Paraphrasing Data Management and Data Warehousing

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Discover SAP Data Intelligence
  • Describe SAP HANA Cloud Modeling
  • Identify the capabilities and use cases of SAP Data Warehouse Cloud

SAP Data Intelligence

Data To Value: Data Management & Data Warehousing

In between the Data To Value process is the Data Management and Data Warehousing. With this, you can prepare your data to utilize a value out of it in the last phase. You integrate, manage, model, process and share your business data with the capabilities built in SAP Data Intelligence, SAP Data Warehouse Cloud and more.

SAP Data Intelligence: Capabilities

SAP Data Intelligence Cloud is a comprehensive data management solution. As the data orchestration layer of SAP Business Technology Platform, it transforms distributed data sprawls into vital data insights, supporting innovation and business growth. It gives you the ability to do the following:

Data Integration

Connect and integrate everything, structured, unstructured or streaming data to further work or process this data in use cases afterwards.

Data Processing

Extract meaning from data, orchestrating any mix of engines to have a good structure and solid data set.

Data Catalog

Discover, classify, profile, understand and prepare all your enterprise data assets before consuming and using them in your analytics and enterprise planning.

SAP Data Intelligence: Overview

More information about SAP Data Intelligence:

SAP HANA Cloud Modeling

Pushing Down Data Processing to Database

Traditional databases provided storage capabilities and offered limited (if any) data processing capabilities. This means that applications would read raw data from the database and, using application code such as ABAP or JAVA, develop complex data processing code to run on the application server.

SAP HANA Cloud database provides sophisticated, multi-tier data storage and, also, advanced data processing capabilities so that instead of an application requesting raw data from the database, it can request information. Data processing is now pushed down from the application layer to the in-memory database of SAP HANA Cloud. This means, not only is data processing faster, applications are leaner as they do not have to handle data processing logic. Leaner applications means more agility.

Advanced multi-models with SAP HANA Cloud

Calculation views are defined on top of tables to provide the data processing layer. Calculation views are usually stacked so that the lower calculation views provide opportunities for reuse by defining only the basic data layer. On top of those are more calculation views that add further calculations and semantics until they are ready for consumption by clients. Calculation views do not persist data but calculate results on-the-fly based on live data in source tables. Source tables can be local tables in the SAP HANA Cloud database or remote tables in any database.

With SAP HANA Cloud, you can combine any type of data: text, geometries, IoT data, and so on to create multi-models that power high-performance, advanced analytics.

Learn more about modeling in SAP HANA Cloud in our learning journey:

Data Warehouse Cloud

The concept of data warehousing was initially defined in the late 1980s. A popular definition originates from Bill Inmon, who described it as "a subject-oriented, integrated, time-variant, and non-volatile collection of data in support of management's decision making process". These four key properties mean the following:

  1. Data is collected about entities that have an impact on the future success of the organization (for example, vendor, product, customer) and their relationships (for example, key figures representing processes like purchasing, production or sales).
  2. Data is integrated from many different sources, and as a result, they are available in a consolidated way in a separate system.
  3. Data is collected for different points of time to enable time series analysis and comparisons. So, the time dimension has a crucial significance.
  4. Data is not changed anymore. It is stable and permanent once it is transferred to the data warehouse.

SAP has multiple data warehousing solutions. To close the gap towards a full public cloud offering, SAP launched SAP Data Warehouse Cloud.

It is important for SAP to keep customers' investment from existing on-premise investments: First of all, customers can leverage so-called hybrid scenarios based on integration with existing on-premise landscapes. In addition, SAP introduced the SAP BW Bridge in SAP Data Warehouse Cloud that provides a path to the public cloud for on-premise landscapes. Recommended reading:

SAP Data Warehouse Cloud: Capabilities

More information about SAP Data Warehouse Cloud

Learn more about SAP Data Warehouse Cloud on the official product page:

Get product assistance from the official help documentation:

Key Takeaways Of This Lesson

Integrate, Prepare, catalog, manage and model your data through data management and data warehousing capabilities from SAP BTP and start utilizing offerings like SAP Data Intelligence, SAP Data Warehouse Cloud, Modelling with SAP HANA Cloud and SAP Master Data Governance Cloud.

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