SAP Information Steward(IS) Insights
Welcome back 🙂
Today, in this blog post, we are going to learn W2h-what, why and how
- What is IS(Introduction section describes),
- Why to use IS(components section describes),
- How to use(scenario section describes)
and explained how to use information steward for profiling and generate scorecards in 8 steps.
Many of us struggle to start with information steward, logically, who is expertise in SAP BODS, can easily pull up insights of IS(Infomation Steward), even though if you have no experience in DS(Data services) you can get on IS easy.
SAP Information Steward, which is a component of SAP BusinessObjects, is an environment to discover, assess, define, monitor and improve the enterprise’s data quality. This is achieved by the following main features that SAP Information Steward offers:
Information steward components– In a simpler way, we can call as architecture too:
- DATA INSIGHT – The Data Insight module is used to get a high-level data quality view on a particular data source
- METADATA MANAGEMENT – The Metadata Management module offers a central repository where you can store your metadata information from across your different enterprise systems.
- METAPEDIA – As its name already reveals, the Metapedia module is a central repository (“encyclopedia”) where you can create a business glossary of words, phrases, and business concepts and relate them to metadata objects from the Metadata Management or Data Insight modules.
- CLEANSING PACKAGE BUILDER – A cleansing package is a concept part of Data Services in which you add data that needs to be parsed and standardized by rules which you have defined. The Cleansing Package Builder module of Information Steward provides you a graphical user interface to create a cleansing package from scratch based on sample data or refine an existing cleansing package (custom built or SAP-supplied) to meet your enterprise-specific requirements.
- MATCH REVIEW – The results of a data transformation (cleanse, standardize, duplicate matching of data) in Data Services are stored in a staging table.
Even if the original purpose of Information Steward is to create Validation Rules that represent policies or requirements on data quality, you can also use Information Steward as a data reporting tool.
Data profiling, scorecards, etc. This feature enhances the ability of the Data Steward to communicate with stakeholders, an executive sponsor for example, and helps non-stewards understand the governance event and direct appropriate action.
Today, I am going to simplify the IS to below scenario.
Let us see how:
I am going for a simple data profiling on a column level and generate scorecards for the same.
Find out the Product Id is not null values from the Product table, the percentage report calculates how the sources match up against the rules.
1.Creating a project:
2.Defining a rule as below:
3. Give details:
4. create a rule: define conditions
5.Test rule: with runtime values
6. Run the test rule: to see results
7.Results: over different rules
Few keynotes here :
- If you can define in a validation rule that you bind to the view you have created that expression is TRUE if the old value is equal to the new value and the expression is FALSE if the old value is different from the new value; then all “changes” are treated as Failed Records as they violate your rule “Field Values are not allowed to be changed”.
- After binding the rule to your view, you can execute a Rule Task on your view (Calculate Score) and you will be able to see results in the IS Workspace area on the Rule Result tab and on the Rules panel.
- If you want to create a full DQ Scorecard, you will need to do a DQ Scorecard Setup first defining Key Data Domain, Quality Dimensions, Rules to be used and Bindings to be used.
Note: A DQ Scorecard calculation (based on the Rule Results calculated by the Rule Task Execution (Calculate Score)) is executed or scheduled via Scorecard Calculation Utility in the CMC.
In the next blog posts, we can discuss more on processings.
Find my continuation blog on latest updates:
That’s all about this blog post.