Power BI - Mastering DAX for Power BI

Understand tables, including fact and dimension, and how their relationships shape DAX models. Master DAX by studying functions, their purpose, behavior, and the pivotal evaluation context for filter manipulation.

Understand how dimension tables filter the fact table in a Power BI model, and explore cardinality (one-to-one, one-to-many, many-to-one, many-to-many) and cross-filter direction.

Explore bidirectional cross filtering between product, orders, and customer tables to count customer segments by product, enabling orders to filter back to customers.

Master DAX functions in Power BI by using table and scalar expressions, understand function arguments, and classify functions by return type and purpose for efficient data models.

Use the if function to create a calculated column classifying sales quantity into small, large, and bulk (1–4, 5–10, 11–14). Build a nested if to test ranges and assign labels.

Learn how the switch function replaces nested ifs by evaluating a true expression with paired conditions and results, using orders quantity between five and ten, and a default else.

Create a calculated column in the orders table to pull the city from the related location table using related, which returns a single value from the one side of relationship.

Explore how all and allexcept control tables in DAX to return all rows or a unique list of values, and contrast table functions with scalar functions.

understand how all, values, and distinct return a unique list from a column, with values and distinct offering the same results and only minor variations when used in measures.

Learn how the DAX engine uses row context and filter context to evaluate expressions, and how measures, calculated columns, and iterator functions operate within these contexts in Power BI.

Create a revenue measure in DAX and explore how filter context shapes its results in visuals, breaking revenue down by region, category, and customer segment.

Show how DAX uses filter context to compute revenue by region in Power BI, selecting only revenue and region, summing per region simultaneously and returning results to the report.

Learn how aggregators and iterators in DAX work, from sum and count to sumx and averagex, and why iterators offer row by row calculations for powerful measures.

Learn how sum works on a column and why sumx enables row context calculations for columns and measures, using orders table to compute revenue and costs from sales minus profit.

Learn to aggregate on a filtered table in Power BI by building a south revenue measure with sumx, filter, and related to sum orders sales for the south region.

Discover how the DAX engine computes filtered aggregates by simulating a data model, summing order sales where region is south, and returning blanks when no matching region exists.

Explore how DAX computes filtered aggregates by combining segment and region filters within the filters context, and distinguish external versus internal filters, using slicers, tables, and the filter function.

Use the all function on orders to expand filters in DAX, blow up the whole table and ignore current regional selections, then compare south revenue to other regions.

Master the DAX calculate function, the only tool that can completely alter the filter context, by exploring row context, filter context, and context transition with related data.

Learn how the calculate function triggers a context transition from row context to filter context. This enables breakdown of totals in calculated columns and affects measures in Power BI.

Learn how sum X triggers row context within a measure by scanning the orders table and summing orders sales across regions, contrasting with the starting filter context.

Learn how DAX handles context transition with SUMX across regions, showing row context evaluation and how CALCULATE shifts to filter context to compute revenue.

Explore how to use the calculate function to alter filter context in Power BI measures, creating a south revenue measure by filtering location to south and comparing regional revenues.

Learn how to use the DAX CALCULATE function to filter revenue by multiple columns, such as region and product category, and understand how to apply different filters across columns.

Use the or operator (double pipe) to filter the location region for south or west and sum the revenue in the calculate context, with the option to include east.

Learn to use the in operator in DAX to replace multiple or conditions, filtering by a list of regions such as south, west, and east for a cleaner revenue calculation.

Explore the four types of filtering - maintain, shrink, expand, and change filter context - and how the calculate function uses them to shape region revenue and totals.

Use ALL() to adjust filter context in CALCULATE with the FILTER function. Compare a syntax sugar approach to the explicit FILTER version for calculating south region revenue.

Explore how ALL() changes a DAX measure by replacing the region in the filter, revealing revenue across segments.

Explore how the dax engine applies filters across state and region columns in a Power BI measure, and why California returns blank when the region is south.

Learn how to use variables in dax to pre calculate values within a formula, using var and return, and the if function to halve revenue over 100k by city.

Learn to activate bidirectional filtering across customers, orders, and product data using DAX CALCULATE and CROSSFILTER to enable cross-table counts via measures, not permanent relationships.

Master time intelligence in DAX by using table date functions to filter dates for year-to-date, previous year, and previous month, and create a marked date table in Power BI.

Create a date table with calendar auto to generate contiguous dates from the first to the last year in your data, then mark it as the date table.

Create a year column in Power BI by applying the YEAR() function to dates from the calendar table, and use FORMAT(date, "yyyy") to produce a text year.

Create month and quarter columns in Power BI using FORMAT() and MONTH(), apply Q1–Q4 prefixes, sort by month number, and link the calendar table to the fact table for reporting.

Build a matrix with year and month to test time intelligence calculations in DAX, using syntax sugars and custom measures like previous month and revenue variance.

Learn to calculate previous month revenue in Power BI by manipulating filter context with the calculate function and the previous month function using a calendar date table.

Explore how to expand the previous month DAX function by using selected year and month, variables, and an all calendar filter to calculate the prior month revenue.

Expand the previous month in DAX by using VALUES and DATEADD to generate previous month dates, then apply a filter on the calendar and calculate revenue for accurate totals.

Apply DAX CALCULATE and the DATESYTD function to compute revenue YTD from January 1 to the selected date, using a calendar table.

Expand the dates ytd function by using dates between to define a date range from first day of selected year to last day in selection to compute revenue.

Learn how to calculate year to date revenue using the total ytd function, which avoids calculate and dates ytd while using a calendar date table.

Create a DAX measure revenue sply using same period last year to return the exact value for the same period in the previous year, based on the calendar date.

Create a custom same period last year using values and dateadd to map selected dates to the previous year. Filter the calendar table to these dates and calculate revenue.

Learn how to rank sales reps with the DAX rankx iterator, using sum of sales and calculate to convert row context to filter context for accurate ranking.

Create top N visuals in Power BI using the filters pane and the Top N DAX function to display the top five states by revenue.

Learn how the top N function in DAX selects the five states with the highest revenue, building a top five states table and applying it within a measure.

Learn to create a top five states measure using calculate and topN to show the highest revenue states in a bar chart.

Add a parameter table and slicer to dynamically drive a top N measure in Power BI, enabling seamless switching from top five to top ten selections.