Advanced DAX in Power BI is a course that goes deep into row context, filter context and context transition, then moves on to table functions, window functions, calculation groups, DAX user-defined functions and performance tuning with VertiPaq. It suits data analysts, Power BI report developers and BI teams who already write basic DAX and want measures that are correct and fast.
Many teams can already write DAX, yet they still meet measures that return wrong figures when a slicer changes, totals that do not match the sum of their rows, formulas so long that nobody dares to edit them, and reports that slow down as the data grows. The cause is rarely the choice of function. It is usually an incomplete understanding of evaluation context, context transition and how the Power BI engine actually processes a formula.
This course takes learners systematically through the mechanics of DAX: variables and iterators, row context and filter context, CALCULATE and context transition, table functions and advanced relationships, and newer tools such as window functions, calculation groups, DAX user-defined functions and DAX query view. It closes with performance analysis through the formula engine, the storage engine and VertiPaq. Every topic is practised on business questions using the same model throughout the course.
Course Details
This course is the 2026 edition of Advanced DAX in Power BI Desktop, rewritten for the current Power BI Desktop. It runs for 2 days, 6 hours per day (12 hours in total, 09:00-16:00), as lectures with labs on a single sales model throughout. Intermediate to Advanced level. Day one goes deep into evaluation context, CALCULATE, context transition, table functions and advanced relationships. Day two practises advanced time intelligence, window functions, calculation groups, DAX user-defined functions and performance tuning with VertiPaq. The course builds on Analyzing Data with Power BI Desktop and Basic DAX in Power BI Desktop, so it does not repeat data preparation or dashboard design. Learners take home the Power BI files and DAX exercises for every lab.
Section 1: Lab: Variables, Iterators and Testing with DAX Query View
Section 2: Lab: Row Context, Filter Context and Relationships
Section 3: Lab: CALCULATE in Depth and Context Transition
Section 4: Lab: Table Functions and Virtual Tables in Measures
Section 5: Lab: Advanced Relationships
Section 6: Lab: Advanced Time Intelligence
Section 7: Lab: Window Functions
Section 8: Lab: Calculation Groups
Section 9: Lab: DAX User-Defined Functions
Section 10: Workshop: Performance Tuning and a Measure Library
No public rounds are open right now. Join the waiting list and we will contact you first when the next round opens, or ask us on LINE. Or call 02-570-8449 or 088-807-9770
Row context means the formula knows which row it is evaluating. It exists in calculated columns and in iterators such as SUMX, letting you refer to column values on that row. Filter context is the set of filters affecting a calculation, coming from slicers, the rows and columns of a visual, or arguments to CALCULATE. Importantly, row context does not filter data or follow relationships on its own until context transition occurs.
Context transition is when CALCULATE turns an existing row context into a filter context, using the values of every column in the current row as filters. It happens when CALCULATE is called inside a calculated column or an iterator, and whenever a measure is referenced inside an iterator, because measures are automatically wrapped in CALCULATE. Misunderstanding it leads to wrong figures or slow formulas.
DAX user-defined functions let you write parameterised logic once in the model and call it anywhere DAX is supported, for example a margin calculation or a currency conversion. Calculation groups instead modify the calculation of existing measures through SELECTEDMEASURE, for example turning every measure into YTD or prior year from a single slicer. Both reduce duplicated formulas, and real models often use them together.
VertiPaq stores data by column rather than by row and compresses each column using value encoding for numbers, hash encoding, which builds a dictionary of unique values, and run-length encoding, which stores repeated adjacent values as a single run. Columns with many unique values, such as timestamps to the second or transaction IDs, use more memory and slow calculations, so removing unused columns or splitting date from time keeps the model smaller. You can check this with VertiPaq Analyzer.
It suits data analysts, Power BI report developers, BI teams and anyone who already uses basic DAX and wants a deeper understanding of how calculations work. You should be able to build reports and data models in Power BI Desktop and write basic measures such as SUM, DIVIDE and simple CALCULATE. The course does not repeat data preparation or dashboard design.
Yes. It can be run in-house for your team, with examples adapted to your own work, such as reviewing measures in your own model that return wrong results or run slowly. You can request a quotation from this page, or contact us on LINE @itgenius or by phone on 02-570-8449.
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