Over the years, while leading analytics team, teaching Analytics & Data Science, I’ve noticed a common pattern 👇 📊 Analysts spend a huge amount of time on: Reading & cleaning data 🧹 Writing repetitive code 💻 Creating pivot tables & summaries 📋 Formatting tables, colors & charts 🎨 …and very little time on what actually matters most 👉 analysis & interpretation 🧠 🤖 How AI can genuinely help in Analytics AI is no longer just about complex models. It can be a powerful enabler for day-to-day analytics: ➡️ 🧭 Shows only relevant options based on your task & data➡️ ⏱️ Reduces time spent on setup & coding➡️ 📊 Instantly creates: Summary tables with color coding Corresponding charts & visuals➡️ ✅ Produces results without trial-and-error➡️ 🔴 Clearly explains if something is not possible 🧩 Do you really need to code for everything? For many analytics tasks: Pivot table creation Summary-based analysis Trend & comparison analysis ❌ Coding is not mandatory✅ Thinking & interpretation are AI can handle the enablers so that you can focus on insights. 🚀 AI in Machine Learning (Step-by-Step Guidance) AI can also:➡️ 🔍 Understand your data type➡️ 🪜 Guide you step-by-step through ML workflows➡️ ✏️ Allow you to modify or override steps, if you wish➡️ 🚫 Prevent invalid paths that lead to errors This makes learning & applying ML far more intuitive and reliable. 🎥 See AI-driven analytics in action (4 use cases in 1 hour) ▶️ Demo Video: Classification, Text Mining, Time Series Forecasting and Visual Analysis - You’ll see how AI can drastically cut down execution time and shift focus back to analysis, where real value lies. https://youtu.be/KzqqrXvdaF8 💡 Final thought:If AI can save hours on coding, cleaning, and formatting, imagine how much better your decisions become when that time is reinvested in thinking. Happy learning & deeper analysis 🚀
