If you’ve ever built a BI solution it’s likely you will have had to integrate third party data, and if that’s the case you will know how painful it often is to get your hands on that data. Badly designed portals you have to log into every week to download the data, CSV files emailed to you, APIs with complex authentication – it’s usually an unreliable, slow and manual process.
Some weeks ago, I had a challenge. I develop my own app to be published on the AppSource. As I always talk about “add some smartness into your apps”, it was strange not to include “some smartness” into my app. Right?
But the smartness is not always a synonym of machine learning. And not everything could (and need to be) done with ML. If you want to get and show some insights from your data, and you know how to get them – you are free to follow the classic dev approach.
One of the biggest headaches right now, is the missing feature for move data from a C/AL table to an extension table without having to do export and import, RapidStart Packages or other funky operations. The idea behind my method is to avoid too much data copying and instead rely on a Rube Goldberg’sk series of SQL rename operations.
Most of the focus on Power BI dataflows so far has been on the use of Power Query Online to load data from external data sources. However, when you create a dataflow you also have the option to attach an existing Common Data Model (CDM) folder stored in Azure Data Lake Storage Gen2:
Today Gartner released the 2019 magic quadrant for Business Intelligence. As expected (by me at least), Microsoft is continuing its trail blazing and now has a clear lead over Tableau in both ability to execute and completeness of vision. I thought it would be interesting to see a trend over time for the last 5 years, as this is the time period that I have been a professional Power BI Consultant. I needed some way to extract the numerical data points from the images I had collected. This article shows you how to do that. Here is the final output – a scatter chart with a play axis in Power BI of course.
I have already blogged in great detail many times about Power BI/Power Query data privacy settings (see this series for example) but there’s always something new to learn. Recently I was asked a question by Ian Eckert about how Power BI handles data privacy for cloud or web-based data sources after a dataset has been published, and it prompted yet more revelations…