Rimon Ghosh’s Post

While learning different tools for data analysis, I’ve started noticing something interesting. The tools keep changing, but the way you think about data stays the same. Whether it’s Excel, SQL, Power BI, or Python, the real work is still about: - Understanding the dataset - Asking the right questions - Cleaning the data properly - Finding meaningful patterns The tools help with scale and efficiency, but the core thinking remains the same. For me, this has been an important reminder while learning Python for data analysis. #DataAnalytics #LearningJourney #AspiringDataAnalyst #ContinuousLearning

Everyone asks which tool they should learn first? Excel? SQL? Power BI? Python? And I always answer the same way: The best tool is the one you can practice with consistently. Not the most popular one. Not the one with the most YouTube tutorials. Not the one every job description mentions. The one you can open today, work with for two hours, and come back to tomorrow. Here is what I see constantly as a data tutor: Students who start with Python because everyone says it is the future but spend three weeks just trying to install it correctly. Students who download Power BI because the dashboards look impressive but their laptop cannot run it without freezing every ten minutes. Students who jump from tool to tool every time they hit a difficulty and six months later they have touched everything and mastered nothing. The tool does not make the analyst. Consistent practice makes the analyst. Start with Excel. It runs on almost any device. It is in every workplace on the planet and the thinking it builds- how to structure data, how to ask questions of numbers, how to spot what looks wrong. That thinking transfers to every other tool you will ever learn. Master one tool completely before you touch the next one. You're welcome 🤗 #dataanalyst #datagirl #excel

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You don't need to learn 10 tools to get started in Data Science 🤦♀️ You need these 5 👇 🐍 Python The #1 language for data science. flexible, beginner friendly, and has libraries for literally everything. 🗄️ SQL Every company stores data in databases. SQL is how you talk to them. non negotiable. 📊 Excel Underrated fr. great for quick analysis and still used in 90% of companies. 📈 Power BI / Tableau Turn your data into visuals that actually make sense to people who don't code. 📓 Jupyter Notebook Where you write, run, and present your Python code all in one place. start with Python + SQL. add the rest as you go. you don't need all of them on day 1... (post 5 of the 30-day Data Science Learning Ladder 🪜) which one of these are you currently learning? 👇 #DataScience #Python #SQL #LearningInPublic #TechEducation

The 4 Powerful Tools Every Data Analyst Must Master in 2026 Breaking down Data Analytics into 4 core tools: 🗄️ SQL — Extract the data 🐍 Python — Clean & analyze the data 📊 Power BI — Build dashboards 📈 Matplotlib — Visualize insights 💡 Most beginners make one mistake: They try to learn everything at once. Instead, focus on mastering these 4 tools step by step. 🎯 My approach: 1️⃣ Start with SQL (data retrieval) 2️⃣ Move to Python (data processing) 3️⃣ Learn visualization (Matplotlib) 4️⃣ Build dashboards (Power BI) Consistency > Complexity. 💬 Which tool are you currently learning? #DataAnalytics #Python #SQL #PowerBI #Matplotlib #LearningJourney #TechSkills #CareerGrowth #DataScience #Analytics

One mistake I made while learning Data Analytics: Focusing too much on tools ❌ Python, Tableau, Power BI… I tried to learn everything. Result? Confusion. What actually helped: 👉 Understanding the problem first 👉 Then using the right tool Tools don’t make you a Data Analyst. Thinking does. Don’t repeat this mistake. #DataAnalytics #Learning #CareerAdvice

Data Analytics Portfolio | SQL • Python • Power BI Projects I’ve built this portfolio to showcase my work in SQL, Python, Machine Learning, and Power BI. It includes projects where I worked on: • Data cleaning and exploratory analysis using SQL • Machine learning models built with Python • Interactive dashboards created in Power BI The goal was simple- move beyond theory and start solving real data problems through projects. You can explore the portfolio here: 🔗 https://lnkd.in/gMtenAjV I’m always open to feedback and conversations around data analytics and machine learning. #DataAnalytics #SQL #Python #PowerBI #MachineLearning

🛠️ Every Data Analytics tool you need — in one place. Here's a complete breakdown of 40+ tools across 9 categorise. Save this post for reference. 🔖 This is part of my complete Data Analytics Roadmap — a 5-phase guide from beginner to expert. #DataAnalytics #DataScience #Python #SQL #MachineLearning #DataEngineering #MLOps #BigData #Tableau #PowerBI #AyushKumarSahu

🐍 Python Data Analysis Project I recently completed a data analysis project using Python (pandas, seaborn, matplotlib) as part of my transition into data analytics. This time I worked with a real dataset (restaurant sales data), which made the learning process much more practical and meaningful. 🔍 What I did: • Data exploration using pandas • Calculated key metrics (average bill, tip percentage, etc.) • Grouped and compared data (by day, gender, smoker status) • Built visualizations to better understand patterns 📊 Some insights: • Higher bills are more common on weekends • Tip amounts increase with total bill • Tip percentage varies across different groups 💡 Key takeaway: Working with real datasets helps me learn much faster than abstract examples — it feels much closer to real analytical work. I’m continuing to build my portfolio and currently focusing on: • SQL (main priority) • Tableau / Power BI • Real-world data projects 👉 Project on GitHub: https://lnkd.in/dhizXesv Feel free to check my work or share feedback 🙌 #python #dataanalytics #pandas #datavisualization #careertransition

“Day 1 of my Data Analytics Journey 🚀 Today I started learning Data Analytics. I will learn Excel, SQL, Python & Power BI step by step. My goal is to become a Data Analyst and achieve financial independence. I will share my progress here daily. #DataAnalytics #Learning #Excel #SQL #Python”