Numbers you already understand. Now learn to make them talk. A three-month, 150-hour classroom programme in Excel, Power Query, SQL and Power BI, built for commerce graduates who want data on their CV without starting from code.
Most analytics courses in Kochi start with Python in week two and lose half the room. DABI runs the tools in the order a commerce brain already thinks: Excel → Power Query → SQL → data model → a little Python at the end. Nothing is skipped; the sequence is just the one that does not break B.Com students.
The centre of the course is Module 4 — financial and audit analytics: ratio and variance dashboards, cash-flow and receivables ageing, ledger and GST reconciliation, sampling versus full-population testing, and anomaly and duplicate detection, worked on anonymised real client files and taught by staff from the auditing practice behind the academy.
That module is the reason to do this course here. A general analytics institute can teach you Power BI. It cannot teach you to find a duplicate in a real ledger, because it has never seen one.
An AI layer runs through the whole course, not at the end of it. Copilot in Excel and Power BI, prompt patterns for analysis, where the machine fabricates, and a verification protocol for every number that leaves your hands. One assessed exercise is simply: here is an AI-produced dashboard, find the lie.
Three months, 150 hours, one capstone you defend in front of a panel. This is what you walk out able to do.
Power Query as the way out of manual work — take a broken five-sheet workbook and turn it into something a model can actually use.
SELECT through joins, aggregation and window functions. Half the assessment is reading and correcting AI-written SQL, because that is the actual job now.
Star schema, relationships, DAX measures versus columns, report design and publishing — not just charts that look busy.
Reconciliation, ageing, variance, exception reporting and anomaly detection on live-derived client data. The module that does not get cut.
Use Copilot to draft, then verify every figure. Catch the fabrication before it reaches a stakeholder.
Stakeholder storytelling, one-slide summaries, and a ten-minute capstone defence under challenge.
Thirteen weeks, roughly 11 hours a week — Tuesday and Thursday evenings plus a six-hour Saturday. The final week is capstone and defence.
| Module | Hours | What is covered |
|---|---|---|
| 0 · Business questions before data | 8 | What a stakeholder actually asks for, turning a vague ask into a measurable question, and data literacy. No tools. |
| 1 · Excel → Power Query | 15 | Lookup and index, pivots, then Power Query as the bridge out of manual work. Assumes working Excel on entry. |
| 2 · SQL | 24 | SELECT, joins, aggregation and window functions. Half the assessment is reading and correcting AI-written SQL. |
| 3 · Data modelling & Power BI | 32 | Star schema, relationships, DAX (measures versus columns), report design and publishing. |
| 4 · Financial & audit analytics | 30 | Ratio and variance dashboards, cash-flow and receivables ageing, ledger and GST reconciliation, sampling versus full-population testing, anomaly and duplicate detection — on anonymised real client files. |
| 5 · The AI layer | 14 | Copilot in Excel and Power BI, prompt patterns for analysis, where it fabricates, and a verification protocol. |
| 6 · Python for analysts (light) | 10 | Read, run and modify a pandas script. Awareness of scale and repeatability — explicitly not a machine learning module. |
| 7 · Communication + capstone | 17 | Stakeholder storytelling, one-slide summaries, defending a number under challenge. Capstone plus viva. |
Entry requirement: working Excel. There is a short placement check at enrolment, and a free pre-course Excel clinic for anyone who does not clear it — because module 1 assumes you arrive able to use a spreadsheet.
Who it is not for: Engineering graduates who want machine learning. DABI deliberately keeps Python light. Go to DSML — though most people are better off doing DABI first, since DSML assumes everything DABI teaches.
DABI is a three-month, 150-hour Data Analytics and Business Intelligence course at BeeTees Academy of Commerce in Edappally, Kochi. It covers Excel and Power Query, SQL, data modelling and Power BI, an AI layer, light Python, and a 30-hour financial and audit analytics module taught on anonymised real client files by staff from the auditing practice behind the academy.
No. DABI is built for commerce graduates. Tools run in the order a commerce background already thinks — Excel, then Power Query, then SQL, then the data model, with only ten hours of light Python at the end. You do need working Excel, and there is a short placement check at enrolment plus a free pre-course Excel clinic if you do not clear it.
Look for two things: whether the tools are taught in an order that suits a commerce background, and whether the financial data you practise on is real. DABI at BeeTees does both — the 30-hour financial and audit analytics module uses anonymised client files from a working auditing firm, which a general IT training institute cannot offer.
Three months, about 13 weeks and 150 hours, running roughly 11 hours a week — Tuesday and Thursday evenings of 2.5 hours each plus a six-hour Saturday session. The schedule is built so working students can attend, with Saturday as the anchor day.
Fee and batch dates are being finalised and go to our enquiry list before they are advertised. Call +91 80757 34949 or use the enquiry form on this page and a counsellor will call you within 24 hours.
The course teaches the Power BI skills the PL-300 Microsoft Power BI Data Analyst exam tests, and PL-300 preparation is available as an optional add-on. It is not bundled into the course fee, because most students do not sit the exam and bundling it would inflate the price for everyone.
Fees and batch dates go to our enquiry list first. Leave your details and an academic counsellor will call you within 24 hours.
Four AI-era programmes launched together. They are designed to stack.