Don't miss your chance to take the Fabric Data Engineer (DP-700) exam on us!
Learn moreWe've captured the moments from FabCon & SQLCon that everyone is talking about, and we are bringing them to the community, live and on-demand. Starts on April 14th. Register now
Hi, I have a big problem in completing my queries for a huge dataset which until now I still have no idea what has caused this. Thus, I was thinking to transfer my data back to MySQL database and extract it for my subsequent query.
I would like to know how can I transfer my queried data to MySQL database?
Solved! Go to Solution.
You can use an R-script for this task: https://www.youtube.com/watch?v=ANIZkTZO3eU
You might also want to check out my collection of performance killers here: https://www.thebiccountant.com/speedperformance-aspects/
Imke Feldmann (The BIccountant)
If you liked my solution, please give it a thumbs up. And if I did answer your question, please mark this post as a solution. Thanks!
How to integrate M-code into your solution -- How to get your questions answered quickly -- How to provide sample data -- Check out more PBI- learning resources here -- Performance Tipps for M-queries
You can use an R-script for this task: https://www.youtube.com/watch?v=ANIZkTZO3eU
You might also want to check out my collection of performance killers here: https://www.thebiccountant.com/speedperformance-aspects/
Imke Feldmann (The BIccountant)
If you liked my solution, please give it a thumbs up. And if I did answer your question, please mark this post as a solution. Thanks!
How to integrate M-code into your solution -- How to get your questions answered quickly -- How to provide sample data -- Check out more PBI- learning resources here -- Performance Tipps for M-queries
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
| User | Count |
|---|---|
| 57 | |
| 37 | |
| 34 | |
| 19 | |
| 17 |
| User | Count |
|---|---|
| 74 | |
| 70 | |
| 37 | |
| 35 | |
| 25 |