DAY 1
| What is data analytics and business analytics |
| Business Analyst v/s Data Analyst |
| What is PowerBI |
| Why do we need Power BI |
| Tableau V/s Power BI |
| How a business problem is resolved [methodology]+ work of Power BI in it. |
| Power BI Components |
| • Power BI Desktop |
| • Power BI Services |
| • Power BI Mobile |
| Installation of Power BI |
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DAY 2
| Entire Power BI flow (Data collection → Power BI Desktop → Power BI Services) |
| • What are Servers |
| • How data is Stored |
| • ETL process |
| • OLAP/OLTP/Data Warehouses, Data Lakes, Data Marts etc. |
| • Data Cleaning |
| • Data Transformation. |
| • Data Visualization. |
| • Power Query |
| • DAX |
| • Measures Etc. |
| • Publishing of dashboard, Self Service BI, Refresh Reports, Sharing of reports. |
| Power BI user Interface. |
| Data types available, their Identification, and Changing Data Types. |
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DAY 3 AND DAY 4
| Editing working area |
| Creating and editing visuals. |
| Elements such as cards, slicers, KPI, gauge, etc. |
| Bookmarks, hyperlinks, and page navigation. |
| Format Painter. |
| Area chart [Lasso setting], Area bubble chart, Area filled chart. |
| Integration of AI to create charts. |
| Tables, matrix creations, and differences between them. |
| Conditional Formatting. |
|
DAY 5
| Tooltips. |
| Filters. |
| Drill up, Drill down, Drill Through. |
| Data Modelling (Data Relationships). |
| • Cardinality. |
| • Relationships. |
| • Cross Filter Direction. |
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DAY 6 AND DAY 7
| Data Modelling Continuation. |
| Filters v/s Slicers [performance]. |
| Introduction to DAX |
| • Basic Dax Queries. |
| • If, switch Statements |
| • DAX and logic building practice. |
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DAY 8 AND DAY 9
| Consolidating Data (Grouping, Bins) |
| Measures (Continuation of DAX) |
| • Questions and logic. |
| • Difference between measures and columns. |
| • Types of measures. |
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DAY 10
| Filter Context. |
| Queries and Logic building in Filter Context (DAX) |
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DAY 11
| Parameterized Charts Continuation. |
| Measure Parameterized Charts + DAX. |
| Tree Map. |
| Scatter Plot. |
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DAY 12
| Quick Measures. |
| Introduction to Power Query. |
| Problems and issues with data and continuation of Power Query |
| Data Transformation using Power Query Editor. |
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DAY 13 AND DAY 14
| Data transformation Continuation. |
| M-language. |
| Merge Queries. |
| Append Queries. |
| Connect of data from Servers (SQL servers) |
| Query Folding. |
| Python Integration. |
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DAY 15
| Pivot and Unpivot tables. |
| Granularity and Group by. |
| Row Level Security in Power BI. |
| Power BI Services Introduction. |
| DAX and measures using AI. |
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DAY 16
| Power BI Services. |
| • Publishing of Services. |
| • Assignment of roles. |
| • WorkSpaces. |
| • Self Service BI. |
| • Managed Access. |
| Power BI pricing. |
|
DAY 17
| Power BI roles. |
| Self-Service Capabilities. |
| Reports (In Power BI Services). |
| Dashboard (In Power BI Services). |
| Reports V/S Dashboards. |
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DAY 18
| Power BI Architecture. |
| Gateways. |
| Refresh Time. |
| Embedded links. |
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DAY 19
| Power BI Interview Questions. |
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DAY 20
| Gen AI Enabled Power BI |
| • AI charts. |
| • Analysis Using AI to Drive Insights from Created Charts. |
| • Formatting background using AI. |
| • Formatting charts using AI. |
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DAY 21, 22, 23, 24, 25
| Power BI projects + Microsoft Power BI PL 300 certification Guidance. |
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