I have a couple measures in a Power Pivot data model to analyze activities by a group of consultants:
Total Activities = calculate(DISTINCTCOUNT(ServiceRecords[Activity ID]))
Service Status = if([Distinct Activities]>=5,2,IF([Distinct Activities]=0,0,1)). >> This is to assign a numerical status to customers based on volume of activities
I have a pivot table set up to slice by consultant and show the output of these measure against clients in rows.
I run into trouble when I add a new fact table (Addressable) to the model - this contains Yes/No feedback from sales as to whether a particular account is relevant for a particular consultant. This is linked to the original fact table with two typical index tables classifying consultants and classifying accounts. But the direction of the relationship is inwards from the index tables to this table.
What I'm trying to do is add a second slicer by the Yes/No field in "Addressable" to filter only the records that show Yes or No for the chosen consultant. I thought a CROSSFILTER measure was supposed to do this, but it ends up filtering the data behind calculation of the existing measures instead of just filtering the view. Any idea what I should be doing here?
Related
I am trying to provide on of our FHF fundraising campaign managers with a tool they can use to help them pick postcodes to send a campaign to.
Spoecifcally, I'm seeking help writing an Excel PowerPivot Measure for a cumulative total that counts only the visible cells in a Pivot Table and wherein the source data is OLAP (i.e. an Excel Data Model - which seems to carry some constraints to possible solutions)
The linked worksheet is a simplified example of the excel worksheet tool I want to give to the Campaign Manager in a Fundraising setting https://www.dropbox.com/scl/fi/3pfc8ix2ekduoocsa90zs/minReprodExample_share1.xlsx?dl=0&rlkey=m6gqf5zbjxhl6dzkjq653it3d
We have two predictive models both giving different predicted response rates per postcode
The 'data' tab contains the raw data
The 'modelA_pivot' tab contains a pivot table ranking the raw data according to the predicted response rates from ModelA
'model_pivotB' does the identical pivot for ModelB
Focussing just on the 'modelA_pivot' tab for now
you can see a slicer that allows the campaign manager to exclude postcodes with only 3,000 addresses
(or some other threshold level of their choosing)
The slicer's exclusion of a single postcode with 3,000 addresses in this example is why you see the rank column in the pivot run; 1, 3, 4, 5
(i.e. missing rank 2 postcode with 3,000 addresses)
In the pivot, the last column - 'addressCount_postcodeCumulative_modelA' - is based on an excel Power Pivot 'Measure'
And the current formula of the measure is
=VAR rankCurrent = MAX([rank_modelA])
RETURN
CALCULATE(
SUM([addressCount_postcodePer]),
FILTER(
ALL(data),
[rank_modelA] <= rankCurrent
)
)
You can see in the 'modelA_pivot' tab the 'addressCount_postcodeCumulative_modelA' column
doesn't work or make sense. As it includes the cumulative total of ALL addresses (including the 3,000 addresses that are excluded from the pivot)
Can anyone help me with a 'Measure' formula that sums only the addresses of the postcodes that are visible and included in the pivot table
FYI and in case anyone is wondering, why a 'Measure'; I am using excel Power Query and Power Pivot so if/when the data upstream changes, the data team will be able to refresh this worksheet with a single click (more or less), and the campaign manager still gets to use excel (the tool they know and like)
But, the use of excel Power Query and Power Pivot and setting this up as an excel Data Model (which uses OLAP structured data)
is also injecting constraints which I'm hoping to fit the answer to this puzzle inside
Constraints such as;
I can't seem to put calculated fields onto the pivot table, and
I don't want to just add conventional excel columns on the side of the pivot table as the size of the pivot table is dynamic depending on choices of the Campaign Manager (like their choice of threshold # addresses in the slicer)
Goal
Create a working relationship between my Category Sales and Voids PivotTables so I can leverage one slicer for all data.
Background
Using two PowerQueries, I pull in data from SQL to Excel. Because Sales and Voids have DateStamp and StoreID columns in common, I essentially concatenate these in the SQL query to create an ID. For example:
select concat(StoreID,convert(int,DateStamp)) as ID, DateStamp, StoreID, Category, Sales from...
select concat(StoreID,convert(int,DateStamp)) as ID, DateStamp, StoreID, Voids from...
This is a one-to-many relationship between the two (Sales --> Voids)
Problem
Despite creating the relationship in Excel (through Manage Relationships, as PowerPivot is not available) I can't get it to apply and Excel tells me relationships between tables may be needed. I've no idea what I'm doing wrong.
Workaround
The only workaround I can think of is to take the void value for a given day and divide by the number of categories that have sales, then just do a join to create one table that I pull into Excel. It would technically work for my application, but I'd love to know why the relationship isn't working.
Thanks.
The answer is to export your data into the data model so that you can use power pivot, PLUS a export another power query (or several) into the data model that is a deduplicated table of keys.
