Data Analytics with Excel, SQL and Power BI
Why colleges run this
The most employable single skill a degree student can leave with, and it works just as well for Commerce and Management cohorts.
Course outcomes
CO1
Profile a raw dataset and identify structural defects — duplicates, type errors, missing values
K4CO2
Transform an unnormalised table into a queryable relational structure
K3CO3
Construct SQL queries using joins, aggregates and window functions
K3CO4
Design a Power BI data model with defined relationships and DAX measures
K5CO5
Evaluate a dashboard against its intended decision and justify each visual choice
K5Modules tap a module for its theory & lab
Hours shown are the recommended 3-day format — module time scales to the duration you pick.
01Spreadsheet engineering4 h
Theory
Tables, absolute references, named ranges, lookup functions, pivot tables
Lab
Rebuild a messy sheet into an analysis-ready table
Output
Clean workbook with pivots
02Data cleaning discipline4 h
Theory
Duplicates, type errors, missing values, outliers, documentation of decisions
Lab
Profile and clean a genuinely dirty dataset
Output
Cleaning log + clean dataset
03SQL foundations4 h
Theory
SELECT, WHERE, ORDER BY, aggregate functions, GROUP BY
Lab
Query drills against a seeded database
Output
Twenty working queries
04SQL that answers questions4 h
Theory
Joins, subqueries, window functions for running totals and ranks
Lab
Translate five business questions into SQL
Output
Question-to-query workbook
05Power BI modelling4 h
Theory
Data model, relationships, DAX measures, calculated columns
Lab
Model the cleaned dataset with defined relationships
Output
Power BI data model
06Dashboards that decide4 h
Theory
Visual selection, interactivity, publishing; capstone build
Lab
Capstone: a dashboard answering one stated decision
Output
Published dashboard + walkthrough
Every participant receives
Certificate of completion Course material LMS access Interview question bank Mock interview & viva practice Optional nasscom NSQF assessment