing and conversion rate optimization (CRO)

Customer journey and attribution modeling

Module 11: Mobile Marketing

Mobile marketing trends and opportunities

Mobile app marketing and optimization

SMS marketing and push notifications

Mobile advertising and location-based marketing

Mobile analytics and tracking

Module 12: Digital Marketing Strategy and Planning

Developing a comprehensive digital marketing strategy

Integrating various digital marketing channels

Budget allocation and resource planning

Measuring ROI and KPIs for digital campaigns

Case studies and real-world examples

Module 13: Legal and Ethical Considerations

Privacy and data protection laws (e.g., GDPR)

Ethical practices in digital marketing

Dealing with online reviews and reputation management

Handling customer data responsibly

Module 14: Emerging Trends in Digital Marketing

Artificial Intelligence (AI) and machine learning in marketing

Voice search and voice-activated devices

Augmented Reality (AR) and Virtual Reality (VR) marketing

Influencer marketing and social media trends

Future outlook and staying ahead in the digital marketing landscape

Module 15: Final Project and Certification

Capstone project applying concepts learned throughout the course

Presentations and feedback sessions

Issuance of course completion certificates

Remember that this is just a general outline, and the content and depth of each module can be adjusted to suit the course’s duration, audience level, and objectives. Additionally, including practical exercises, case studies, and hands-on projects will enhance the learning experience. We provide 100% Job Placement after completion of Course.

Digital marketing online course in Mohali and Chandigarh.

[j0shm0]

How we all feeling after Japan? With it bringing in spring versus early fall the weather sure was different which lead to some interesting track/racing conditions in my opinion. Yuki sure did deliver a worldy performance in his home race. But that's not what we are here for, we are here to see how the Rookies are improving in their sophomore years.

Logan in 2023 along with a decent amount of others didn't finish the race, and this year in 2024 he was doing well to pressure for points until lap 41 where he went super wide having to reverse onto the tack and put again for new tyres. But outside that one off track event he was still lapping faster than 2023 overall.

As for Oscar he finished on the podium in 2023 and was not so lucky this year with the improvements across the field with teams like Ferrari on top of George and Checo being on form. Regardless of finishing position it can be seen that Oscar was indeed lapping much much faster then he did last year which just goes to show how tight the field is across the top 5 teams.

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Predictive vs Prescriptive vs Descriptive Analytics Explained 

Business analytics leveraging data patterns for strategic moves comes in three key approaches – descriptive identifying “what has occurred", predictive forecasting “what could occur” and prescriptive recommending “what should occur” to optimize decisions. We decode the science behind each for aspiring analytics professionals.

Descriptive analytics convert volumes of historical data into insightful summaries around metrics revealing business health, customer trends, operational efficiencies etc. using direct analysis, aggregation and mining techniques producing current reports. 

Predictive analytics forecast unknown future probabilities applying statistical, econometric and machine learning models over existing data to minimize uncertainties and capture emerging behaviors early for mitigation actions. Risk models simulate scenarios balancing upside/downside tradeoffs. 

Prescriptive analytics take guidance one step further by dynamically recommending best decision options factoring in key performance indicators for business objective improvements after predicting multiple futures using bell curve simulations. Optimization algorithms deliver preferred actions.

While foundational data comprehension and wrangling abilities fuel all models – pursuing analytics specializations focused on statistical, computational or operational excellence boosts career-readiness filling different priorities global employers seek!

Posted By:

Aditi Borade, 4th year Barch,

Ls Raheja School of architecture 

Disclaimer: The perspectives shared in this blog are not intended to be prescriptive. They should act merely as viewpoints to aid overseas aspirants with helpful guidance. Readers are encouraged to conduct their own research before availing the services of a consultant.

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Mangools Review: Interactive Analytics for Marketers

Interactive Analytics for Marketer

What is a Marketing Automation Tool and How Does It Work?

Marketing automation tools are software programs that help marketers grow their businesses. They are designed to help marketers automate marketing tasks, such as email campaigns, social media content, and website updates.

