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sohananahid
Post Partisan
Post Partisan

Clean up previous data posted in a dashboard?

Hi all: Good day! I have developed and published a dashboard that shows new ‘maintenance events’ and ‘critical notices’ on different pipelines in ‘Table’ visuals. I have added filter to pull only data that has ‘End Date’ of today or future [events that has not expired yet]. I am using ‘Import’ to Get data as I need to change format of Dates, etc. [tried ‘direct query’, doesn’t work]

sohananahid_0-1605029671878.png

 

The Power BI Publish Team in our company told us that the data memory report shows we are exceeding 1 GB memory limit.

I have a question: With our ‘Scheduled Refresh’ happening 4 times a day to pull new data and show those in the dashboard- what happens to the old data before the last ‘data Refresh’? Does Power BI desktop/Service side store those ‘old data’ in memory? If so, how can we delete those old data to free up memory space so that we are within our 1 GB memory limit?

Many thanks in advance. 😊

1 ACCEPTED SOLUTION
v-yingjl
Community Support
Community Support

Hi @sohananahid ,

Datasets in Import mode: 

Power BI imports the data from the original data sources into the dataset. Power BI report and dashboard queries submitted to the dataset return results from the imported tables and columns. You might consider such a dataset a point-in-time copy. Because Power BI copies the data, you must refresh the dataset to fetch changes from the underlying data sources.

Because Power BI caches the data, Import mode dataset sizes can be substantial. In shared capacity, the maximum size is 1GB, this is why you have been reminded that your dataset is over 1GB.

Please refer: Data refresh in Power BI 

 

"I have added filter to pull only data that has ‘End Date’ of today or future [events that has not expired yet]."

You can try to use incremental refresh for your dataset, refer: Incremental refresh in Power BI 

 

In addition, you can try to optimize your data model to reduce the dateset size:

  1. Optimization guide for Power BI 
  2. Data reduction techniques for Import modeling 
  3. Power BI Performance Optimization Tips 

 

Best Regards,
Community Support Team _ Yingjie Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

 

View solution in original post

2 REPLIES 2
v-yingjl
Community Support
Community Support

Hi @sohananahid ,

Datasets in Import mode: 

Power BI imports the data from the original data sources into the dataset. Power BI report and dashboard queries submitted to the dataset return results from the imported tables and columns. You might consider such a dataset a point-in-time copy. Because Power BI copies the data, you must refresh the dataset to fetch changes from the underlying data sources.

Because Power BI caches the data, Import mode dataset sizes can be substantial. In shared capacity, the maximum size is 1GB, this is why you have been reminded that your dataset is over 1GB.

Please refer: Data refresh in Power BI 

 

"I have added filter to pull only data that has ‘End Date’ of today or future [events that has not expired yet]."

You can try to use incremental refresh for your dataset, refer: Incremental refresh in Power BI 

 

In addition, you can try to optimize your data model to reduce the dateset size:

  1. Optimization guide for Power BI 
  2. Data reduction techniques for Import modeling 
  3. Power BI Performance Optimization Tips 

 

Best Regards,
Community Support Team _ Yingjie Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

 

lbendlin
Super User
Super User

Power BI does not store historic snapshots of your data. There is one caveat to that - during a dataset refresh Power BI briefly keeps two copies of your data - one to show to the users, and one that is rebuilt with the refresh. Once the refresh is complete, the old copy gets jettisoned and the new copy gets shown to your users.

 

Use DAX Studio or other tools to understand which tables in your data model cause the memory issues, or what measures  you have that may have excessive memory needs during calculation.

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