SV Infotech · Dilsukhnagar, Hyderabad
Power BI & Data Analytics
Personal study sheet
This is an independent study aid, not an official syllabus, admission assessment or promise of class assignments. Confirm the current teaching scope and practical access with the office.
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Set your starting point
Useful foundations: Comfort with spreadsheets helps; SQL and basic business metrics are useful for deeper analysis.
Explore the learning roadmap
01Define business measures
Translate a business question into a metric with a clear unit, period and calculation rule. Agree what a total means before choosing charts or building a dashboard.
02Clean data with Power Query
Inspect source tables, data types, missing values and inconsistent labels. Keep transformation steps understandable and check how a later source update affects the result.
03Create a usable data model
Identify facts, dimensions, relationships and the level of detail in each table. Explain how an incorrect join or relationship can multiply a total and produce a convincing but wrong report.
04Develop calculations
Distinguish a calculated column from a measure and explore how filter context changes a result. Reconcile important calculations against a small, independently checked example.
05Design accessible reports
Choose visuals that answer the question, use readable labels and reduce unnecessary decoration. Test filtering, drill-through and the experience of a reader who has not built the report.
06Plan refresh and sharing
Discuss data-source credentials, refresh behaviour and appropriate access. Separate what is possible in a local file from the licensing and administration needed for publishing and collaboration.
Power BI & Analytics: a worked study example
Illustrative scenario for discussion and self-study.
Two sample orders total 300: order A is 100 and order B is 200. Order A has two line items. Joining order totals to every line and summing can produce 400 instead of 300. Use this case to explain data grain, relationships and why a visually convincing report still needs reconciliation.
What to check in your work
- Reconcile a headline measure with the original order records.
- Explain what a date or product filter changes in the result.
How this pathway compares
Power BI presents and explores modelled data. Advanced Excel is useful for spreadsheet analysis; Tableau offers another visual-analysis workflow. Compare the reporting task and data sources before choosing a tool.
Check your reasoning
Why should a dashboard define its measures before choosing visuals?
Suggested explanation
A label such as revenue can mean invoiced, paid or net revenue over different periods. Specify the unit, date rule, exclusions and aggregation first. Then reconcile a small sample independently and choose a chart that communicates that agreed definition.
Plan the conversation
Ask about the actual syllabus, practical environment and feedback arrangements. Confirm fees, duration, trainer and current batch schedule directly; this sheet supplies none of those details.
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