Marketing automation refers to the act of using technology to manage certain aspects of a business's marketing activities. These automated tasks can include things like sending regular emails to customers who have given consent for receiving them, publishing content across social media channels, and updating a company's website with new products or services it offers.

Marketing automation tools gather information about visitors to a company's website or people who use its products. This information is then used by the software program to determine which messages should be sent out and when they should be delivered.

keywords: marketing automation, customer database, marketing analytics 

How Mangools Helps You Achieve the Goals in Your Marketing Strategy

Mangools offers a range of features to help you achieve the goals in your marketing strategy. You can use a number of tools to create a comprehensive plan that will let you execute your strategies more efficiently.

keywords: sales funnel analysis, sales funnel optimization, social media automation

How Mangools Helps You Achieve the Goals in Your Marketing Strategy

Mangools offers a range of features to help you achieve the goals in your marketing strategy. You can use a number of tools to create a comprehensive plan that will let you execute your strategies more efficiently.

keywords: sales funnel analysis, sales funnel optimization, social media a

Mangool Benefits for B2B Companies

Mangool is a technology company that specializes in creating the fastest and most accurate lead generation engine. The company has been helping many companies from different industries to generate more qualified leads, which in turn helps their sales team close deals faster. The Mangool Benefits for B2B Companies section will introduce the benefits that help B2B companies with Mangools product.

Mangool’s lead generation engine provides a one-of-a-kind solution for generating quality B2B leads by using artificial intelligence to sift through thousands of data signals and connect marketers with the right prospects.

keywords: business intelligence dashboard, business data dashboard

Mangools Budget-Friendly Pricing and Powerful Features

Mangools is a new and affordable software for automatic content generation. This software has powerful features such as:

- Text spinning: It provides text spinning and paraphrasing that will give you the fres

- Article Spinning: The software can spin your text into 100 different versions of it, so the target audience will not be bored while reading it.

- Keyword research: The software automatically searches for keywords related to your topic. This can help you generate more traffic to your blog or website by optimizing the content on it.

Mangools is a great tool for generating quality, affordable content in no time!

keywords: cost of mangools vs. other software, interactive analytics for marketers

The Conclusion of Mangools Review

h and unique content that you need.

- Article Spinning: The software can spin your text into 100 different versions of it, so the target audience will not be bored while reading it.

- Keyword research: The software automatically searches for keywords related to your topic. This can help you generate more traffic to your blog or website by optimizing the content on it.

Mangools is a great tool for generating quality, affordable content in no time!

keywords: cost of mangools vs. other software, interactive analytics for marketers

The Conclusion of Mangools Review

The article concludes with a few tips to help you get the most out of your SEO, including how to track keywords and stay on top of Google updates.

1) Track your keywords: The first step is to find out which keywords are converting best for you. This will enable you to focus less on meaningless or unproductive keywords, and concentrate on the ones that are making an impact for your bottom line.

2) Stay one step ahead of Google: Keeping up with Google updates is crucial, as they can have a major impact on SEO rankings. If you know that an update is coming up, it's much easier to prepare than reacting after the fact.

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What is Solr – Comparing Apache Solr vs. Elasticsearch

In the world of search engines and data retrieval systems, Apache Solr and Elasticsearch are two prominent contenders, each with its strengths and unique capabilities. These open-source, distributed search platforms play a crucial role in empowering organizations to harness the power of big data and deliver relevant search results efficiently. In this blog, we will delve into the fundamentals of Solr and Elasticsearch, highlighting their key features and comparing their functionalities. Whether you're a developer, data analyst, or IT professional, understanding the differences between Solr and Elasticsearch will help you make informed decisions to meet your specific search and data management needs.

Overview of Apache Solr

Apache Solr is a search platform built on top of the Apache Lucene library, known for its robust indexing and full-text search capabilities. It is written in Java and designed to handle large-scale search and data retrieval tasks. Solr follows a RESTful API approach, making it easy to integrate with different programming languages and frameworks. It offers a rich set of features, including faceted search, hit highlighting, spell checking, and geospatial search, making it a versatile solution for various use cases.

