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.
💡 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 🚀