Complete DAX Bootcamp for Power BI from Beginner to Advanced

Install Power BI desktop and download the course datasets. Import, clean, and transform the data in Power Query, then load it into Power BI and build a standalone date table.

Create a standalone date table in Power Query to support yearly, quarterly, and weekly visuals by adding year, month, quarter, and week columns and linking to sales and customer data.

Explore how to distinguish dimension and fact tables by their primary keys, records, and data changes, using customer and product examples and a banking transaction scenario to illustrate relationships.

Explore building a Power BI data model by creating relationships, distinguishing dimension and fact tables, marking a date table, and configuring filter flow and cardinality for a snowflake schema.

Explore what DAX is, how the DAX engine works, and distinguish measure, calculated column, and calculated table, including implicit versus explicit measure.

Discover DAX, a data analysis expression formula language in Power BI, to calculate sales and profit, top customers, rolling averages, and to create measures, calculated columns, and calculated tables.

Learn to create a measure that sums product cost in Power BI, and compare calculated columns with measures, including when to use each in visuals like cards, tables, and slicers.

Explore implicit and explicit measures in Power BI by showing how a product cost auto-sums, then contrast DAX-based explicit measures with automatically generated ones.

Explore aggregation functions like sum, min, max, average, and count, and how they yield scalar values in a Power BI data model with fact and calendar tables.

Apply Dax functions to calculate total returns quantity, minimum product price, and maximum product price using the returns and product tables.

Create measures for total return quantity, min product price, and max product price using the sum, min, and max functions. Display each metric on a card with consistent formatting.

Create a DAX measure to compute average values across product price, order quantity, and return quantity using the average function; demonstrate aggregation on sales and returns tables.

Count function tallies non-blank rows in a column and ignores duplicates. Create a measure to count customers in the customer table, showing 18,448 total customers.

Learn how the distinct count function counts unique values in a column, and build a total customers in sales measure to show buyers by removing duplicates.

Learn how count rows counts the number of rows in a specified table using the table name, with examples using the territories table and creating a measure total territories.

Apply count and distinct count to build measures for total products, products in sales, and returned products. Use dimension and returns tables to reveal 293 total, 130 sold, 124 returned.

The calculate function evaluates an expression in a modified filter context, where expression can be a measure or a sum, overriding category filters to compute total product cost by category.

Explore row context and context transition in dax by creating calculated columns and measures that switch from row to filter context with calculate, showing how total product cost propagates.

Master DAX calculations by building a table of category name and total product cost. Then create measures for accessories and components costs, and a final difference measure to compare them.

Apply calculate to compute total product cost by category, create measures for accessories and components, and compare them with a diff measure, then format a matrix visualization.

Learn to create and organize a standalone measure table, move all measures into a key measures table, and use folders like 01. basics to keep Power BI DAX measures tidy.

Learn how to format DAX measures for readability using indentation, spacing, and proper line breaks, with variables for component and accessory costs.

Apply sumx in dax to calculate revenue by evaluating each row, multiplying sold price by quantity, and summing the results with related to bring product prices in Power BI.

Create a total cost measure by multiplying order quantity by product cost using a related function. Sum this value and pull the total cost into the visualization.

Learn how to use the MINX function to compute the minimum revenue across rows by evaluating price times quantity, with or without filter context, using measures versus calculated columns.

Create two measures: calculate total minimum cost by referencing the product cost and quantity, then derive minimum revenue by referencing the total cost measure.

Apply the maxx function in dax to evaluate an expression across rows and within filter context, using price multiplied with quantity to identify maximum revenue.

Use the averagex function to compute average revenue by iterating over each row, evaluating price multiplied by quantity, and applying filter contexts by category.

Apply the DAX context function to count revenues by iterating rows in the fact sales table, calculating revenue as price times quantity with the related function to get product price.

Explore solutions with iterators by building measures for total, minimum, maximum, and average return price across product categories using related, calculate, and returns data in Power BI.

Discover how DAX filter functions—filter, all, all except, and all selected—return tables and enable scalar calculations, contrasting with sum, min, max, and sumx/minx/maxx in Power BI.

Learn how the dax filter function acts as an iterator that returns a table and enables precise filtering with calculate for regions, categories, and amounts.

Create three continent-based total revenue measures by subcategory using calculate and filter, compare with actual revenue, then build max and min revenue measures for North America subcategories.

Use the all except function to remove all filters on a table except the specified columns, and apply it as a calculate modifier.

Master DAX concepts all, allexcept, and allselected in a two-scenario assignment that replicates total revenue across countries and customers and counts products by country and customer.

Learn to build DAX measures that manage filter context with ALL, ALLEXCEPT, and ALLSELECTED, calculating revenue and country-specific product counts across a Power BI model.

Learn to build DAX measures in Power BI to calculate total return price and total return quantity across United States, Canada, and Australia using dim territories and fact returns table.

Explore information functions in DAX and how a cell or row argument yields true or false for conditions like is blank or in scope; selected value is a filter function.

Learn the selected value function in DAX, which returns the value when a filter yields a single value and an alternate result otherwise, with cases in customers, regions, and months.

Understand how hasonevalue returns true when a column's context is filtered to a distinct value, compare it with selectedvalue, and apply to continent, country, and region hierarchies in Power BI.

Demonstrate how to use DAX ISEVEN and ISODD to determine if numbers are even or odd in Power BI, with examples on revenue and total return products, including blank values.

Develop DAX information functions to create measures for email selection with selected value, check scope with assign scope, and detect 13 in email text using content string and selector value.

Learn the DAX if function with logical tests, true and false results, and nested if logic to categorize total revenue into low, medium, and high with blank handling.

Complete a DAX assignment: build year-month hierarchies in a matrix, classify return products as low/medium/high, map months to quarters, and implement a revenue all selected measure for category and subcategory.

Create DAX measures to map month numbers to names, display year and month hierarchies in a matrix, and derive quarters with switch and if.