Maksim Samasiuk - Fotolia

SAP data management must start with a conceptual framework

It's hard to make sense of the many SAP data management and business intelligence products -- let alone use them effectively -- without putting good data practices in place first.

There are so many approaches to SAP data management and business intelligence -- many of them offered by SAP itself -- that one can be forgiven for not grasping them all. With the roster evolving annually, some overarching framework of understanding usually has to be in place before an organization can buy third-party and SAP data management products and use them effectively in their BI applications.

The practical methods involve using either the data warehouse modeling and management application, SAP Business Warehouse (BW), or a mix of SAP and third-party tools. But data warehous­ing is really a discipline for integrating and managing data over time, according to one consultant and SAP mentor. It's also important to sift through SAP data management buzzwords and big data hype and instead elevate plain-English words like honesty, integrity and transparency as signposts for quality BI and analytics. Honesty, for example, means telling the truth about the accuracy of data so users know how reliable it is for prediction and other analysis.

But no SAP data management strategy is complete without a firm grasp of critical technologies, including Hadoop, today's most talked-about technology for big data -- and the foundation of many SAP data management and BI projects. It's also important to understand how well SAP products such as HANA and Data Services integrate with Hadoop's various parts.

Nowadays, analyt­ics and visualization software are the mechanisms through which BI users interact with data. It's difficult to understand these user-interface tools without knowing something about the data transforma­tion that products including BW use to first filter and organize the data, both important steps in SAP data management.

Separating the layers can invite trouble by masking data-integrity issues, which argues for a seamless, integrated approach that gives users the power to fix problems on the spot. In an age increasingly characterized by self-service, SAP data management may call for a more integrated technology stack than SAP is ready to provide.

Next Steps

Read Ethan Jewett's SAP BI handbook

Understand SAP Data Services

Learn about SAP data warehouses

This was last published in February 2016

Dig Deeper on Business Objects and SAP business intelligence

PRO+

Content

Find more PRO+ content and other member only offers, here.

Join the conversation

2 comments

Send me notifications when other members comment.

By submitting you agree to receive email from TechTarget and its partners. If you reside outside of the United States, you consent to having your personal data transferred to and processed in the United States. Privacy

Please create a username to comment.

What are the main challenges of SAP data management?
Cancel
To my mind this all hinges on what a person really thinks data management means. Business Intelligence, I think is well understood, but unless you are responsible for the quality of the data and the maintenance of it, wherever it comes from; Data Management in SAP is more or less a different topic from business intelligence altogether
Cancel

-ADS BY GOOGLE

SearchManufacturingERP

SearchOracle

SearchDataManagement

SearchAWS

SearchBusinessAnalytics

SearchCRM

SearchContentManagement

SearchFinancialApplications

Close