Understanding Key DAX functions in POWER BI

Explore how context shapes DAX calculations in Power BI, including external context, filter propagation, and how visuals and selections influence total sales.

Explore how aggregation and iteration engines shape Power BI totals, with sum applying the initial filter context to reduce data before aggregation.

Understand row context and iterator functions in Power BI, compare aggregate sum with sumx, and see how measures calculate on the fly using order quantity and unit price.

Understand cumulative sales in Power BI by summing values from the start of the period to today, while managing filters with all, all selected, and filter expressions.

Explore cumulative totals and rolling totals with DAX in Power BI, using seven- and thirty-day windows and dates between for dynamic start-end calculation.

Explore how to link slicer selections to multiple measures in Power BI using a supporting table and the values function, enabling dynamic percentage changes in reports.

Explore how the DAX all function ignores context to compute percentage of total sales per customer in Power BI; create a measure using all(table) to fix the denominator.

Learn to apply the topn function in power bi to extract top or bottom values within a given context, using region and suburb breakdowns to show dynamic filtering.

Explore how the DAX ALLSELECTED function differs from ALL in Power BI, showing how ALLSELECTED respects filters while ALL ignores them, and how this affects cumulative calculations.

Demonstrate the LASTNONBLANK value function in DAX to compute the last non blank sales amount for each customer within the model context.

Learn how the Treatas function in Power BI creates a virtual relationship to filter tables without joins, using CALCULATE and VALUES to align budget data by city and year.

Explore how userelationship activates an inactive relationship in your data model to drive correct sales and ship-related totals. Contrast this with treatas, which handles calculations without creating a physical join.

Learn how to calculate the median in power bi with dax by using medianx on a summarized table of product names and total sales, and understand the middle value concept.

Learn how CALCULATETABLE returns a filtered table rather than a scalar. It enables table expressions for multi-column analysis, such as counting products sold in a city and the previous month.

Explore how to use the parallel period time intelligence function within calculate to compute last month and last quarter values, including panel period considerations for Power BI.

Explore how to use TopN in Power BI to compute the top five sales and average them, while using ALL to remove context and keep a constant benchmark across customers.

Understand how iterative functions multiply order quantity by unit price to compute total revenue and costs, and learn when measures outperform calculated columns for better performance and data granularity.

Explore the main difference between all and allselected in DAX: learn how all removes filters to return the overall maximum, while allselected respects slicer selections in Power BI.

Explore advanced rankx usage in Power BI by building dynamic rankings on total sales, removing filter context, and highlighting top customers through time filtering.

Use the group by function in Power BI to group by product name and city, and calculate total sales as revenue in a new table.

Learn how to handle multiple conditions in Power BI with DAX using the switch function, applying it in measures and calculated columns, and use conditional formatting for color by value.

Resize Power BI visuals dynamically by using a ranking selection and dax measures such as rankx and hasonevalue to display top N customers by total sales.

Create dynamic visuals and a responsive scorecard in Power BI by using DAX ranking with TOPN and rank-based filtering to display top customers and their total sales via a slicer.