I have a table products with some signs of participation in certain promotions.
The condition of promotion work like this:
Take any product from set 1 AND take any product from set 2
There is a big table of sales
and table about regions for sales of point
I need to make a calculated measure for promotion 1 as the unique number salepoint_id for points that fulfill the condition promo 1
I prepared a scheme in powerpivot
Added calculated fields
And measures
Result correct
but:
The sales table is large and the calculated field is not the best approach
It is assumed in the table to use a hierarchy (Year/Quarter/Month, Region/Territory) and therefore the use Allexcept becomes impossible
How to create a calculated measure that counts the number of unique sale points have complied with the condition of promotion based on the context of the PivotTable?
Download link example
Related
I have a Pivot Table with Salespeople as columns. I have income measures that correctly show (in the rows) the income each of them produced. However, I would like to show everyone's income in each column on some of the measures.
The reason is I want them to be paid on some income items (row measures) on the total of all salespeople not on their individual production.
Is there a way to make a measure ignore the column context?
DAX ALL
Try to use ALL function and give your column as a parameter.
It will clear currently applied filters.
How can I combine data coming from different tables.
Let's assume I have 2 tables:
First with sales:
id shop
id product
date
amount
Second with stocks:
actually, with the same structure
id shop
id product
date
amount
I need to analyze for how many days' stock there is in the shop now. For that I need to calculate the average sale per shop per day for last 20 weeks and then divide the remaining stock by the average sales rate.
How can I achieve this?
This is not a actual problem in MDX as you can combine dimension over different fact tables.
You need to create your 3 dimension (using reference table or similar) :
id_shop -> [Shop]
id_product -> [Product]
date -> [Time]
Now we need to add the two tables as 'fact' tables. Recall that Fact Tables are the ones defining measures.
In icCube create a default Cube, e.g. [Cube], and for each table create a 'measure group' (just click the '+' ).
Bind your tables to the dimension, the 'magic'wand will do the work and create a measure for each table (e.g. [Stock] & [Sales] ).
Once the schema is defined and deployed you can use both measures without taking even noticing they are coming from different tables :
[Measures].[Sales] / [Measures].[Stocks]
I have 2 fact tables with a measure group each, Production and Production Orders. Production has production information at a lower granularity (at the component level) productionorders has information at a higher level (order level with header quantities etc.).
I have created a surrogate key link between the two tables on productionorderid. As soon as I add Prod ID (from productiondetailsdim) to the pivot table it blats out the actual qty (from prod order measure group) and I cannot combine the qty's from the two measure groups.
How can I design the correct relationship between the two? Please see my dim usage diagram. Production Details is the dim that links the two fact tables, at the moment DimProductionDetails is in a fact relationship with Production. I'm not sure what the relationship should be with Production Order (it is currently many to many).
Please see example data between the two tables:
I have to be able to duplicate this behaviour:
Do you want the full actual qty from prod order measure group to repeat next to each product? If so a many-to-many relationship is right. I suspect once I explain how that many-to-many works you will spot the problem.
When you slice full actual qty from prod order measure group by product from the Production Details dimension it does a runtime join between the two measure groups on the common dimensions. So for example, if for if order 245295 has a date of 1/1/2015 while the production details for order 245295 have dates of 1/8/2015 then the runtime join will lose rows for that order and actual qty will show as null. So compare all the dimensions used on both measure groups and ensure all rows for the same order have the same dimension keys for those common dimensions. If for example dates differ then create a named query in the DSV that selects just the dimension columns from the production fact table which match the order fact table. Then create a new measure group off that named query and use the new measure group as the intermediate measure group in your many to many dimension. (The current many to many cell in the dimension usage tab should say the name of the new measure group not the existing Production measure group.)
Edit: if you want the actual qty measure to only show when you are at the order level and be null at the product level then try the following. Change the many-to-many relationship to a regular relationship and in the dialog where you choose how the fact table joins to the dimension change the dimension attribute to ProductionOrder_SK (which is not the key of the dimension) and choose the corresponding column in the fact table. Then left click on the Production Order measure group and go to the Properties window and set IgnoreUnrelatedRelationships to false. That way slicing actual qty by work center or by an attribute that is below grain in the Production Details dimension will show as null.
I wish to change the default aggregation from SUM to SUM on Distinct ID Values.
This is the current behaviour
ID Amount
1 $10
1 $10
2 $20
3 $30
3 $30
Sum Total = $90
By default, I am getting a sum of $90. I wish to do the sum on distinct ids and get a value of $60. How would I modify the default Aggregation Behavior to achieve this result?
Design your data as a many-to-many relationship: create one table/view having one record per ID and the amount column from the data shown in your question (the main fact table), and one table/view having one record per record of your data as shown in your question, presumably having another column, as otherwise it would not make any sense to have the data as shown in your question). This will be the m2m dimension table. Then, create a bridge table/view having the id of the m2m dimension table and your ID column.
Then create the following AS objects: A measure group from the main fact table, a dimension on column ID of the same table (in case there is no other column making a dimension table meaningful, in that case, you would better have a separate dimension table having ID as the primary key). Create a dimension from the m2m dimension table, and a measure group having only the invisible measure "count" from the bridge table. Finally, on the "Dimension Usage" tab of Cube Designer, set the relationship between the m2m dimension and the main measure group to be many to many via the bridge measure group.
See http://technet.microsoft.com/en-us/library/ms170463.aspx for a tutorial on many-to-many relationships.
I am trying to build a calculated measure in SSAS that incorporates a dimension parameter. I have two facts: Members & Orders and one Dimension: Date. Members represents all the unique members on my site. Orders are related to members by a fact key representing a unique user. Orders also contains a key representing the vendor for an order. Orders contains a key to the date dimension.
FactMember
- MemberFactKey
- MemberId
FactOrder
- FactOrderKey
- OrderId
- FactMemberKey
- DimVendorKey
- DimDateKey
DimDate
- DimDateKey
- FYYear
The calculated measure I am trying to build is the number of unique vendors a member has ordered from. The value of the calculation must of course change based on the date dimension.
Wouldn't the DISTINCTCOUNT function be the one to use here? Creating a distinct count of Vendors could then be used in this query and elsewhere.
WITH MEMBER [Test]
AS
DISTINCTCOUNT([Vendor].[Vendor].[Vendor])
I will say in advance that this may well be slow (Depending on data volume/distribution), so if this query will be a popular/big part of the design it may be worth considering a restructure.
I am confused, it would make more sense to make Members and Orders both separate dimensions and then reference them from a FACT table, say Fact.Sales. This would eliminate the need to even build a calculated member if you keyed your Members dimension on some sort of member_key.