Built by a learner, for learners
ChaturIQ exists for one reason: to help you walk into your SQL interview ready, not just familiar with the syntax.
Why "ChaturIQ"? Chatur (चतुर) is Hindi for clever: the kind of sharp you only get by doing, not by watching. Our motto is ratta nahi, riyaaz: no rote learning, just practice. IQ is the part you build here, one question at a time.
Why I built it
I learned SQL from YouTube. There are excellent channels, but watching someone else write a query is not the same as writing it yourself, and the practice I could find stopped at the basics.
Interviews don't ask for the basics. They ask the question with a twist: the duplicate rows, the NULL that changes the answer, the join that quietly doubles the revenue. Those are the mistakes I later saw cost real money at work.
So I built the place I wished I'd had: interview-level questions you answer yourself, on data that looks like a real company's, with feedback that tells you why you're wrong.
Interview-level, not just syntax
Every lesson climbs from Warm-up to Build to Interview questions, the kind that decide a SQL round.
Your mistake, explained
Each question knows the most common wrong answer. Write it and you're told exactly why it's wrong.
Data that behaves like work
Banking, ride-hailing, streaming, SaaS, pharma and real retail data, with the duplicates and gaps real tables have.
Analytics consultant with 5+ years across US pharma commercial analytics, healthcare and e-commerce. SQL, Power BI and Excel are my daily tools, and checking numbers before they reach a client is most of my job.
ZS Associates · Amgen US account · Decision Analytics Associate Consultant
Built the independent check every incentive and contest report went through before release, recalculating results from IQVIA sales data pulled with SQL in Databricks.
Vibes Healthcare · Assistant Manager, Analytics & Planning
The only analytics person across a 30+ centre network: built reporting from scratch, and an outlier check nobody asked for exposed an incentive loophole that led to a new slab-based policy.
1DigitalStack · Business Analyst
E-commerce analytics across marketplaces like Amazon and Flipkart; learned Python to build review crawlers when demand outgrew the tech team.
Learning in public
MBA in Business Analytics, and currently on Airtribe's AI-First Product Management Launchpad. ChaturIQ is where I put both into practice.
The pharma sales, targets and incentive tables you practise on are modelled on the kind of data I validated every week. The traps in the questions are the ones I've seen in real reports.
This is version 1. Help shape version 2.
Every lesson and feature is built around learner feedback. Tell me what helped, what didn't and what you'd like next.