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SAP BusinessObjects Information Steward

Michael Briles
Senior Solution Manager
Enterprise Information Management
SAP Labs LLC

June, 2011
Agenda



Challenges with Data Quality and Collaboration



Product Vision & Value Proposition



Solution Today – Key Capabilities



Demonstration



Q&A

© 2011 SAP AG. All rights reserved.

2
Challenges with Data Quality and Collaboration
Business Challenges with Data Quality
and Data Integration Projects Today
No environment for
business users to
collaborate with IT
regarding data issues

Not sure what the business
definition is

No consistent repeatable
way to measure and score
data quality

No clear strategy and
discipline for improving data
quality

IT

No ability to analyze data
dependencies across
systems

Lack of visibility to where
the numbers or data is
coming from

Minimal reuse of data
assets; lots of data
duplication

© 2011 SAP AG. All rights reserved.

and many
more…

BUSINESS
USER

4
Introducing
SAP BusinessObjects Information Steward

Product Vision & Value Proposition
Business Analytics Solutions from SAP
Most complete offering
Analytic Applications
By Industry

Enterprise Performance
Management
Strategy
Management

Planning,
Budgeting, and
Forecasting

Profitability and
Cost Management

By LoB

Financial Services
Public Sector and Healthcare
Manufacturing
Consumer Products
Retail and Telco
Utilities and more….

Service, Sales, and Marketing
Procurement
Supply Chain
Finance
Sustainability
IT, HR, and more…

Financial
Consolidation

Governance, Risk,
and Compliance
Enterprise GRC

Access Risk
Management

Global Trade
Services

Continuous
Transaction
Monitoring

Disclosure
Management

Enterprise Information
Management

Business Intelligence
Reporting and
Analysis

Dashboards and
Visualization

Data
Services

Master Data
Management

Data Exploration

Mobile

Event
Processing

Content
Management

Information
Governance

BI Platform

Data Warehousing
Enterprise Data
Warehousing

© 2011 SAP AG. All rights reserved.

High-performance
Analytic Solutions

Data Mart
Solutions

6
SAP BusinessObjects Information Steward
Product Overview

Empower data stewards with a single environment to discover, assess,
define, monitor, and improve the quality of their enterprise data asset
Discover

SAP BusinessObjects
Information Steward

Define
Define business
terms, validation
rules, cleansing
rules, models

Discover & understand
enterprise data
(Data profiling,
Metadata management)

Define data
ownership: Assign

Catalog data
assets

data ownership,
accountability, and
roles

Monitor & Remediate
Monitor
data quality
© 2011 SAP AG. All rights reserved.

Surface data quality
score in business
user applications

Workflows to
resolve data
quality issues
7
SAP BusinessObjects Information Steward
Single solution, multiple benefits
Collaborative environment for your IT and business users

EMPOWER

SAP BusinessObjects
Information Steward

GOVERN

IMPROVE

© 2011 SAP AG. All rights reserved.

8
Target Personas for Information Steward

Data Analyst/IT

Data Steward




Reviews data quality
scorecard



Defines rules



Creates a project



Reviews data quality
dashboards



Creates a connection



Defines user security



Configures Information
Stewards application



Schedules a task

Analyzes Scorecard


Defines a scorecard



Analyzes profiling result



© 2011 SAP AG. All rights reserved.

IT Administrator

Adds sources to the project

9
SAP BusinessObjects Information Steward
Value propositions
Improve information governance and quality

EMPOWER
GOVERN

IMPROVE

© 2011 SAP AG. All rights reserved.

Empower Business Users
Bridge gap between business and IT
with collaborative solution for driving
information management initiatives
Govern Enterprise Information
Enable effective data governance with
the industry’s first combined data
profiling, metadata management, and
data quality monitoring solution
Improve Information Transparency
Give instant visibility into data quality
levels and origins with end-to-end
impact analysis and data lineage
10
Empower Business Users
What’s new with SAP BusinessObjects Information Steward
No other competitor offers a single business user-oriented solution for
metadata management, data profiling and data quality monitoring

EMPOWER




Share information regarding governance and data quality
metrics while also tracking progress toward quality goals



View data quality reports via dashboards and scorecards, or
via sophisticated inquiries into data origins and lineage



Enable business users to visualize how data quality is
impacting business



© 2011 SAP AG. All rights reserved.

View how information measures up against information
governance rules and standards

Increase efficiency and reduce costs with one solution for data
profiling, metadata management, and data quality monitoring

11
Govern Enterprise Information
What’s new with SAP BusinessObjects Information Steward
Good data governance depends on creating consistent rules and guidelines
about who can access, change, add, share, or integrate enterprise information

GOVERN




Help pinpoint error hot spots, which often indicate areas in
which governance controls must be refined or adjusted



Trace data lineage all the way from a report down to a source,
gaining a better understanding of your complete business
intelligence environment



© 2011 SAP AG. All rights reserved.

