Hands-On Data Analytics with AI

From the FabAcademic Unfiltered talk series — Session 5.8, 8 March 2026. (Watch / source)

Every business and every life is sitting on data — sales records, stock lists, attendance, expenses — and most of it is never used. This talk is about turning those numbers into decisions, even if you've never written a line of code.

The problem

"Data analyst" sounds like a job for someone with a degree and a fancy laptop. So ordinary people leave their data to rot in notebooks and on till slips. A salon owner doesn't know which service makes the most money. A spaza shop restocks by gut feel and ties up cash in stock that doesn't sell. An NGO can't show funders its impact because nobody turned the records into a chart. Meanwhile, employers are desperate for people who can read and explain data — but the training looks intimidating and expensive. The result: businesses guess instead of knowing, and capable people never enter a well-paid field because the door looks locked.

How AI solves it — real-world application

AI has made data analytics something you can do by talking. Put your sales data into a spreadsheet and use ChatGPT's data analysis feature (or Google Sheets with Gemini) and simply ask: "Which products made the most profit last month? Show me a chart and explain it simply." The AI cleans messy data, spots trends, builds graphs and writes the plain-language summary — no formulas memorised. You can ask "why did sales drop in April?" or "which customers should I focus on?" For bigger work, AI writes the spreadsheet formulas or even basic Python for you, and explains each step so you learn while you work. Free tools like Google Sheets plus an AI assistant are enough to start today.

Skills you'll learn

• Organising messy records into a clean spreadsheet AI can read
• Asking AI the right business questions of your data
• Cleaning data: fixing duplicates, errors and missing entries
• Generating charts and dashboards that non-technical people understand
• Letting AI write spreadsheet formulas and simple code for you
• Telling a clear story with numbers — the heart of real analytics
• Sense-checking AI's output so you don't act on a wrong conclusion

Where to use them

• Spaza shops, salons and small retailers optimising stock and pricing
• Stokvels and savings groups tracking contributions and growth
• NGOs and community projects reporting impact to funders
• Students and graduates building a data skill for the job market
• Marketers and side-hustlers measuring what actually works
• Anyone managing a budget, inventory or sales record

What it can earn you (potential value)

These ranges are indicative, not guaranteed — they depend on your clients and consistency. Data analytics is one of the best-paid skills you can self-teach. As a freelance service for small businesses — monthly sales reports, simple dashboards, stock analysis — you can realistically charge R500–R2 000 per report or per client per month. Land 3 small business clients on a R750 monthly retainer and that's roughly R2 250 a month of recurring income from your laptop. The same skill on a CV opens junior data analyst roles paying far more. And for your own business, knowing your numbers often saves or earns more than any side gig — better stock decisions alone can lift a small shop's profit meaningfully.

Watch / listen

• FabAcademic Unfiltered — Session 5.8