SAP Data Strategy

What Is SAP Data Strategy?

Business and IT executives are convinced that data equates to value. Yet, to convert data into tangible business value, companies need a strong data strategy.

SAPInsider research on Data Management and Data Warehousing on Cloud found that 58% of respondents are completely or mostly satisfied with how their data strategy is meeting their organization’s data access, reporting, and intelligence requirements, while 33% are partially satisfied.

What Is SAP Data Strategy?

Business and IT executives are convinced that data equates to value. Yet, to convert data into tangible business value, companies need a strong data strategy.

SAPInsider research on Data Management and Data Warehousing on Cloud found that 58% of respondents are completely or mostly satisfied with how their data strategy is meeting their organization’s data access, reporting, and intelligence requirements, while 33% are partially satisfied.

A data strategy is a vision for how a company will collect, store, manage, share, and use data. Increasingly, enterprises recognize the importance of formulating an enterprise data strategy that spans across SAP and non-SAP data.

A good data strategy is driven by the business strategy. It translates the goals, risks, and requirements of the business into data models, processes, policies and technologies. Without a good data strategy, the organization is likely to have inefficient and poorly executed business processes, frequent data privacy and compliance issues, poor data analytics, customer dissatisfaction due to delays and errors, and significant costs due to manual operations.

Many specialist consultants can help companies with data strategy such as Pythian and cbs-Consulting.

Data Strategy Elements

There are four commonly acknowledged elements of data strategy that generate questions to consider:

1. Goals and Objectives for Data: What are the goals for data? For example, goals may be to enable enterprise analytics and smooth business processes, provide data to business users efficiently, and reduce data storage costs. Companies also have short-term goals such as consolidating data stores in one location or cleaning up master data.
2. Organizational Roles: What are the roles that manage or use the data? Data architects and engineers may build the data infrastructure, data scientists may use it for analytics, while business users may create, update, or use specific data based on their role.
3. Data Architecture: Where will data be stored and how will it be accessed? A wide variety of storage is used both on-premise and on cloud. Increasingly, companies are consolidating data on the cloud in the form of data lakes, data hubs, or data warehouses with SAP HANA or other solutions. Vendors like Dell, NetApp, NTT Data, and TIBCO offer robust solutions to store and manage data.
4. Data Management: How will data be governed, converted, transported, and archived? Data is considered a business asset; similar to a physical asset, companies develop ways to govern its use and manage it over its lifecycle. There is a proliferation of vendors offering services such as master data governance, including the Laidon Group.

In addition to the above, companies are now considering a short-term data strategy around how to migrate to SAP S/4HANA. This presentation, Data Readiness and Preparation for Your SAP S/4HANA Implementation, outlines how to develop a data foundation during and before the migration.