Supplies are limited. Contact info@espc.tech right away to save your spot before the conference sells out.
Get your discountScore big with last-minute savings on the final tickets to FabCon Vienna. Secure your discount
Hello All!
I am working on a model to track the activities completed by our service team to see whether they are being over/underworked. This is done by taking data from our system and using a query to link it to Excel. The model is complete but I am somewhat new to using PowerQuery/Pivot and I don't believe that it is optimized enough.
I need to start tacking on historical information so that I can compare month to month information. Currently I am just increasing the size of the source data every month in order to eliminate extra connections (Query starts as Jan 1 - Jan 31, next month becomes Jan 1 - Feb 28). My concern with this method is that each month contains around 10,000 - 15,000 rows of data. Currently the model is floating around 20,000 lines of data in the query, and it takes just over 7 minutes to refresh the workbook, and I'm worried that this will increase exponentially as the months go on.
Is there a more efficient way to query this type of data in general? I know that Excel is supposed to be able to handle millions of rows of data, but I'm not sure if it can handle this in queries. I am more than happy to post a copy of the workbook if the inefficiencies involve my query steps themselves putting a strain on the workbook.
Thank you in advance for your help!
Hi @Anonymous . Do you have access to Power BI? There is an option to incrementally load data to avoid re-query every day since the being of time.
User | Count |
---|---|
12 | |
11 | |
8 | |
6 | |
6 |
User | Count |
---|---|
24 | |
19 | |
14 | |
10 | |
7 |