Is there a way to define dimension value synonyms for desired dimension values through ATG?
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I have got a dimension tables with 1 million records which is SCD type 2.I am using pentaho Dimension lookup step for populating this dimension table. I am getting a version number,start date and end date. Now I want to populate the fact table based on the scd type2. What is the best approach for this?
Use the 'Dimension lookup/update' step for looking up the surrogate id ('Technical key field'), based on the natural key(s) ('Keys') and timestamp ('Stream Datefield'). Uncheck 'Update the dimension' if you only do lookup.
I have this fact table
I want to create a calculated member like this : S = the sum of the "TOT_LIV" that have the "NUM_PROD" = 1
For example:
S should be equal to 50
How could I do it ?
Assuming you have a measure defined on this fact table named "TOT LIV", this measure has "Sum" defined as its aggregate method, and that NUM_PROD is a foreign key to a dimension named Prod having an attribute named Num Prod which I assume being based on the primary key of the dimension, and hence it would be 1 as well for the records that are references by the NUM_PROD primary key, you would use
([Measures].[TOT LIV], [Prod].[Num Prod].[1])
You see there is no 1:1 translation from SQL to MDX, a lot of things depend on cube setup, which predefines many behaviors that you have to repeat again and again in SQL queries (like the usage of sum).
I have entity called Dimension. It has three attributes - ID, width and height.
ID is primary key. In the table, the dimension should be unique so there has to be only one record with given dimension (for example 40x30). What constraints I need to set?
Is uniqueConstraints={#UniqueConstraint(name="dimension", columns={"width", "height"})} correct?
From the documentation,
#UniqueConstraint annotation is used inside the #Table annotation on
the entity-class level. It allows to hint the SchemaTool to generate a
database unique constraint on the specified table columns. It only has
meaning in the SchemaTool schema generation context.
Required attributes:
name: Name of the Index
columns: Array of columns.
The anwser is then YES
/**
* #Entity
* #Table(name="xxx",uniqueConstraints={#UniqueConstraint(name="dimension", columns={"width", "height"})})
*/
class Dimension
should then do the job.
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.
Hi i m new to SSAS 2005/08. I want to create Cube from 1 table , Stored in OLTP Database. Table containg billions of records.
how to select dimension and Fact from this alone table.
Please help me.
A dimension derived from data in the fact table is known as a degenerate dimension:
http://en.wikipedia.org/wiki/Degenerate_dimension
Here's a link discussing how to model an data as both a dimension and fact attribute, if that's what you're wanting to do:
http://www.ralphkimball.com/html/07dt/KU97ModelingDataBothFactDimen.pdf