Mapping complex logic in a variable system - with the SAP Data Warehouse Cloud

The SAP Data Warehouse Cloud completes SAP's portfolio with a solution that is optimized for both SAP HANA in-memory databases and the SAP Cloud environment (SAP Business Technology Platform). It is exactly what its name promises: a variably usable and flexibly scalable "Software as a Service" model ("Cloud") to merge data from multiple - usually heterogeneous - sources and optimize it for analysis purposes ("Data Warehouse").

In contrast to on-premise BW/4HANA technology, it does not include an application platform for hosting self-written programs. Instead, the SAP Data Warehouse Cloud relies on SQL technology to map business logic in order to exploit the full potential of an in-memory database ("code to data" paradigm). However, if you use applications that go beyond business logic and provide entire user interfaces, you should combine the DWC with the SAP Business Technology Platform.

Increased agility through flexible scalability

The deployment scenario of an SAP Data Warehouse Cloud is therefore pure data warehousing with cloud technology. But what are the advantages? First of all, the natural advantages of a cloud-based solution using software as a service: it offers flexible scalability in terms of available users, storage and even entire sub-areas (so-called "spaces"). This means that if additional requirements are to be added to the data warehouse cloud, it can be expanded directly. Payments for unused space can also be quickly canceled. Both lead to projects being implemented more quickly. The importance of investment protection decreases and agility increases.
In addition to these technology-driven advantages, there are also practical benefits: The data warehouse cloud makes it possible for specialist sites to load and manage their data themselves and enrich it with business logic - using accessible user interfaces(modeling in the "business layer"). This also makes it possible to react more quickly to new requirements, thereby increasing agility and innovation within the company.

Integration of local, unharmonized data

In addition, this approach also offers the opportunity to integrate data that previously existed completely outside of any business data governance in local Excel or other non-orchestrated sources. The SAP Data Warehouse Cloud now offers around 30 adapters for data sources(SAP Help Portal - DWC connection types). Depending on the connection type, replications or the purely virtual connection of data sources are possible.
After applying the business logic, users are not only dependent on the SAP Analytics Cloud as a BI client to consume the data. Instead, Tableau, Excel and Power BI, for example, can consume the data from the Data Warehouse Cloud directly. Using an ODBC driver, this series can also be extended to any other third-party BI clients .

Using the full bandwidth of an SQL data warehouse

If such a prototype reaches a level of maturity in terms of useful life and, above all, complexity, it may be desirable to hand the project over to IT. They can then draw on the full bandwidth of an SQL data warehouse. The range of tools in the data layer then extends from graphical views to SQL views. Graphical views provide a clear and accessible graphical editor with which SQL statements can be easily created and managed.
SQL views offer even greater functionality, allowing both simple SQL statements and the complex use of SQL scripts (table functions). This also covers a special use case, namely the operation of an SQL data warehouse (for example in a hybrid use of BW/4HANA and HANA native).

Conclusion

The SAP Data Warehouse Cloud should not be understood as BW/4HANA in the cloud. Rather, we see a flexible deployment scenario as realistic. In this scenario, the Data Warehouse Cloud enables rapid prototyping by involving business users more closely and reducing the involvement of IT. As a result, a lot of previously unharmonized data can be integrated into business data governance. Many connection types and high compatibility with BI tools contribute to usability and acceptance. Last but not least, SQL data warehousing also enables the mapping of complex logics.