• DAX Functions Reference
  This DAX functions reference guide is for anyone who wants a fairly complete guide to the main DAX functions you are going to need to create business intelligence reports for businesses with Power BI. Converting and Checking Data Types with DAX Functions When writing DAX functions, such as with SQL, you will find that you… Read more: DAX Functions Reference
• Setting up Power BI and Git Integration with Azure DevOps
  Git version control keeps track of every change to DAX measures, model relationships, table metadata, M code, and report visuals (if any). It allows you to go back to older versions and compare versions, and see exactly what has been changed. If 2 people work on the same PBIX file, changes can be overwritten, making… Read more: Setting up Power BI and Git Integration with Azure DevOps
• DAX Optimization – Analyzing the Query plan and storage retrieveal
  Learning how to optimize DAX measures is an essential skill for improving slow-running reports. We can use DAX Studio to help us understand how our DAX measure is translated into code that can retrieve the data for us, and it gets pretty complex. A summary of the steps for executing a Power BI report measure… Read more: DAX Optimization – Analyzing the Query plan and storage retrieveal
• Multiple parameter selections using Invoke Custom Function.
  Making use of a parameter and ‘invoke custom function’ allows you to control the filtering of a Power BI report data source without editing the Power BI file. This method can offer filtering multiple selections at the source and offers end users the option of controlling this filtering from a spreadsheet without the need to… Read more: Multiple parameter selections using Invoke Custom Function.
• How to create Multiple DAX Measures
  There are different ways we can build multiple DAX measures at once in Power BI. This can save time and can be useful if you have a good understanding of what you require. Creating measures in Power BI Desktop individually is a slow process, but there are alternatives that are good to learn. Creating multiple… Read more: How to create Multiple DAX Measures
• Analyzing DAX Server Timings in DAX Studio
  Improving DAX measure speed. We can take a measure like the one customer order measure, add it to a card visual, and use the performance analyser to give us the DAX query, which we can paste into the performance analyser. However, we may see different results if we use it in a matrix, so we… Read more: Analyzing DAX Server Timings in DAX Studio
• Testing DISTINCTCOUNT() Speed in DAX
  The DISTINCTCOUNT() function can slow down reports, but if it’s required, then what are the alternatives?Here we test DISTINCTCOUNT DAX speed against other DAX Options. Test 1: Adventure Works The measures all give the same results, but which one is faster? We can test these measures by opening the above matrix for all years to… Read more: Testing DISTINCTCOUNT() Speed in DAX
• Measuring DAX Performance of DAX Table Functions
  We can test the DAX performance in measures using the performance analyzer in Power BI to see which table function used in a formula performed best. Below are the results of 10 tests per measure. SUMMARIZECOLUMNS() and SELECTCOLUMNS() are neck and neck, with the old SUMMARIZE() function finishing last. We will check out the results… Read more: Measuring DAX Performance of DAX Table Functions
• Power BI Model Performance Optimization
  1. Model Optimization a) Remove unnecessary columns and tables b) Use correct data types: c) Use Star schemas d) Reduce cardinality e) Disable auto date/time tables. Turn this feature off in options, as it bloats the model with hidden additional data. Use a central date table instead. f) Aggregation tables g) Incremental refresh to reduce… Read more: Power BI Model Performance Optimization
• Comparison of Full Data Pipelines from Data Ingestion to Data Science
  A comparison of three types of data pipelines. Technology data flowCode data flow Technology Data flow Stage Path 1 — Microsoft / Fabric Path 2 — Snowflake + dbt (Cloud-agnostic) Path 3 — Google Cloud (GCP) Sources & Ingestion Azure Data Factory (ADF) Fabric Dataflows Gen2 Event Hubs / IoT Hub (stream) ADF Copy Activity,… Read more: Comparison of Full Data Pipelines from Data Ingestion to Data Science
• SQL Code comparisons: SQL Server, Snowflake, BigQuery
  When jumping from one project to another, it can be useful to be able to compare common code structures.I couldn’t find anything like this out there, so here it is magically created. Contents:Common Code StructuresWorking with DatesWindow FunctionsError HandlingCastingJoining TablesCTE (Common Table Expressions) Common Code Structures Topic SQL Server Snowflake BigQuery Select & Filtering SELECT… Read more: SQL Code comparisons: SQL Server, Snowflake, BigQuery
• Testing Dual mode in Power BI and BigQuery
  In this test, we will try to see the performance improvement of using dual mode in a Power BI dimension table using a cloud database and a shared dataset, so we don’t get the performance issues experienced in the first dual mode test on a laptop. Test 1In the first test, we will use a… Read more: Testing Dual mode in Power BI and BigQuery

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