Often, friends & colleagues ask me about learning Power BI and the best sources to do that. Below is my answer
Updated: 31/10/2019
I use several channels:
- on Twitter (I’m @Vitali_Burlathere) and LinkedIn I follow Marc Reguera, Amir Netz, Matthew Roche, Patrick Le Blank, Adam Saxton, Daniil Maslyk (who frequently teases info about upcoming features), David Eldersveld, Gil Raviv, Matt Allington, Chris Webb, Phil Seamark, Alex Powers, Joel Crest, Devin Knight.
- on YouTube I follow the channel of Microsoft Power BI and a few more (Guy in a Cube, EnterpriseDNA, BI Elite, Havens Consulting, Curbal, Excel on Fire, Avi Signh). SQLBI don’t maintain their channel often, but their videos are here.
- on Facebook I’m in the Global Power BI user group, as well as in our local Sofia Power BI User Group;
- I’m subscribed to a few newsletters – by Ken Puls (for Power Query), by Lars Schreiber, Radacad, the monthly newsletter from SQLBI (Marco Russo and Alberto Ferrari), Enterprise DNA by Sam McKay, Datachant by Gil Raviv
- I (try to) read the blogs of the people above plus some more like The Biccountant by Imke Feldmann (strongly recommended for financial/accounting tasks), that of Maxim Zelensky, Uwe Meister, Hans Peter Pfister, Prathy Kamasani, Matthew Rosche (for Dataflows!), Miguel Angel Escobar (Power Query), dax.tips by Phil Seamark and powerbi.tips by Mike Carlo & team.
- For a good starter course edx.org offers a free one and another one you can find if you search for “Power BI Guided Learning”
- Free starter courses can be found also on SQLBI.com, EnterpriseDNA, ExceleratorBI, PowerPivotPro
Disclaimer:
I’m not listing books here because I have very little time to learn and I usually learn on the go, during my commute, on my phone, or while addressing a task. However, 4 free books are available on Radacad!
There are many good books for Power BI/Power Query/Power Pivot, the reviews on Amazon/GoodReads/Book Depository are plenty. In my opinion though, you need real-life cases to really understand the solutions a book offers and, preferably, some practical experience to build on and relate to.
Тitle photo: Photo by Janko Ferlic on Pexels.com
Vitali on Data 