Building Objects in SAP Datasphere

Objectives

After completing this lesson, you will be able to:

  • Build Objects in SAP Datasphere

Graphical Views

Suppose you have shared your SAP BW bridge models and other models with the customer Space in which you want to integrate the different data sets. Suppose you want to connect additional non-SAP sources. It is recommended to avoid copying data. Instead, you define a graphical view in the Data Builder tool of SAP Datasphere core tenant.

Databuilder artifacts

The figure, SAP Datasphere Data Builder Artifact Types, shows the entry point from the navigation bar on the left side of the SAP Datasphere home page and some useful types of artifacts for this purpose.

Creating Graphical Views

The series of screen captures shows the SAP Datasphere modeling process: First create a connection in your space and select source objects, then build your model with transformation elements in the view canvas. Finally, define additional properties (settings) for view type, view persistence, associations, data access controls, or measure types.

SAP Datasphere provides an editor to model Data Builder artifacts in an intuitive graphical interface.

The graphical view allows you the following options:

  1. Drag and drop sources from the Source Browser
  2. Add transformation operators in the intended sequence to a canvas
  3. Specify details of your output structure in the output node

The first step is to choose the source object(s).

The next step is to define include nodes for transformation steps. In a view, these steps are performed at each time when data is accessed.

This screen capture shows how you define a graphical view. It shows an example with a join of Sales Orders and items. After a Union or Join element, calculation elements with formula, filter elements, projection elements to remove or rename columns or, alternatively, aggregation elements to sum up values are graphically displayed. On the right side, the modeling details are visible. The action buttons Save, Deploy, and Share on the top left are highlighted.

The following table lists the available operators.

Types of Transformation Operators

Transformation OperatorPurpose
UnionCombine two data sets with similar columns
JoinCombine two data sets based on a join condition
FilterDefine a condition to restrict the data set
ProjectionRename or remove columns
AggregationAggregate values
FormulaAdd a column with a calculation

Finally, define additional properties (settings) for view type, view persistence, associations, data access controls, or measure types.

This screen capture shows how you define a semantic usage of a view or table in SAP Datasphere. It is an option in the general model properties below the model names. Possible Semantic usage options are also listed in the following lesson text.

When setting a Data Builder model, you have to make a decision on the semantic usage type:

  • Relational Dataset: [default] Contains columns with no specific analytical purpose.
  • Dimension: Contains attributes containing master data like a product list or store directory, and supporting hierarchies.
  • Fact: Contains one or more measures and attributes and form the foundation for the Analytic Model.
  • Text: Contains attributes used to provide textual content in one or more languages.
  • Hierarchy: Contains attributes defining a parent-child hierarchy.
Note
For transactional data that with measures that should be displayed in reports, you should choose Fact.

This screen capture shows how you define a semantic type of a column.

Modelers can specify semantic types for fields to identify the type of data in your columns (attributes and measures) in Facts and Dimensions. This property defines the contents of a column, for example, a value, a quantity, a date, geo or textual information, or another kind of semantic information. Semantic types are used by the core engines for data processing, analytics, and data consumption.

Note
If you have already defined similar semantic properties in SAP BW bridge, are lost during the import of the objects. Therefore, you must define them again.

At the end, you save and deploy the model.

Watch the following video and learn how to create a graphical view.

It is possible to preview the data contained in your tables and views and, when working in the graphical view editor, the data output by each of the nodes in the diagram. The preview options is not only available in graphical modeling, but also for the other SAP Datasphere artifacts.

Now, you want to make the enriched data set available for consumption from external tools, add parameters and business-oriented measures. Therefore, you should learn about the model type Analytic Model which is designed for this purpose.

Analytic Models

Creating Analytic Models

Suppose you have defined a consistent data foundation. You could make a graphical view available for consumption, but selecting specific subsets, defining parameters and must be done in SAP Analytics Cloud (SAC). There is an easier, recommended way.

The image shows positioning the Analytic Model. It is based on a fact model and can have associated dimensions, hierarchies, or texts.

In SAP Datasphere, Analytic Models form the analytical foundation for making data ready for consumption in SAP Analytics Cloud (SAC). They enable the definition of multidimensional models to provide data for analytical purposes for different business questions. Predefined customer-specific measures, complex aggregations (including exception aggregation), hierarchies, filters, variables, and associations provide flexible and simple navigation through the underlying data.

The only possible sources for Analytic Models are views of semantic type Fact. During modeling, there is the option to select relevant attributes, measures and any associated dimensions, texts, and hierarchies.

The image describes possibilities of the Analytic Model. Fact is the only possible source. It shows some of the options in the Measures section , such as creating a Calculated Measure, a restricted measure, a Distinct Count Measure, Currency Conversion Measure. In the Variables section, it displays the option to generate a Source Variable, Restricted Measure Variable, Filter Variable, or Reference Date Variable.

The Analytic Model is the core Artifact for Consumption of SAP Datasphere data, especially in SAP Analytics Cloud.

Launch the following video to learn how to create a simple Analytic model.

The Analytic Model offers the following features:

  • Distinct count measures
  • Calculated and restricted measures, with or without constant selection (to be used as reference values)
  • Currency conversion measures
  • Nested dimensions (this is a dimension of a dimension)
  • Variables for filters, restricted measures, reference data, and source variables for calculations
  • Multidimensional preview including filtering, pivoting, hierarchies
  • Integration with the repository
  • Impact and lineage analysis

Since Q2.2023, there has been a big change in the modeling architecture in the SAP Datasphere Data Builder.

  • The Fact View has replaced the Analytical Dataset. The Analytical Dataset can still be maintained for compatibility reasons, but new applications should now use the Fact artifact instead.
  • Facts are designed 100% like Analytics Datasets with the exception that during deployment, only the relational HANA view is deployed and the analytical star schema for SAC is not deployed any more. This means, all analytical modeling should happen in the Analytic Model that consumes the Fact. This new approach separates relational from analytical modeling.
  • For this reason, this artifact has many features which a special for a reporting requirement (for example, variables, currency conversion, calculations, associations, and so on).

Log in to track your progress & complete quizzes