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Building a Logical Data Warehouse using SAP BW/4HANA Why and How?

By Vvolve

Logical Data WarehouseOne of the key building blocks of a SAP Intelligent Enterprise is analytics and decision-making using Intelligent Technologies like Machine Learning, Big Data, Data Intelligence and Predictive Analytics among others. While these technologies are often discussed as the next game-changers for enterprises, what is less discussed, but not less critical, is the underlying data management required to make these Intelligent Technologies happen.

Today, I focus on one aspect of data management the use of a Logical Data Warehouse to organize data from different sources, and how this can be implemented using SAP BW/4HANA.

What is Logical Data Warehouse (LDW)?

The term Logical Data Warehouse (LDW) was first used by Mark Beyer of Gartner who is often referred to as the Father of the Logical Data Warehouse. In his blog, Mark proposed the idea of a Logical Data Warehouse as a logical information delivery platform that includes all information in an enterprise.

In general, a LDW is an extension to the traditional data warehouse where an architectural layer sits on top of the usual data warehouse store of persisted data. The logical layer provides several mechanisms for viewing data in the warehouse store and elsewhere across an enterprise without relocating and transforming data ahead of view time.

Data virtualization is a critical part of the LDW architecture enabling queries to be federated across multiple data sources both traditional structured data sources, such as databases, data warehouses, etc., and less traditional data sources, such as Hadoop, NoSQL, Web Services, SaaS applications, and so on while still appearing as a single logical data source to the user.

What are the advantages of Logical Data warehouse?

The advantage of the logical layer is that data is fresher and the structure of delivered data is created at run time without limiting data to the pre-built structures of the data warehouse’s persisted store. Achieving these advantages has been a challenge in the past, because software, hardware, and networks simply lacked the speed, scale, and reliability required of large, complex, ad hoc instantiations. Today, multiple advances have made the logical data warehouse fully practical and feasible for most organizations to implement it.

Building a Logical Data Warehouse using SAP BW/4HANA

With help of SAP Enterprise Information Management (EIM) Smart Data Access component, Open ODS Views and Composite Providers, data virtualization can be achieved in SAP BW/4HANA.

Logical Data Warehouse

With SAP HANA Source System type, SAP BW can now fully leverage SAP HANA Smart Data Access and Smart Data Integration. This source system enables data provisioning from various data sources. A full list of data sources supported using SAP SDI can be found here. Based on specific requirements, we can further decide whether data has to be persisted in SAP BW or can be accessed virtually from its data source.

Virtualization of data access is, however, only one aspect of LDW. In most scenarios, data from different sources often don’t blend readily and need to be transformed according to business needs before it can provide meaningful insights.

By adding the SAP Agile Data Preparation (ADP) component, another SAP EIM component which comes bundled with SAP BW/4HANA, we should be able to implement a true Logical Data warehouse where all enterprise data can be accessed from one platform.

SAP SP enables users to discover, understand, cleanse, enrich and combine their data. SAP ADP uses HANA SDI to acquire data from multiple sources and create Business Rules to transform raw data and publish it HANA Tables or Calculation Views which can be further used in Open ODS Views and integrate with other data sets for getting complete information.

At vVolve, we have implemented data warehousing, business intelligence and analytics solutions for multiple industries including financial services, oil and gas, aviation, education among others. This has given us a deep knowledge base of business rules and best practices as well as extensive implementation in a wide range of IT system architecture and landscapes, which has translated into faster and more robust implementations and quicker return on investment for our clients.

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