I want to count the number of stores in a particular region within Power BI. Similar to how you would use a SUMIF in Excel.
Below is a rough example of what I mean (and the data in its current format) as I am unable to share actual snips due to sensitive information.
I'm happy for any working solution, even if the count of stores is repeated on the store lines.
Thanks.
Related
I need some help creating a measure to change the name of "FROM_USER" in the slicer here.
I think I need to use the function SELECTEDVALUE, but I have not managed to get it working.
So, the column has only two values, CRAWLER and FROM_USER.
Any suggestions would be helpful!
See picture
Measures can't be used as slicer values. If you want the column values to be changed and yet to be used in a slicer, you need to create a calculate column to change that.
Column = IF('Table'[Column1]="FROM_USER","desiredValue","CRAWLER")
If you are really keen on using a measure to slice, you need to build a disconnected table and follow the method described here. But the performance will take a hit depending on how complex your data model and calculations are.
I'm working on a project where we are converting a client from Tableau to PBI. One of the Tableau reports I'm converting looks like this:
Each row is a different calculation (measure). I can achieve a similar look, with regards to the column headers, in PBI by using a matrix. However, there isn't a way, that I know of, to apply a different measure for each row. The only way I can think of to do this is to create three matrix tables and stack them on top of each other. It won't look nearly as good but I can generate the same results. Does anyone have a better solution?
Put the Measure Names pill on Rows, Measure Values on Text and your date fields on Columns. That should give you when you want.
When I get data into Power BI I can edit the query as well as perform edit to the model.
What is difference between edit performed in query edit vs during modelling?
When you edit the query, you use Power Query, with its own Query Editor user interface. The steps you apply are recorded in the "M" language. Use Power Query to extract, transform, and finally load data into the Data Model.
Once the data is in the Data Model, you use DAX to create measures that you use in visuals. You can also use DAX to add more columns or even tables to the data model.
Whether to use Power Query or DAX to add columns or tables to the data model depends on a variety of factors. Some things are dead easy to do in Power Query, but harder to achieve with DAX, and vice versa. If you create a column with a formula that depends on a DAX measure, then you can only do that with DAX, because Power Query is not aware of the measures that are created after the load into the data model.
Power Query is very powerful, but the M code syntax is very different to the Excel formula syntax, or the VBA macro language. Learning to write advanced M code can be quite challenging.
DAX, on the other hand, behaves very similar to Excel formulas. Many Excel functions can even be used in DAX verbatim. If you know Excel, you've already got a head start on DAX and you can ease your way into it by learning additional functions and then expanding into more complex formulas.
The latter is probably the reason why many data manipulations are done in DAX, even though they could as well have been done in Power Query.
There are also some efficiencies with data storage and performance. Power Query makes use of query folding with SQL queries, for example, where its transformations are actually performed at the data source, i.e. on the SQL server side, and not in desktop client, and only the final query result is transferred to the desktop client.
Edit after comment: When the data is loaded into the data model, an algorithm processes the data and sorts it in a way that is most efficient for maximum compression and minimum storage. I don't have any concreate examples, but adding a column in Power Query will result in a smaller footprint than adding the same column with DAX. Read more about the compression algorithm VertiPaq here: https://towardsdatascience.com/inside-vertipaq-in-power-bi-compress-for-success-68b888d9d463
But apart from that, it mainly comes down to personal preference based on skill and experience.
By the way, many of your questions can be answered by reading through the Microsoft documentation, e.g. https://learn.microsoft.com/en-us/power-bi/guidance/import-modeling-data-reduction
I am new to Power BI and with the limited time given, I am stuck at how to come up with:
Below Table B-Row1 ("1/20" and "M"-Monday cell) - how to
specifically place the date measures in their specific cell and put
it in one column?
How can I merge the cells under the Total column?
How to add all the numbers from the Type1 and Type2 columns and place it in the merged cell in #2?
Any clues/direction/links on how to achieve the Target Table B below will be much appreciated.
PS. Below Table A. Current is just using Matrix Visualization in Power BI.
You can't exactly do what you are after. PowerBI allows you to rapidly put amazing visuals together however that comes at the price of lack of (easy) flexibility. You could build your own custom visual or look in App Source for a visual that does this, or build the Visual in some other tool (via custom code).
However, I'd recommend sticking with the PowerBI matrix, which will give you a cascading drill down and work out how best to align your data to it and other out of the box visuals. Once you start to delve in to convoluted work-arounds to give users data in exactly the format they request you start to burn a lot of time. Look for alternatives to tell the data's story and work with your end-user to buy in to it.
Just wanna share that I have resolved my problem not using one type of visualization, but through using 3 different visualizations in Power BI. I used:
1 Table visual for Date column
1 Table visual for Total column
1 Matrix visual for the Code+Type mapping and counts
I also used DAX function to get the Date format and another DAX function used for both Total and Code+Type counts(to filter data according to the specified date).
Thanks for the response, #Murray and #RADO.
In PowerBI I'd like to build Non-standard matrix very similar to the report in Google Analytics.
What do I have now:
I want to change my subtotal to measure, which is calculated as the difference in percentage of the two values
What I want to get:
In Power BI, there is no way to override the subtotals of a matrix with a calculation. Part of the challenge is that you know there are only two date ranges, but as far as Power BI is concerned, there could be any number of date ranges.
It's difficult to tell from your question exactly what input you have and what output you're looking for. Further, the numbers in your screenshots are obscured. However, one consideration would be to solve the problem using measures (i.e. a measure representing the first date range, a measure representing the 2nd date range, and then a measure calculating the difference between them). You may need to change the layout of your visual a little to make this work and the specific design would depend on how static your date ranges are.