suhas Venkat’s Post

🚀 Day 138 | Day 139 | Day 140 of My Data Analytics Journey Today, I covered some important concepts that are essential for real-world data projects 👇 📊 BI Tools Review (Day 138) Explored different Business Intelligence tools like Power BI and Tableau, and understood their use cases. Learned how powerful data visualization can support better decision-making. ⚙️ Introduction to Model Deployment (Day 139) Building a machine learning model is not enough — deploying it is equally important. Learned the basic workflow of model deployment and how models are used in real-world applications. 🌐 Flask Basics (Day 140) Learned the basics of Flask — how to create web applications using Python and deploy machine learning models. This is a big step toward turning data projects into real products 💡 Consistency in learning is the key to growth 🔑 #Day138 #Day139 #Day140 #DataAnalytics #DataScience #BusinessIntelligence #PowerBI #Tableau #MachineLearning #ModelDeployment #Flask #Python #LearningJourney #Upskilling #CareerGrowth

Your Data Analyst journey starts here 📊 From Statistics → SQL → Python → Excel → BI Tools This roadmap is all you need to break into data. Stop overthinking. Start learning. 👉 Take the first step today. #DataAnalyst #DataScience #LearnData #SQL #PythonForData #ExcelSkills

The Blueprint to Data Analytics 🚀 1️⃣ Prerequisites (Math & Excel) 2️⃣ Data Wrangling (Python/Pandas) 3️⃣ Database Fundamentals (SQL) 4️⃣ Visualization (Tableau/Power BI) 5️⃣ EDA & Statistics 6️⃣ Portfolio Building 7️⃣ The Job Search Success doesn't happen overnight, but it does happen with a plan. Save this for your own journey! SLA Institute #DataAnalyst #TechCareer #Roadmap #DataVisualization

📊 Everyone talks about Data Science… but here’s what Data Analysts actually do 👇 Most people think it’s just “working with Excel” — it’s not. A Data Analyst: ✔ Cleans messy data 🧹 ✔ Finds hidden patterns 🔍 ✔ Builds dashboards that tell stories 📊 ✔ Helps businesses make smarter decisions 💡 Tools I use daily: 🐍 Python | 🗄️ SQL 📈 Pandas & NumPy 📊 Power BI & Advanced Excel And I’m currently diving deeper into 🤖 Machine Learning 👉 The goal isn’t just data… It’s turning data into decisions that matter. If you're learning data analytics too, let’s connect 🤝 #DataAnalytics #DataScience #MachineLearning #Python #SQL #PowerBI #LearningJourney

Most people think data analysis is just about charts and Excel sheets.But real data analysis is about asking the right questions. I'll explain with an example: If sales drop, it’s not just → “sales decreased by 10%” It’s : • Which segment dropped the most? • Was it due to pricing, seasonality, or user behavior? • What action can actually fix it? Tools like Python, SQL, or Power BI are just the medium the real skill is turning raw data into meaningful insights. Currently building my skills in SQL, Python, and data visualization and more importantly learning how to break down real-world problems.📊 #DataAnalytics #DataScience #SQL #Python #ProblemSolving

The "Big Picture" Approach Mastering the syntax of Python or the formulas in Excel is only half the battle. The true magic happens when you understand the data lifecycle as a cohesive story. Looking at this toolkit, it is easy to get overwhelmed by the number of software options. But I like to view them as specialized instruments for specific stages: Foundation (Data Collection): SQL and spreadsheets are where the raw truth lives. The Heavy Lifting (Cleaning & Analysis): This is where tools like Python and R act as the ultimate janitors and translators for messy, real-world data. The Bridge (Visualization): Tableau and Power BI turn abstract numbers into visual narratives that anyone can understand. But notice row 5: Supporting Skills. Tools will change, software will update, and new AI will emerge. However, solid Statistics, Data Storytelling, and Critical Thinking are evergreen. You can know every Python library by heart, but without a grasp of the underlying variance and probability, the output is just noise. Which of these stages do you find yourself spending the most time in? Let's connect and talk data! 🤝 #DataAnalytics #Python #RStats #SQL #BusinessIntelligence #DataScience #Statistics #MST #MastercardFoundation #Baobab #YALI

