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I'm new to Power BI. I have a 12 tables (one for each month of the year) which are identical in terms of the names of the columns and rows. In each table is a column which identifies an Availability % for various common Resources (as rows).
I want to create a new table called Availability Summary. The table needs to contain 12 instances of the Availability % column, one from each of the 12 tables.
In this scenario, you have one table for each month, each of them has different number of rows, it's not possible to "join" 12 different Availability Summary columns together.
It's insignificant to include them into same table. And it's not good practice to split your data into 12 tables. You should combine all data into one table so that you can build an entire Calendar hierarchy for your table. It will be much easier to categorize your data on different date part level when populating into a visual.
Regards,
@v-sihou-msft Thanks for the insight. I may be misunderstanding what you are saying so forgive me.
My intent is not to join 12 availability columns together. I am investigating if, within a Summary Table, I could replicate each of the 12 availability columns individually to show the values held in the source 12 tables and then use the Summary Table as my source from which to build visualisations and conduct any necessary tranformations.
I take your point that it is not good practice to split my data into 12 tables. These 12 tables represent the source 12 spreadsheets and I am seeking not to change the source data. I hoping I can perform the necessary transformations in Power BI so the business can continue to output thes source spreadsheets and the Power BI model function.
I have considered merging these 12 spreadsheets on upload however each is a snapshot in time and this the same row item will be repeated numerous times. My concenr here is that if I merge them how will I be able to realise which rows relate to which snapshot period.
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