I am trying to create a measure which should slice the value based on only one dimension in SSAS tabular.
e.g the cube has a measure Population. and it has dimensions Country and time the data is something like:
Crty_A : 2018 :100
Crty_A : 2017 :200
Crty_B : 2018: 50
Crty_C : 2018: 25
The data in the measure should get aggreted only at country level. like when only country name is selected the data should be like:
Crty_A :300
Crty_B : 50
Crty_B : 25
But if time and the measure is selected the data should be:
2018 :100
2017 :200
2018: 50
2018: 25
is there any way this can be achieved?
You should be able to add simple SUM into your formula that sums the entire column. Save that as your measure and then when you bring the measure into the downstream application (Excel, PowerPivot, PowerBI, ETC) the slicing should already be applied to that measure based on the filters being applied. I'm assuming that you have a star schema and all the tables appropriate relationships.
Measure_Name:=SUM(TableName[Population])
Related
I want to define a cube measure in a SSAS Analysis Services Cube (multidimensional model) that calculates ratios for the selection a user makes for a predefined hierarchy. The following example illustrates the desired behavior:
|-City----|---|
| Hamburg | 2 |
| Berlin | 1 |
| Munich | 3 |
This is my base table. What I want to achieve is a cube measure that calculates ratios based on a users' selection. E.g. when the user queries Hamburg (2) and Berlin (1) the measure should return the values 67% (for Hamburg) and 33% (for Berlin). However if Munich (3) is added to the same query, the return values would be 33% (Hamburg), 17% (Berlin) and 50% (Munich). The sum of the values should always equal to 100% no matter how many hierarchy members have been included into the MDX query.
So far I came up with different measures, but they all seem to suffer from the same problem that is it seems impossible to access the context of the whole MDX query from within a cell.
My first approach to this was the following measure:
[Measures].[Ratio] AS SUM([City].MEMBERS,[Measures].[Amount])/[Measures].[Amount]
This however sums up the amount of all cities regardless of the users selection and though always returns the ratio of a city with regards to the whole city hierarchy.
I also tried to restrict the members to the query context by adding the EXISTING keyword.
[Measures].[Ratio] AS SUM(EXISTING [City].MEMBERS,[Measures].[Amount])/[Measures].[Amount]
But this seems to restrict the context to the cell which means that I get 100% as a result for each cell (because EXISTING [City].MEMBERS is now restricted to a cell it only returns the city of the current cell).
I also googled to find out whether it is possible to add a column or row with totals but that also seems not possible within MDX.
The closest I got was with the following measure:
[Measures].[Ratio] AS SUM(Axis(1),[Measures].[Amount])/[Measures].[Amount]
Along with this MDX query
SELECT {[Measures].[Ratio]} ON 0, {[City].[Hamburg],[City].[Berlin]} ON 1 FROM [Cube]
it would yield the correct result. However, this requires the user to put the correct hierarchy for this specific measure onto a specific axis - very error prone, very unintuitive, I don't want to go this way.
Are there any other ideas or approaches that could help me to define this measure?
I would first define a set with the selected cities
[GeoSet] AS {[City].[Hamburg],[City].[Berlin]}
Then the Ratio
[Measures].[Ratio] AS [Measures].[Amount]/SUM([GeoSet],[Measures],[Amount])
To get the ratio of that city to the set of cities. Lastly
SELECT [Measures].[Ratio] ON COLUMNS,
[GeoSet] ON ROWS
FROM [Cube]
Whenever you select a list of cities, change the [GeoSet] to the list of cities, or other levels in the hierarchy, as long as you don't select 2 overlapping values ([City].[Hamburg] and [Region].[DE6], for example).
I have data in a cube, organized across 5 axes:
Source (data provider)
GEO (country)
Product (A or B)
Item (Sales, Production, Sales_national)
Date
In short, I have multiple data providers for different Product, Item, GEO and Date, i.e. for different slices of the cube.
Not all "sources" cover all dates, product, countries. Some will have more up to date information, but it will be preliminary.
The core of the problem is to have a synthesis of what all sources say.
Importantly, the choice of data provide for each "slice" of the cube is made by the user/analyst and needs to be so (business knowledge of provider methodology, quality etc).
What I am looking for, is a way to create a 'central dictionary' with all the calculation-types.
Such dictionary would be organized like this:
Operation Source GEO Item Product Date_start Date_end
Assign Source3 ITA Sales Product_A 01/01/2016 01/01/2017
Assign Source1 ITA Sales Product_A 01/01/2017 last
Assign with %delta Source2 ITA Sales Product_A 01/01/2018 last
This means:
From Jan2016 to Jan 2017, ProdA Sales in Italy, take Source 3
From Jan17 to last available, take Source 1
From Jan18 to last available, take the existing, add %difference across time from Source 2
The data and calculation are examples, there are other more complex, but the gist of it is putting slices of the "Source" 5-dimensional cube into a "Target" 4-dimensional cube, with a set of sequential calculations.
In SQL, it is the equivalent of a bunch of filtered SELECTs + INSERT, but the complexity of the calculations will probably lead to lots of nested JOINS.
