Sometimes we encounter a bunch of mixed strings, which contain various types of information, such as dates, numbers, currencies, etc. How to extract date/currency amount from such text strings?

This is a blog about how to fuzzy match the dirty data and horizontal display the corresponding table

Scenario:

In Power BI Desktop, when we connect to a .json file, power query editor will transform it automatically if its structure is single.

The basic navigation panel used by M query function can calculate with query table records and add different query steps into the query table. They were not suitable to handle some complex scenarios(e.g. apply some advanced operations with its result or interaction with its calculations contents).  

In this article, I would like to share some tips on nested functions to handle some general scenarios where some basic functions don’t work.

The article is about Partial Grouping in Power Query.

This is a blog about Count the number of successes/failure and combine the reasons for failure for each machine.

This is a blog about how to batch crawling web page data

A year ago, I was developing a solution for collecting and analyzing usage data of a Power BI premium capacity. There were not only some simple log files, but also data that I had to convert into a slowly changing dimension type 2. Therefore, I decided for the following architecture - Azure Data Factory pipelines collect data on daily basis, the raw data is stored in a data lake forever, and the cleansed data is then moved to a SQL Server database. Because the data is stored on a SQL Server, I can use incremental refresh in Power BI service. It works perfectly.
But the times are changing, new requirements are coming, and I have found a new straight way, how to load logs directly from the data lake into a Power BI dataset. And all that incrementally! Where I need a SCD, a SQL Server database will stay in the middle, whereas for all other data I can use a new mindset.

In this article I want to show you how you can load parquet files stored in an Azure data lake direct into your Power BI dataset. It involves an incremental refresh and an ETL process, too!

As shown in the following sample table, when we want to get all the values of the ID with the latest start time, we need to filter twice to get the result.
Ex: The Dataset ID (A) contains the latest Start Time. Now we want to get all rows which contain Dataset ID A. We can see Dataset ID A has two rows. If we only filter the latest Start Time, we can only get one row of A.
Therefore, we first get the dataset ID based on the latest start time, and then get all the values by filtering the previous obtained dataset ID(A).
If you want to get result in the example table below, you can use Power Query or Dax.

Do you every dream of becoming the Heavy-weight Power Query Champion of the World? Join our Power BI Dev Camp session on March 25th for a fast-paced primer on the fundamentals of the M programming language. The goal of this deep dive session is to give campers a stronger foundation for working directly with M code in the Advanced Editor when designing queries for datasets in Power BI Desktop or when designing queries for dataflows in the browser.

The default display style of Power BI (whether it is a table or a matrix) is nothing more than interlaced display. Such a layout cannot help us intuitively find the details of each country at a glance. The conditional format in PowerBI can help us solve this kind of problem very well.

This article uses a simple example to briefly introduce how to change the interlaced background style of the table/matrix based on measures and custom columns.