Then, in the data model editor, set up the data relationships so that there is a one to many relationship between your deduplicated key table(s) and the "actual data".
Then, in a power pivot, use those "key" tables as much as possible, maybe even to the ruthless ideal(1) of using ONLY key tables in your primary row and column headers, and if you have a second level of categorization then a deduplicated table of primary to secondary, and so on, then using the real data tables only in the body of your power pivot.
(1) - Keep in mind that this is just an ideal I'm just explaining to help you understand and maybe start moving towards as much as actually makes sense. As with most things, in reality, the ideal is almost never worth reaching because there are other factors (like your own patience and time).
I have a very large dimension in my OLAP cube - a customer dimension. Each customer has her own unique ID. I require a pivot table to be filtered for a single specific customer (ID).
Unfortunately Excel Pivot table takes very long to display the appropriate customer ID (checkbox) in the report filter.
It also does not help to pre-select customer from a specific town or birth year - it seems that all customers are scanned anyway.
How can I speed up this process?
Is there maybe a specific setting/property that I can apply in the SSAS solution?
Would attribute relationships help?
Can I maybe pre-calculate something in the cube?
Maybe I should add an additional attribute to the dimension?
Try Olap Pivot Table extensions for Excel. You can insert a filter list without having to wait for the costly excel filter.
You could add an attribute hierarchy to the customer dimension ItIsJoeBloggs. In the customer dimension table this would be True for the JoeBloggs rows and False for all others.
Then in Excel this hierarchy could be an additional filter with True selected.
Or in another words the question is - how to add some calculation in the pivot table based on columns which do not exist in model level.
I've reproduced my problem using AdventureWorksDW2014 sample database.
Let's say I want to calculate difference between Actual and Budget scenario amounts in the FactFinance table for each Organisation and present it in a form of pivot table.
To achieve that I've created a simple model (screen above) and added SumOfAmount measure to the FactFinance table SumOfAmount:=SUM([Amount])
Next, I've opened my model in Excel and created very simple pivot table (shown below)
So, (the question part) now I want to add an extra column to my pivot table, which should calculate something (for example difference) between columns Actual and Budget. And I want this new column been a part of the pivot table so I could filter it or\and add new grouping levels without necessity to change something "outside" the pivot table.
TRIED SO FAR
I tried to add Calculated Field but it seems like I can only use "real" columns for calculations. Columns which appeared in a pivot table based on values from COLUMNS quadrant can't be used as sources for calculations.
FINAL SOLUTION
I got it finally combined two pivot tables: the old one and the one with Diff measure, defined as Diff:=[Actual Amount]-[Budget Amount], where
Actual Amount:=Calculate([SumOfAmount];'DimScenario'[ScenarioName] = "Actual")
Budget Amount:=Calculate([SumOfAmount];'DimScenario'[ScenarioName] = "Budget")
as #WimV suggested
First calculated measure is good:
SumOfAmount:=SUM('FactFinance'[Amount])
Add the following Calculated measures (if needed mark as hidden):
Budget Amount:=Calculate([SumOfAmount],'DimScenario'[Scenariokey] = "Budget")
Actual Amount:=Calculate([SumOfAmount],'DimScenario'[Scenariokey] = "Actual")
You can use the new calculations for example in a difference calculations
I have few tables in my data source in Power Pivot:
One is a "Calendar" table from Azure Marketplace (http://datamarket.azure.com/dataset/boyanpenev/datestream) that I'm using for user friendly date representation. Clients table that has basic information about clients (ClientId, Client Name, Recent Address). Each clients may have multiple Accounts (AccountId, Account Name, ClientId). And I have AccountActivity table (AccountId, Date, Income). I've setup relations between tables accordingly.
I need to build a resulting table that is based off AccountActivity and will have Date(Month, Year), Sum of Incomes, # of accounts and # of clients. I was able to get everything except # of clients. Once I'm adding # of clients into the table it starts to complain that there is no reference and instead of showing proper # of clients it is showing total # of clients that does not have any relation to the accounts. Is there any way of making it work or I will have to add into AccountActivity ClientId column?
You shouldn't need to add the ClientID to your source. You can just make a calculated column in your PowerPivot model. I recreated what I think you have
I made 3 tables with fake data that includes 4 clients, 6 accounts:
I added them to my data model and then added the DateStream to my model and created relationships.
Then I:
Went to the activity table in my model and added a calculated column [ClientID] with formula =related(Client[Client ID]).
Created a calculated measure [# Clients]:=DISTINCTCOUNT(Activity[ClientID])
Created a calculated measure [# accounts]:=DISTINCTCOUNT([AccountID])
Created a calculated measure [Sum of Income]:=SUM([Income])
Then I created a pivot table. These calculated measures seem to work across all of your dimensions.