The solution will be most likely custom functions, but I was wondering if anyone is aware of a language or software other than DAX/MDX which would allow to do this with minimal customization?
Many thanks
I have a table built off of a dataset. It contains both a column and row group. The intention is that each cell will specify it's percentage of the total in it's column, without looking at the row. For example:
Jan Feb Mar
New Accounts 50% 35% 86%
Old Accounts 50% 65% 14%
Currently, I have it set up with three groups: One parent, all-encompassing
row group, one row group that will limit to new or old accounts, and one month-specific column group. The code I'm using in each individual cell is as follows:
=SUM(Fields!amountOfAccounts.Value, "newOrOldAccountGrouping") / SUM(Fields!accts.amountOfAccounts,"allEncompassingGroup")
This works somewhat, but the issue is that it does not separate by column group - it just averages across all the months. As a result, I'll end up with something like this:
Jan Feb Mar
New Accounts 57% 57% 57%
Old Accounts 43% 43% 43%
I've already tried filtering by both row and column group, but Report Builder throws a scope error if I do so. For instance, the following code will not work:
=SUM(SUM(Fields!accts.Value, "columnGrouping"), "rowGrouping")
I'm not certain how to fix this, does anyone have any ideas?
Your expression should look like the one below
=Sum(Fields!accts.Value)/ Sum(Fields!accts.Value,"columnGrouping")
I have a linked table in Access that I want to update from a local table. The problem is that the linked table is used for specifications so it contains one line for each attribute. For example, the two fields used in the linked table are ATTRIBUTE_DESC and ATTRIBUTE_VALUE. Each specification may have multiple descriptions. Here is a sample from the linked table:
SPECIFICATION_NO SPEC_SEQ_NO ATTRIBUTE_DESC ATTRIBUTE_VALUE
------------------ ----------- --------------- -----------------
0000000001 10 MANUFACTURER AMERICAN DARLING
0000000001 15 MODEL B84B-5
0000000001 20 YEAR MANUFACTURED 2000
0000000001 25 DATE INSTALLED 5/3/1999
0000000001 30 EXTENSION LENGTH
0000000001 35 MAIN VALVE SIZE 6
0000000001 40 ISOLATION VALVE DIAMETER
0000000001 45 ISOLATION VALVE DIRECTION
0000000001 50 ISOLATION VALVE DISTANCE
0000000001 55 AS BUILT # C025-106-113
0000000001 60 ENVIRONMENT
0000000001 65 STR
0000000001 70 FIVE YEAR PM DUE OCTOBER 2015
The local table has different ATTRIBUTE_VALUES based on the ATTRIBUTE_DESC in the linked table. For example, above the MANUFACTURER might be CLOW instead of AMERICAN DARLING.
The query I created has all of the relevant specification information in the table and I've used the ATTRIBUTE_DESC with different criteria to update the ATTRIBUTE_VALUE.
Unfortunately doing it this way I get an error "Duplicate Output Destination "PROD_SA_SPECIFICATION_DETAILS.ATTRIBUTE_VALUE". So my question is whether there is a better way to update this type of table - either through a different query setup or via VBA. I don't know much VBA so if that is the best answer can I get an example for one of the attributes?
Thanks.
My query is like this:
Table being updated: PROD_SA_SPECIFICATION_DETAILS
Field: ATTRIBUTE_VALUE
Table: PROD_SA_SPECIFICATION_DETAILS
Update to: [UPDATE: SA_SPECIFICATION_DETAILS].[ATTRIBUTE_VALUE]
Criteria: MANUFACTURER
So I have the same for each criteria, none of the criteria are duplicated. In the case above there would be 13 as above with the different criteria. I realize I could use the sequence number since they are different for each spec but we add lines and remove lines on occasion and I'd rather not have to remember to update the query so that wrong information goes in the wrong fields.
I realize that this table is not normalized and that is by design (blame Oracle). It is not normalized because various specifications may be variable lengths, ie some may have 10 lines and some may have 12. There are two parts to this table the other is the SA_SPECIFICATION_DATA which is linked by specification_no.
I am new to MDX and I just want to ask if it is possible in MDX query to make aggregations and groupings on the fly.
Here is the scenario, I have a dimension called "Department". And it has department code values e.g.
1234
1257
1346
1390
I also had a measure called "Sales".
What I need to do here is to make a Calculated Member that will get the Maximum "Sales" grouped per department based on the its first two digits. For example, consider the following output when browsing the cube using the Department dimension and Sales Measure
Department | Sales
1234 | 100
1257 | 200
1346 | 100
1390 | 400
Then I need to make an MDX query to produce an output something like below,
Department | Sales
12xx | 200
13xx | 400
You will notice that Maximum Sales based on the two digits of each department concatenated with "xx" string were the expected output.
Well determining the maximum is not a problem. with <name> as max(<something>) but you should reconsider the approach with the on the fly grouping.
I'm sure, that it is achievable, although I cannot provide a solution, but it will perform poorly. (I'm assuming that the digits of the department are not implemented as measure)
If you need this grouping more often you should add an additional dimension, or better a hierarchy to the department dimension.