SAP BW/4HANA is an on-premise data warehouse. The main purpose of a data warehouse is to extract data from any data source, integrate the data, store the cleansed data, and provide modeling tools so that data models can be created ready for use by any analytical tool. This is exactly what SAP BW/4HANA can do.
One of the main reasons for implementing a data warehouse is to ensure that operational systems do not become data archives, with table sizes growing as data is collected. Operational systems should focus on providing current data, whereas a data warehouse focuses on data history. So we constantly move data that is no longer considered current and store it in the data warehouse, ready for when a business user needs the data for historical analysis.
SAP BW/4HANA supports data history management, but can also handle live data feeds to create a hybrid model that combines historical and live data.
With these impressive capabilities you may wonder if SAP BW/4HANA is the only data modeling solution you will need. For many customers, SAP BW/4HANA has become a core system in their IT landscape. It was introduced to the market more than 20 years ago and is a mature solution. Thousands of customers trust SAP BW/4HANA to handle their most important business data.
Customers chose SAP BW/4HANA because of its tight integration with SAP ERP systems such as SAP Business Suite (SAP ERP) and SAP S/4HANA. But in recent years, SAP have provided more data modeling solutions that may be a better fit, such as solutions that run in the public cloud.
A data warehouse is fed by data that comes from the source systems. However, this raw data cannot easily be used for targeted analysis. Therefore, the data coming from the source system is cleansed and converted to a standard format. This is called harmonization. This enterprise data can be combined with historical or with external data in the data warehouse. The knowledge gained from analyzing the data can help the organization to optimize its business strategy and the business processes.
Watch the following videos which highlight the useful data warehouse features.
There are many reasons to implement a data warehouse. For example:
If different source systems deliver values in different data types, currencies, or with different texts or attributes, harmonization can take place during the loading process
Removing duplicate data, storing only the latest information
Defining hierarchies, and aggregations
The data provisioning tools in SAP BW/4HANA provide the following:
Scheduling the data loads allows you to extract data during windows of low activity in both the source system and the reporting system.
Data load simulation and monitoring functions help you to identify and prevent errors.
DataStore Objects can be set to allow overwriting data so that load requests can be executed multiple times as data changes in the source system. This means the DataStore Object always present the latest data.
If different sources provide different key figures or attributes, the integration of data from different sources can be managed.
Launch the video to learn about the most important SAP BW/4HANA objects and their relationships.
Depending on the type of InfoProvider, the data is stored physically in the InfoProvider or is generated at run time.
Launch the video to learn about the different types of InfoProviders in SAP BW/4HANA.
Once defined, an InfoObject can be used in different contexts, and it always has the same technical format and allows the same entries:
as basic characteristic that can be drilled down in rows or columns in a report,
as attribute of another InfoObject, for example, Product Category is an attribute of Product (and such an attribute can then be added to the data set already during the data staging process, or in a BW query or report),
as part of a hierarchy, for example controlling area is be used in cost center hierarchies,
as a reference in key figures if it is a unit/currency InfoObject, especially when currency or unit conversion is calculated.
Apart from these special cases - why do you still need InfoObjects? And where do you assign them?
InfoObjects are always needed to manage master data that changes over time. This is because InfoObjects provide the history tracking capabilities that analytics tools require.
Launch the video to learn how we track history using InfoObjects.