Overview of Elasticsearch

Elasticsearch, also based on Apache Lucene, is a distributed search engine that stands out for its real-time data indexing and analytics capabilities. It is known for its scalability and speed, making it an ideal choice for applications that require near-instantaneous search results. Elasticsearch provides a simple RESTful API, enabling developers to perform complex searches effortlessly. Moreover, it offers support for data visualization through its integration with Kibana, making it a popular choice for log analysis, application monitoring, and other data-driven use cases.

Comparing Solr and Elasticsearch

Data Handling and Indexing

Both Solr and Elasticsearch are proficient at handling large volumes of data and offer excellent indexing capabilities. Solr uses XML and JSON formats for data indexing, while Elasticsearch relies on JSON, which is generally considered more human-readable and easier to work with. Elasticsearch's dynamic mapping feature allows it to automatically infer data types during indexing, streamlining the process further.

Querying and Searching

Both platforms support complex search queries, but Elasticsearch is often regarded as more developer-friendly due to its clean and straightforward API. Elasticsearch's support for nested queries and aggregations simplifies the process of retrieving and analyzing data. On the other hand, Solr provides a range of query parsers, allowing developers to choose between traditional and advanced syntax options based on their preference and familiarity.

Scalability and Performance

Elasticsearch is designed with scalability in mind from the ground up, making it relatively easier to scale horizontally by adding more nodes to the cluster. It excels in real-time search and analytics scenarios, making it a top choice for applications with dynamic data streams. Solr, while also scalable, may require more effort for horizontal scaling compared to Elasticsearch.

Community and Ecosystem

Both Solr and Elasticsearch boast active and vibrant open-source communities. Solr has been around longer and, therefore, has a more extensive user base and established ecosystem. Elasticsearch, however, has gained significant momentum over the years, supported by the Elastic Stack, which includes Kibana for data visualization and Beats for data shipping.

Document-Based vs. Schema-Free

Solr follows a document-based approach, where data is organized into fields and requires a predefined schema. While this provides better control over data, it may become restrictive when dealing with dynamic or constantly evolving data structures. Elasticsearch, being schema-free, allows for more flexible data handling, making it more suitable for projects with varying data structures.

Conclusion

In summary, Apache Solr and Elasticsearch are both powerful search platforms, each excelling in specific scenarios. Solr's robustness and established ecosystem make it a reliable choice for traditional search applications, while Elasticsearch's real-time capabilities and seamless integration with the Elastic Stack are perfect for modern data-driven projects. Choosing between the two depends on your specific requirements, data complexity, and preferred development style. Regardless of your decision, both Solr and Elasticsearch can supercharge your search and analytics endeavors, bringing efficiency and relevance to your data retrieval processes.

Whether you opt for Solr, Elasticsearch, or a combination of both, the future of search and data exploration remains bright, with technology continually evolving to meet the needs of next-generation applications.

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Data Cleaning in Data Science

Data cleaning is an integral part of data preprocessing viz., removing or correcting inaccurate information within a data set. This could mean missing data, spelling mistakes, and duplicates to name a few issues. Inaccurate information can lead to issues during analysis phase if not properly addressed at the earlier stages.

Data Cleaning vs Data Wrangling : Data cleaning focuses on fixing inaccuracies within your data set. Data wrangling, on the other hand, is concerned with converting the data’s format into one that can be accepted and processed by a machine learning model.

Data Cleaning steps to follow :

Remove irrelevant data

Resolve any duplicates issues

Correct structural errors if any

Deal with missing fields in the dataset

Zone in on any data outliers and remove them

Validate your data

At EduJournal, we understand the importance of gaining practical skills and industry-relevant knowledge to succeed in the field of data analytics / data science. Our certified program in data science and data analytics is designed to equip freshers / experienced with the necessary expertise and hands-on experience experience so they are well equiped for the job.

URL : http://www.edujournal.com