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Introduction to Information Steward

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Ryan Muldowney

on 30 June 2014

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Transcript of Introduction to Information Steward

Introduction to Information Steward
SAP Information Steward
A powerful data quality and analysis tool

Adds functionality that has long been missing from the SAP BI Platform
Data Insight
What can I do with Data Insight?
Data profiling
Data validation rule creation
Create data quality scorecards
Get data cleansing recommendations
What can I do with Metapedia?
Create a glossary of business terms related to your data
Organize your terms hierarchically into categories
Associate terms with one or more metadata objects
Designate relationships between terms
Import term information from an Excel spreadsheet
Cleansing Package Builder
What can I do with Cleansing Package Builder?
Use your data validation rules to create a data cleansing package
Publish a completed package for use within a Data Services "Data Cleanse" transform
Improve existing cleansing packages based on run results
Metadata Management
What can I do with Metadata Management?
Search across metadata from many different sources
View Data Lineage and Impact
Add annotations to any metadata object
Create custom relationships between objects
Integrator Sources
Information Steward supports many types of Integrator Sources for Metadata Management.

Relational Databases
BI Platform
Data Services
Data Modeling tools (ERWin, Informatica)
Data Federator
BI Platform Integration
Leverages BI platform for user security, scheduling, and administration

Depends on Data Services for job server and other services

Can also be a standalone deployment using IPS
Compatible with the 4.x Release
Information Steward 4.1
BusinessObjects 4.0 + Data Services 4.1


Information Steward 4.2
BusinessObjects 4.1 + Data Services 4.2

SAP Note 1740516
for more information on compatibility!
Key Features
Data Profiling
Metadata Management
Data Lineage and Impact
Data Validation
Data Cleansing
Business Term Glossary
Data Dictionary
... and much more!
Ryan Muldowney
Solutions Architect
Altek Solutions, Inc.

Data Profiling
Connect Information Steward to your databases and run profile tasks to see:
Minimum, maximum, and average values
String length (min, max, average, median)
Completeness (Percent of nulls, blanks, zeros)

Data Validation Rules
Create validation rules based on your data profiling results

Use a wizard or a simple formula syntax similar to WebIntelligence

Rules are assigned quality scores which can be used in data quality scorecards
Fun fact for Data Services users!
Save yourself hours of frustration!

You must set the option
Calculate column mapping while saving data flow
to ensure that the Metadata Management integrator extracts impact and lineage relationships.

Set this option in
Tools > Options > Designer > General
Data Services Designer

Approval Process
Each new term has to go through the approval workflow.

Approvers are selected based on security rights.

Basic workflow:
Author creates term
Author saves term and submits for approval
Approver reviews and approve term
Term is associated to one or more metadata objects
Full transcript