Most of the time, we learn tools in data science… Python, SQL, Power BI, ML models… But I kept thinking — 𝐡𝐨𝐰 𝐝𝐨𝐞𝐬 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐜𝐨𝐧𝐧𝐞𝐜𝐭 𝐢𝐧 𝐚 𝐫𝐞𝐚𝐥 𝐬𝐲𝐬𝐭𝐞𝐦? So I tried to map it out. I designed this “Data Analytics Engine” to understand the full flow: From 𝐜𝐨𝐥𝐥𝐞𝐜𝐭𝐢𝐧𝐠 𝐫𝐚𝐰 𝐝𝐚𝐭𝐚 → 𝐜𝐥𝐞𝐚𝐧𝐢𝐧𝐠 → 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 → 𝐦𝐨𝐝𝐞𝐥𝐢𝐧𝐠 → 𝐯𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 → 𝐫𝐞𝐚𝐥 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬. . What I found interesting is — it’s not just a one-way process. There’s always a feedback loop, where past data and outcomes improve future decisions. This shifted my mindset from just “building dashboards” to actually thinking in terms of systems. Still learning and improving this… . Would love to hear your thoughts — what would you change or add? #DataAnalytics #DataScience #MachineLearning #Python #SQL #PowerBI #LearningJourney

Start learning Data Analysis today https://lnkd.in/dz3AXtmy You don’t need 20 channels Pick few Stay consistent Math • 3Blue1Brown • Ghrist Math Use them to understand concepts Not to memorize SQL • The Magic SQL Practice after every video Write queries daily Python • Corey Schafer Follow step by step Code with him Excel • ExcelIsFun Learn Formulas Pivot tables Power BI • Guy in a Cube Focus on dashboards Not buttons Machine Learning • StatQuest • DeepLearningAI Understand Why models work Not just how Data Analysis • Alex The Analyst This is closest to real job work How to use them Watch less Do more After every video • Write code • Solve problem • Build mini project Simple weekly plan Day 1–2 Python Day 3 SQL Day 4 Excel Day 5 Project Repeat Ask yourself Are you practicing Or just consuming content More resources https://lnkd.in/d_3vb6RP #DataAnalysis #Python #SQL #LearnData

🚀 Day 10 – Pandas Practice Today I worked on real-world data operations using Pandas: ✔ Merging datasets (SQL-style joins) ✔ Creating new columns (Bonus, Performance Bonus) ✔ Filtering with conditions (.loc[]) ✔ Sorting & finding top values ✔ Using apply() & lambda 💡 Biggest learning: Filter → Sort → Select = Real data analysis workflow 📊 Mini challenge: Filtered IT employees → sorted by salary → picked top performers with bonus 💯 Slowly moving from learning syntax to thinking like a data analyst. #DataScience #Python #Pandas #LearningInPublic

You don’t always need expensive courses to become a Data Analyst… You just need the right roadmap + the right resources And guess what? Some of the best ones are FREE on YouTube. Here’s what I mean👇 📊 Mathematics (your foundation) Start with channels that make concepts click, not confuse you 💻 SQL & Python (your tools) Learn how to query, manipulate and analyze real data 📈 Excel, Power BI & Tableau (your storytelling power) Because insights mean nothing if you can’t communicate them visually 🧠 Machine Learning (your edge) Not mandatory at the start, but a game-changer as you grow 💡 The mistake most beginners make? They jump between random tutorials without structure. Instead: 👉 Pick ONE path 👉 Stay consistent 👉 Build projects as you learn Because watching videos doesn’t make you a data analyst… Solving problems does. Here is a picture of some of the good YouTube channels you can use to learn. Enjoy #DataAnalytics #DataScience #SQL #Python #PowerBI #Excel #Tableau #MachineLearning #LearnToCode #CareerGrowth