Listing the Key Components of SAP S/4HANA embedded analytics

SAP S/4HANA embedded analytics is a core component of SAP S/4HANA on-premise and cloud editions. Its purpose is to support operational analytics.

SAP S/4HANA embedded analytics provides powerful analytical tools inside the business transaction. That is why the solution has the name embedded analytics.

With SAP S/4HANA embedded analytics, there is no need to leave a transaction to open up a new application to work with analytics. In many cases, analytics are presented alongside the transactional data. For example, when an HR user works through a list of leave requests, they might view a chart that provides information relating to future work-loads so they avoid approving leave requested on busy days. As they select each employee who has requested leave, a chart appears indicating the workloads for that employee's department for the requested leave date.

SAP S/4HANA embedded analytics includes a large number of ready-to-deploy analytical applications that are aligned to the lines-of-business across the enterprise. These analytical applications are organized by roles, so once a user has been assigned to a role they can get started with analytics.

SAP S/4HANA embedded analytics meets the key requirements of operational analytics as follows:

• Access to live data: the live tables from SAP S/4HANA are used
• Fast response: powered by the SAP HANA in-memory database
• Access from any device: SAP S/4HANA uses SAP Fiori user interface which supports any device
• Access to analytics within the business transaction: many SAP S/4HANA apps include embedded analytics
• Ability to immediately act: links to common actions are provided from the analytical applications

SAP S/4HANA embedded analytics includes two key components: analytical applications to display and create analytical content and an enterprise-wide virtual data model.

Launch the video to learn about the components of SAP S/4HANA embedded analytics:

SAP S/4HANA embedded analytics includes applications for three types of user:

• Business User
• Analytics Expert
• IT admin / Developer

For the business user, there are various ready-made applications including Overview Pages that provide a birds-eye view of the entire business performance of a line of business. There are Multidimensional Reports that provide flexible navigation across business data for ad-hoc exploration. Each of the analytical applications can be fine-tuned by the business user to suit their requirements.

For the analytics expert, there are tools to extend and create new analytical content. For example, developing custom queries and reports. The analytics experts can create new KPIs and Fiori tiles.

For the IT admin / developer, there are tools to enable the business user and to create new database views.

The virtual data model sits between the database tables and the analytical applications.

But why do we need a virtual data model? Why can't analytics read data directly from the database tables?

The SAP S/4HANA database contains a very large number of tables. There are tables to store transactional data such as sales orders and financial postings. There are tables to store master data, such as customer and product information. Data is spread out across these tables. Even a simple business report would require data from many transaction and master data tables. Tables need to be combined to create a meaningful data set. Also, the data in the tables is held in a raw, technical state and is usually not ready for immediate consumption by a business user. The virtual data model is responsible for combining the tables and preparing the data so it is ready for consumption by analytics.

The virtual data model is built entirely from ABAP CDS views. No data is persisted in the virtual data model, which is why is why it has the word virtual in its name. There are a huge number of views provided. It would be technically possible to generate a meaningful data set using just one view. But this would mean the view would become extremely complex having to take on all the tasks of combining tables, refining and converting data and calculating new values.

The approach taken by the SAP S/4HANA embedded analytics virtual data model is to stack the views in layers. Each layer provides a service to the next layer. The lowest layers take on the job of combining data from tables to create a data set. Master data is assembled into dimensions and transactional data is assembled into facts. But the data is still raw and so the next layer of views generates cubes of data that are ready to be queried. The highest layer of the virtual data model takes on the role of the query. This where the data is organized into shapes that are focused on each specific business scenario. Each view has a Data Category setting which defines its role, such as query or dimension.

One of the key objectives of layering is to ensure each view is as reusable as possible. For example, a dimension view that projects general product master data, would be consumed multiple times by many different cubes, such as sales and purchasing cubes. Same for a cube, which would have many query views built on top.

In addition to the Data Category, each view is defined with a View Type to further define its role. View types include:

• Consumption Views - a view (dimensions, cube, query) that is ready to be consumed directly by applications or analytical tools. (SAP standard views use the name prefix C_).
• Composite Views - Can only reads other views to form cubes or dimensions, and cannot read tables directly. Cannot be consumed directly by applications or analytical tools. SAP standard views use the name prefix I_ (this means 'Interface' view) with the view type composite setting.
• Basic Views - Consume tables directly to form dimensions, cubes. Also uses the name prefix I_ with the view type basic setting

Customers can create their own CDS views, and should use the prefix 'Z'.

Below is an example of an ABAP CDS view:

The views are code-based. The code is a mixture of SQL and SAP-specific syntax. The SQL provides the basic mechanics of selecting data from tables and views. The SAP-syntax add rich semantics that add meaning to the raw fields, such as providing a monetary value field with a currency. The SAP-specific syntax also defines associations to other related data sources to provide access to additional fields.

SAP S/4HANA embedded analytics includes tools to maintain and develop the ABAP CDS views. The tools are either using free-format code editors, or they are simpler, form-based tools where an understanding of the code syntax is not needed.