Faster work in Query Editor - You will clean up and transform data more efficiently in Query Editor, so you can prepare analysis-ready datasets on your own and reduce errors before the data even reaches the report.
Combining multiple data sources - You will learn how to import data from Excel files, CSV files, and databases, then bring it into one consistent model, making it easier to build reports from different information sources.
Confident use of analytical functions - You will practice aggregation, lookup, counting, and time functions, so you can calculate key metrics faster, compare results, and answer specific business questions with your analyses.
Better report model design - You will understand how to build a report model with quick measures and key properties, helping you create reports that are clearer, more consistent, and easier to expand later on.
Smarter tables and filters - You will learn when to use parameter tables and calculated tables, and how to apply filters effectively, so you can control report logic and tailor analyses to different audiences.
Clear data hierarchies - You will learn how to create and adjust hierarchies in Power BI, making your data presentation more structured and helping users move smoothly from summary views to detailed insights.
Practical DAX conditions - You will master IF and SWITCH logic as well as filter behavior in DAX, allowing you to build more flexible calculations and align report results with specific business rules.
Custom measures and calculated columns - You will learn how to create calculated columns and measures in DAX, so you can build custom indicators that go beyond what standard Power BI settings can deliver on their own.
Power BI basics are revisited to align terminology, workflow, and the core elements used throughout the advanced topics. The section refreshes Query Editor, essential platform functions, and the main data analysis concepts needed to work consistently with reports and models.
Working with data from .xlsx, .csv, databases, and existing models requires more than simply connecting sources. The emphasis here is on selecting and loading data correctly, checking imported content, and preparing it for later modeling and reporting in Power BI.
Aggregate, lookup, counting, and time intelligence functions form the core toolkit for many DAX calculations. Rather than treating them separately, the section shows how these groups are used together to build indicators, retrieve values, count elements, and analyze changes over time.
Within the reporting model, field properties and quick measures affect both calculation behavior and the way results are presented. This part focuses on organizing model elements, configuring key properties, and using those settings to support consistent reporting logic.
Using tables as control elements extends the model beyond raw source data. Attention is given to parameter tables, calculated tables, and filter-driven helper structures that influence analytical results and allow reports to respond more flexibly to selected options.
Hierarchies support analysis at multiple levels of detail and make navigation through report data more structured. The section covers automatic hierarchy creation, designing custom hierarchies, and changing their layout so drill paths match the way users interpret business information in Power BI.
Business rules often require different results for different conditions, which is where IF and SWITCH become essential. The focus is on building simple and nested decision logic, combining criteria, and applying conditional expressions in columns, measures, and analytical outputs.
DAX formulas depend on the structure of the data model, data types, and the way filters affect evaluation. Participants work with syntax, expression building, and calculation logic so they can create and modify formulas that behave correctly in analytical scenarios.
Calculated columns and measures are compared through their role in the model, evaluation logic, and use in reports. The section explains row context versus filter context, shows where each approach fits better, and covers formatting and organizing calculations for consistent use in visualizations.
The closing part consolidates the key topics covered across advanced Power BI work, from data modeling and DAX to analytical report design. It also reviews common solution patterns, typical mistakes, and practical rules for maintaining clear calculations and extending reports after training.
Power BI basics - You should know the basic Power BI interface and be able to navigate report, data, and model views, so you can work comfortably with the more advanced features in the course.
Working with tabular data - You should be comfortable working with tables, understand columns, rows, and data types, and read simple summaries, because the training builds directly on those skills.
Basic data analysis concepts - You should understand core analytical concepts such as filtering, grouping, summing, and counting, so you can build measures more easily and interpret report results correctly.
Excel or similar tool experience - You should have experience working with Excel or a similar data analysis tool, because the training assumes you already understand tables, formulas, and common data sources.
