Power BI DAX transition from SQL

Explore Power BI DAX with logical conditions using filter and selectcolumns to select product name, color, and price, filtering for silver and price above 700, and understand end function limits.

Use Power BI DAX to count rows with summarize for grouping, counting subcategories per product category, and joining tables to display total subcategories with english names.

Show how to use addcolumns to aggregate total subcategories by product category without summarize, and connect subcategories to categories with related table to reveal underlying products.

Learn to combine addcolumns with selectcolumns in Power BI DAX to produce a table that includes English product category name and a total subcategory count, with proper aliases.

learn to use AddColumns with summarize in Power BI DAX to derive distinct product category names and a related count of subcategories, enabling efficient group by operations.

Demonstrates using calculate table to filter a product table by color and class, comparing it with the filter function and highlighting performance benefits.

Learn how calculate table enhances performance by applying the filter context to distinct colors before evaluation, while the filter function checks each row, using product color and red as examples.

Learn when to use calculate table versus filter in Power BI DAX, including applying filters to measures or columns and noting performance advantages.

Join four tables in Power BI DAX using natural inner join and inner join semantics, linking product category, subcategory, and products with sales; refine results with select columns and distinct.

Explore natural inner join in Power BI DAX and why a physical relationship is essential; refresh metadata after reconnecting keys to avoid no common join column errors.

Examine alternatives to natural inner join in dax by using summarize and distinct to compute total sales by category and product color, without relying on addcolumns.

Explore how to use the having clause in DAX and SQL to filter grouped results by product. Compute total transactions per product with summarize and apply a 1000 threshold.

Explore how to implement a left outer join in DAX to combine calendar and product data with sales, using relationships and the EVALUATE function to mirror SQL results.

Learn how cross join in DAX and SQL creates a cartesian product and reproduce it with DAX and SQL queries across product category and subcategory.

Learn how to use summarizecolumns in DAX to group by product subcategory name and product color, aggregating total transactions, and compare it with summarize in SQL.

Create a Power BI DAX measure named subcategory count using summarizecolumns to list subcategories where product color is blue.

Learn how the IN operator in DAX mirrors SQL to filter products by color, using FILTER, CALCULATE, and VALUES to return a single-column table of distinct product names.

Explore substring search in SQL using the like operator and replicate it in DAX with a calculated flag for the customers' name to return matches where the name contains characters.

Learn to extract the top 10 products by total sales using sql and the dax topn function, including grouping, summing sales, and ordering results in power bi.

Explore how to perform left and right string searches in Power BI DAX and SQL, using simple functions to match prefixes and suffixes in data like customer names.

Learn to generate top N products by category in Power BI using DAX TopN, translating a SQL approach with summarize, values, and calculate.