Define data ownership in accordance with your organization’s
needs, roles, and accountability principles

Create business term glossary with “metapedia”. Integrates
and consolidates metadata from many sources, linking business
terms with data elements so business people can better
understand data definitions

12
Improve Information Transparency
What’s new with SAP BusinessObjects Information Steward
Gain reliable insight in your Enterprise information quality and
integrated transparency on bad data root cause and usage

IMPROVE


Comprehensive visibility into data quality at all levels of the
information management landscape



Scorecard visualizations of data quality from various
perspectives and levels


High-level data quality scorecards



Validation rules oriented dashboard



Table/column data quality dashboard





© 2011 SAP AG. All rights reserved.

Analyze root cause with drill down capability from scorecards
and dashboards to rules, data profile, data and business terms
Impact analysis that allow you to assess the merits of changes
in your data structures and sources, resulting in reduced risk and
improved data quality
13
Available Today
SAP BusinessObjects Information Steward 4.0

Key Capabilities
How can Business and IT Users Leverage
SAP BusinessObjects Information Steward?
Apply “balanced scorecard” towards data quality performance
Measure and track data quality performance against metrics
Anticipate and spot data quality weakness

Data Profiling

Analyze if data matches business definitions and expectations
Validate data completeness, sparseness, redundancy, pattern distribution
Analyze cross system data dependencies using business views

Validation
Rules

Work with IT to define data validation rules
Apply validation rules against sources to continuous monitor data quality
Reuse validation rules in data migration and integration

Metapedia

Work with business users to define and agree on business terms
Link business terms to data elements to assist business users understand
data definitions

Metadata
management

SAP BusinessObjects Information Steward

Data Quality
Scorecard

Trace data lineage from BI reports to data sources
Assess impact of data quality or changes
Reuse data assets that is available

© 2011 SAP AG. All rights reserved.

15
Key Software Components of
SAP BusinessObjects Information Steward

Data Profiling
DQ
Monitoring

New functionality
added to
metadata
management

© 2011 SAP AG. All rights reserved.

Metadata
Analysis

Cleansing
Rules

Existing SAP
BusinessObjects
Metadata
Management
capabilities

Part of SAP
BusinessObjects
Data Services
and DQM
functionality
surfaced on IS

Business
Term
Taxonomy

Existing SAP
BusinessObjects
Metadata
Management
capabilities

16
Key Software Components of
SAP BusinessObjects Information Steward

Data Profiling
DQ
Monitoring

New functionality
added to
metadata
management

© 2011 SAP AG. All rights reserved.

Metadata
Analysis

Cleansing
Rules

Existing SAP
BusinessObjects
Metadata
Management
capabilities

Part of SAP
BusinessObjects
Data Services
and DQM
functionality
surfaced on IS

Business
Term
Taxonomy

Existing SAP
BusinessObjects
Metadata
Management
capabilities

17
Use Cases for Data Insight
Data profiling and data quality monitoring
Key Drivers
Improve information trustworthiness
 Continuously improve data quality
 Provide visibility into quality of data

Reduce risks for propagating bad data
 Find data anomalies and remediate data issues

Easily understand data and its relationships
 Create data mapping rules for data integration
 Define data cleaning and validation rules

Show ROI for data quality initiatives
 Quantify impact of poor data on business
 Speed up data integration projects with better DQ
information
 Validate governance controls are effective on data
quality (for example: investment in MDM)

© 2011 SAP AG. All rights reserved.

18
Visualization of Data Quality
High-level balanced data quality scorecard

Drill into scorecard
details
Scorecard to
measure DQ from
a Data Steward’s
perspective

Key Quality
Dimensions (KPI
for data)

Latest quality
score

Data quality
score metrics

© 2011 SAP AG. All rights reserved.

Quality trend
19
Visualization of Data Quality
Validation rules oriented dashboard
Select Key data domain, Quality dimension,
Rule, and Rules binding to analyze data
quality based on any combination of these
attributes

View
validation rule
definition

Switch to Workspace to
profile data and create
validation rules

Analyze sample
failed data

Analyze impact
of failed data

© 2011 SAP AG. All rights reserved.

20
Visualization of Data Quality
Data quality scores and trend at table, column, and rule level

Table level score
measures number of
rows that passed all
rules
Column level score
measures number of
rows that passed all
rules for this column
Rules level score
measures rows that
passed this rule

Detailed statistics of
number of failed and
total rows
© 2011 SAP AG. All rights reserved.

Data quality trend
over different time
ranges

Sample failed rows
for analysis of the last
rule execution
21
Interactively Identify Data Quality Problems
Multi-column data profiling
Address profiling
measure % valid
addresses, % invalid
addresses, % can
be corrected

© 2011 SAP AG. All rights reserved.

