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Data Analytics vs Power BI

Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.

Side by side

The differences at a glance

FeatureData AnalyticsPower BI
LevelBeginnerBeginner
Duration3–4 Months1–2 Months
Who can joinBasic computer use; no programming or technical background requiredComfort with Excel; no coding background required
Key toolsMicrosoft Excel, Google Sheets, SQL, MySQL, PostgreSQL, PythonPower BI Desktop, Power BI Service, Power Query Editor, DAX, Microsoft Excel, SQL basics
What you’ll learnModule 1: Data Analytics Foundations · Module 2: Advanced Excel for Analysis · Module 3: SQL for Data Analysis · Module 4: Statistics for AnalystsModule 1: Business Intelligence and Power BI Basics · Module 2: Connecting to Data · Module 3: Data Cleaning with Power Query · Module 4: Data Modelling
Portfolio projects——
Career rolesData Analyst, Business Analyst, MIS ExecutivePower BI Developer, Data Analyst, Business Analyst
Which to pick

Choose the one that fits your goal

Pick Data Analytics if…

Learn to collect, clean, analyse and present data using the tools employers actually ask for, such as Excel, SQL, Power BI, Tableau and Python, through real datasets and hands-on projects.

  • Clean and prepare raw data from spreadsheets and databases
  • Write SQL queries to answer business questions
  • Build dashboards in Power BI and Tableau
Explore Data Analytics

Pick Power BI if…

Turn raw business data into clear dashboards and reports with Microsoft Power BI: data connection and cleaning, modelling, DAX calculations and interactive dashboards.

  • Connect to multiple data sources and clean messy data without manual rework
  • Design a star-schema data model
  • Write DAX measures for KPIs, comparisons and time-based analysis
Explore Power BI

Still deciding between the two?

A counsellor can map either course to your degree, schedule and career goal — one call is usually enough.

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