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Hi All,
I have a couple of questions regarding PowerBI Capabilities. I have a desktop version free license. Planning to get a premium.
1. Does it have any limit (like 10k points) regarding data points for graphic/map images
2. How many rows of data can it manage to run without slowing the performance
Also, please provide suggestions for using larger data that will have millions of rows without slowing the performance.
Solved! Go to Solution.
@KALAKUNTLAS , These are limits for visual -
https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-high-density-sampling
Performance is a function of the model, data size, and hardware. A star schema with all numeric keys would be the fastest. Thin tables without unnecessary columns and rows would be another way to improve performance.
You need to choose premium hardware based on data. Also, use aggregated tables were needed to improve performance.
Hi, @KALAKUNTLAS
1. Purchasing a premium license doesn't change the limits of visual, and the limit you can see in the link shared by amit.
2. It depends on the connection mode. For Direct Query, you can returns 1 million rows maximum. For details you can check this link:
Solved: how many rows can power bi handle - Microsoft Power BI Community
3. Owning premium can make lagre datesets have better performance in service.
I don't know about Tableau, but Powerbi is better than Tableau in data analysis and data modeling. It's up to you to choose.
Did I answer your question ? Please mark my reply as solution. Thank you very much.
If not, please feel free to ask me.
Best Regards,
Community Support Team _ Janey
Thank you, Amit, for the quick response. We have a discussion whether to choose Powerbi or Tableau. We have more than 10k data points and large datasets (I am not sure if it is less than 10gb or greater than 10gb). No one has experience with Tableau. What do you recommend?
@KALAKUNTLAS , These are limits for visual -
https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-high-density-sampling
Performance is a function of the model, data size, and hardware. A star schema with all numeric keys would be the fastest. Thin tables without unnecessary columns and rows would be another way to improve performance.
You need to choose premium hardware based on data. Also, use aggregated tables were needed to improve performance.
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