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Hi,
I am trying to create a Power BI visualisation that is able to provide (1) year on year and (2) daily movement in both value and % when I select different run dates from the filter. Basically the whole dataset will have a few run dates across few different years and I need to be able to compare them based on the selected run dates.
I have tried creating a new date table; to form the relationship to the main data table so that it can be used for filter but it doesn't seem to work. I am not sure how what kind of measures or how to approach it further so that this can be achieved. Would you be able to advise?
Below is an example of how the main data structure looks like.
Account | Account Type | Account Type 2 | Account Description | Code | Code Type 1 | Code Type 2 | Year | Month | Owner | Run date | Amount |
Asset | Current | Cash | Cash on Hand | 15463 | AWE | S1 | 2021 | 05 | Ram | 31 May 2021 | 1000 |
Asset | Non Current | Bank | Cash in Bank | 35671 | AWS | S2 | 2021 | 05 | Ram | 31 May 2021 | 5000 |
Expense | Operating | General | General Cost | 65542 | ERT | T6 | 2021 | 05 | Mary | 31 May 2021 | 300 |
Expense | Manufacturing | Direct | Direct Manufacturing | 78953 | EPB | T7 | 2021 | 05 | Mary | 31 May 2021 | 200 |
Asset | Current | Cash | Cash on Hand | 15463 | AWE | S1 | 2021 | 05 | Ram | 29 May 2021 | 200 |
Asset | Non Current | Bank | Cash in Bank | 35671 | AWS | S2 | 2021 | 05 | Ram | 29 May 2021 | 200 |
Expense | Operating | General | General Cost | 65542 | ERT | T6 | 2021 | 05 | Mary | 29 May 2021 | 50 |
Expense | Manufacturing | Direct | Direct Manufacturing | 78953 | EPB | T7 | 2021 | 05 | Mary | 29 May 2021 | 100 |
Asset | Current | Cash | Cash on Hand | 15463 | AWE | S1 | 2019 | 05 | Ram | 31 May 2019 | 5000 |
Asset | Non Current | Bank | Cash in Bank | 35671 | AWS | S2 | 2019 | 05 | Ram | 31 May 2019 | 7000 |
Expense | Operating | General | General Cost | 65542 | ERT | T6 | 2019 | 05 | Mary | 31 May 2019 | 2200 |
Expense | Manufacturing | Direct | Direct Manufacturing | 78953 | EPB | T7 | 2019 | 05 | Mary | 31 May 2019 | 3000 |
@Anonymous The recommendation is to create a data model and to normalize your one big table into reasonable dimension and fact tables. Dimension tables could be the calendar, the Owner/Person table, the Account table etc, and the fact table could be the amount and code.
With that in place you will be able to use the standard DAX functions for time intelligence. The Quick measures also give you a great starting point for these patterns.
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