A
CDS
(Core Data Services) concept is around for some time and it enables data
models to be defined and consumed on the database server rather than the
application server. The concept is important from many perspectives. It
provides: semantic layer (for use
cases like, analysis, operations, search etc.), a uniform data model for all transactional and analytical application
areas, and brings an simplifications
to the SQL database language, reducing technical complexity for the user. One
of the use cases for the CDS is Analytics/Business Intelligence.
Before
I dig into the Analytics related CDS view let’s define few more terms related
to this area. CDS Annotations describe
semantics related to the business data. The annotation enriches a definition of
a model element in the CDS with metadata. It can be specified for specific
scopes of a CDS objects, namely specific places in a piece of CDS source code.
The
CDS annotation can be ABAP specific (means consumed by ABAP runtime) or
Framework specifics ones. Particular frameworks ca be Service Adaptation
Definition Language (SADL), Business Object Processing Framework (BOPF), Analytics,
or Enterprise Search.
Let’s
focus on Analytics CDS annotations now.
Here we recognize two of them:
1 Analytics Annotations - Enable the Analytic Manager for
multidimensional data consumption, performing data aggregation, and slicing and
dicing data. BI front ends like Design Studio and Analysis Office can consume
the data via the Analytic Manager.
2 AnalyticsDetails
Annotations - Enable
application developers to specify the default multidimensional layout of the
query, the sequence of variables in UI consumption, and the specific
aggregation and planning behavior of the data. All these annotations can only
be used in views with @Analytics.query:
true. Such identified CDS views are called CDS Query.
Based
on Annotation Analytics.dataCategory
we can distinguish between following data categories of the CDS views:
1. Fact View = CDS view annotated with
@Analytics.dataCategory: #FACT
CDS entity is
represented by fact table (center of star schema) of transactional data object.
The fact table contains measures (key figures). Use case here is an replication
thus this type of the CDS view should not be joined with master data views.
2. Cube View = CDS view annotated with
@Analytics.dataCategory: #CUBE
What
it is cube view? Used for reporting on BW’s InfoProviders like cubes or aDSOs. It
is similar to #FACT but as reporting on only figures doesn’t bring any value
such an data need to be joined with master data objects. Example.
3. CDS Dimension = CDS view annotated with
@Analytics.dataCategory: #DIMENSION
Used for
reporting in master data. No key figure fields can be defined as key fields.
Only characteristic fields can be key fields. Example.
4. Aggregation level view = CDS view annotated with
@Analytics.dataCategory: # AGGREGATIONLEVEL
Used in
planning scenarios to provide write-back functionality.
Few
more words about naming conventions related to CDS Views. There are three
different technical names for the CDS view stored in table RSODPABAPCDSVIEW:
SQLVIEWNAME - Name of SQL View (ABAP Object), the
sqlviewname is used in the ABAP dictionary can be seen in t-code SE11.
DDLNAME - Name of CDS View
STRUCTOBJNAME - Name of view defined in CDS View
(Entity Name)
More
information:
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