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The quality of enterprise information is always critical and has an enormous top-line and bottom-line impact on the overall business performance of a company. For example, in an SAP interview, Ericsson reported that at a certain point in the past around 40% of their orders got stuck along the process chain due to data inconsistencies. Applying an MDM strategy was the remedy. Very Custom KPI measurement solution for BPM also state the effectiveness of implementing data governance processes at the customer site. 

These are only a few examples indicating that it is prime time to provide our ISV partners with a comprehensive picture of what Enterprise Information Management is all about, and which contribution they could make to address specific customer pain points in the broad area of enterprise information.  

What is the aim of the new chapter on Enterprise Information Management?

The new chapter 6 is aimed at providing ISVs with comprehensive information about the concept and functional coverage of Enterprise Information Management and the associated SAP solution portfolio. Recommendations help ISVs when it comes to setting up specific solutions on top of the described EIM portfolio.

In general, we see Enterprise Information Management as the overall capability of an enterprise to gather, cleanse, integrate, search and govern all relevant business information, be it, for example, analytical data, master data information or unstructured data.

Enterprise Information Management basically addresses the manifold data consistency issues that can occur in and across enterprises while Business Intelligence basically covers the capabilities of presenting the data from a front-end perspective. BI will be treated in another new chapter of the Guidelines for Best-Built Applications.

Accordingly the key areas covered in the new EIM chapter are:

  1. Data Integration and Data Quality
    Covering integration and QA aspects such as ETL, data profiling, monitoring, cleansing, and matching/merging
  2. Master Data Management and Governance
    Covering MDM scenarios at global scale from a technology and solutions perspective
  3. Enterprise Search
    Covering the collection of structured and unstructured data from different sources into a single work environment
  4. Enterprise Data Warehousing
    Covering the aspects of data warehousing and metadata management 
  5. Information Lifecycle Management
    Covering the lifecycle topics such as archiving and retention management
  6. Enterprise Content Management
    Covering content management aspects for unstructured and structured data

Each area contains a basic description and provides links to related deep-dive information. You may use the specific recommendations as a guideline for setting up ISV projects on top of a given EIM solution.

For more information about Enterprise Information Management and the associated capabilities, see the specific EIM sites on SDN and sap.com.
Also available on SDN:

We hope that the information is useful for your projects.

Best regards,

Markus

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2 Comments

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    1. Markus Ganser Post author
      Hi Kenneth,

      Thanks for your comment. EIM includes both cleansing activities for data that aleady exist in a given landscape (e.g., in master data consolidation and harmonization) and central creation of consolidated data to ensure data consistency upfront (i.e., in central master data management/governance. So I’d say both terms are needed.

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