I have two tables which have counts and sales based on dates and one of them also have customer ID. The counts are not same when we see by customer and summary. I also have customer filter on my dashboard. What I want to achieve is if no customer is selected the count should come from summary table otherwise it should come from customer if multiple or one is selected in the filter.
Customer Table
Summary Table
Any hints, I have tried lookupvalue function but I cant put date as search value from date table.
It's much easier to use Measures, instead of creating calculated tables to obtain those metrics. Also, summarized tables would not have the same filter context your are looking for.
Measure 1
Total Customers =
DISTINCTCOUNT('Customer Table'[CustomerID])
Measure 2
Total Sales =
SUM ( 'Customer Table'[Sales])
Related
I need to create a kind of dynamic DAX view based on another DAX table.
First Table
Year, Category, Sub-category, Sales, Sub-Category Weight
I need to do a intermediary step different calculation for Sales on another table that looks at the above table however I can't work out how to do do it. I have a slicer populated with a subcategory dimension on the tab so every time I make a change I need the below table to reflect the chosen sub category but without it being in the table.
Second Table
Year, Category, Sub-category, Sales, Category Weight filtered by Sub-Category
I have tried the following functions:
Summarize
SummarizeColumns
CalculateTable
(think there are more)
I have tried to use each with a filter based on the slicer but I can't get it to work.
I have a table with below columns in my dataset. We have monthly revenue for each resellers in this table.
For few resellers, there will be no data for some particular months, as they didn’t generate revenue on those months. I want to create rows for those resellers with the missing date and the revenue for those missing dates to be updated as blank.
Please advise how we can achieve this.
Current data:
Expected result:
For the missing dates you need to create a date table using the CALENDAR function like this:
Date table = CALENDAR(MIN(Date), MAX(Date))
This will create a table with a single colmn containing all the dates in your table with filled gaps (even if you don't have certain dates in your table). Then you need to create a relationship between your table and the date table.
When you use the date and the revenue in a visual lets say table or matrix all dates will be visible but the revenues will be blank (except for those that actually had a value in revenue).
I have merged two tabels ( sales and forecast ). For all the rows coming from sales query the cost price column has a value. The forecast rows does not have that.
In order to calculate future metrics/KPI I need to make a Power Query transformation that populates cost price on all forecast rows. I would like to do some kind of refence to the ProductName (exits both on the sales and forecast rows) and pull the cost price from the sales rows. The ProductName can have multiple entries in the table, but will be the same for alle the rows. So maybe a find first/max or something would be fine.
However, I am not sure have to make this calcuated column with some sort of lookup to ProductName?
Well you can definitely do so
Here is an excellent Article form Microsoft on LookupValue
In addition check this Thread as well. It will give you more Idea.
I would do something like
=LOOKUPVALUE(Product[SafetyStockLevel], [ProductName], " Mountain-400-W Silver, 46")
I am fairly new to PowerBI DAX and I want to filter out the top 20 product ids in a measure.
I came up with this formula but it does not seem to be working and I was hoping to get some help here.
$ Amount Parcel =
CALCULATE(
SUM(Data[$ Amount Parcel]),
FILTER (Data, NOT (Data[idProduct], SUM(Data[NetSales])) IN TOPN(20, SUMMARIZE(Data, Data[idProduct], "NetSales", SUM(Data[NetSales]))))
)
I want to show sales per PID for all products except for our 20 best sellers.
Thank you !!
I would suggest an easier approach adding a dimension column.
First of all, you need to have Product dimension table separated from Sales fact table. Make sure to create one-to-many relationship between Product and Sales with "Single" cross filter direction.
Then you can create a calculated column on Product table, which can be used to filter out top selling products.
Sales Rank = RANKX('Product', CALCULATE(SUM(Sales[SalesAmount])))
Now drag and drop Sales Rank field into the Filters pane of your visualization, and set the filter condition so that top selling products will not be shown.
I have data from multiple countries on a monthly basis. Since the updates are not regular, I want to set up filter to visuals, so they would show the last month for which I have data from all the countries. I have data from each country loaded into a separate dataset, which then are merged into one big. Is there an easy way to place such filter? I managed to use "LASTDATE" function in each of country sets to find which date is last, but if I try to filter with that measure, I simply get nothing in a result. Thanks!
Well, this feels a little clunky to me but I believe it will work for you. There are two steps. The first is to create a summary table that reads through your data and counts the number of distinct countries that you have in each month. This will be a new table in your model, so go into the modeling tab, click 'New Table' and add this DAX. Obviously, correct for your table and column names.
SUMMARIZED_ROWS = SUMMARIZE(
'Table1'
,Table1[Month]
,"CountOfCountries"
,DISTINCTCOUNT(Table1[Country])
)
Now add a measure to the table (or anywhere) like this:
MonthWithMostCountries = CALCULATE(
LASTNONBLANK(SUMMARIZED_ROWS[Month], 1 )
, FILTER(SUMMARIZED_ROWS, SUMMARIZED_ROWS[CountOfCountries] = MAX(SUMMARIZED_ROWS[CountOfCountries]) ) )
This is going to give you the month where you have the most distinct countries in your data. You'll want to look at it in a card or similarly isolated visual as it is a measure and can be affected by filter context.
So, on the left is my mock data - 3 countries, 3 months each with a 1 month stagger. On the right you see the result of the Summarize table. Then the measure showing the final result.
Hope it helps.