Dependency profiling
measures the degree
to which two sets of
values are related on
one another

Redundancy
profiling measures
the degree of data
overlap between two
data sets

Uniqueness profiling
measures the degree
of uniqueness of one
or more columns of
a table

22
Interactively Identify Data Quality Problems
Table/column data profiling
Summary indicators for low
cardinality, uniqueness and
sparseness

Tools for analyzing
sample profiling
result rows
© 2011 SAP AG. All rights reserved.

View column properties, value,
string, completeness, and
distribution profiling statistics

Drill from profiling
result to into value
distribution

Drill from value
distribution to sample
profiling result rows
23
Interactively Identify Data Quality Problems
Data redundancy
There can be multiple
advanced profiling tests
(tasks) for a table

Visualize
data
relationship

Drill into
sample data

© 2011 SAP AG. All rights reserved.

24
Key Software Components of
SAP BusinessObjects Information Steward

Data Profiling
DQ
Monitoring

New functionality
added to
metadata
management

© 2011 SAP AG. All rights reserved.

Metadata
Analysis

Cleansing
Rules

Existing SAP
BusinessObjects
Metadata
Management
capabilities

Part of SAP
BusinessObjects
Data Services
and DQM
functionality
surfaced on IS

Business
Term
Taxonomy

Existing SAP
BusinessObjects
Metadata
Management
capabilities

25
Use Cases for Metadata Management
BI-centric metadata management

“Where did this number come
from?”

Key Drivers
 Understand

entire BI
environment

 Trace

data lineage from a
report to sources

 Change

impact analysis for
source to reports and users

 Manage

metadata from various
data sources, data integration
technologies, and BI systems

 Lower
“How will this change in the source
impact my BI reports?”

© 2011 SAP AG. All rights reserved.

TCO by tracking usage
and promote reuse of data and
reports

 Improve

decision making and
regulatory compliance
26
SAP BusinessObjects Metadata Management
Overview

Consolidate, Integrate, Audit, and Trust your Metadata

BI Systems

Metadata
Integrators

Metadata
Repository

 Consolidates
Analysis

Central
Repository

metadata
from various BI related
sources

 Integrates

Databases
Consolidate

Audit

metadata in a
central metadata repository

 Relates
ETL
Integrate

Modeling
Tools

■
■
■
■
■

Custom Attributes
Annotations, Metapedia

 Supplements

metadata
with custom attributes,
annotations

 Creates
Business
Metadata

© 2011 SAP AG. All rights reserved.

Impact
Usage
Lineage
Trends
Search

metadata to enable
auditing, usage, change
impact, and data lineage
analysis

Universe
Creation

universe from
relational objects

27
Metadata Integrators
Metadata Management Integration to:

BI Systems

Metadata Integrators bundled with
Information Steward

Databases

Metadata
Integrators

SAP Software: BI Platform, Data
Services, Data Federator and SAP
NEtWeaver BW
NON SAP Software: CWMXML (CWM),
RDBMS: MSSQL Server, DB2, Teradata
and JDBC Sources

Other Metadata Integrators
available *

ETL

Modeling
Tools

Altova
Borland
CA
COBOL
Embarcadero
EMC
Gentleware
Silverun
Knightbridge (HP)
IBM
Informatica
Micsosoft

MicroStrategy
NoMagic
OMG
Oracle
SELECT
SPARX Systems
SUN
Sybase
Teradata
Tigris
Visible Systems Corp
W3C

* Other metadata integrators available via Meta Integration Technology, Inc. (MITI)
© 2011 SAP AG. All rights reserved.

28
Key Software Components of
SAP BusinessObjects Information Steward

Data Profiling
DQ
Monitoring

New functionality
added to
metadata
management

© 2011 SAP AG. All rights reserved.

Metadata
Analysis

Cleansing
Rules

Existing SAP
BusinessObjects
Metadata
Management
capabilities

Part of SAP
BusinessObjects
Data Services
and DQM
functionality
surfaced on IS

Business
Term
Taxonomy

Existing SAP
BusinessObjects
Metadata
Management
capabilities

29
Cleansing Package Builder (CPB)

Key Drivers
 Empowers data
stewards/domain
experts to
develop custom
data cleansing
solutions for any
data domain
 Cleansing
Package Builder
is available within
Information
Steward

© 2011 SAP AG. All rights reserved.

30
Why Do We Need Cleansing Package Builder?
Unique data for ‘non-party’ data elements

Parsed Output
Product Category

Glove

Size

Large

Material

Synthetic Leather

Trademark

Pro-Fit 2.3 Series

Cuff Style

Elastic Velcro

Palm Type

Ultra-Grip

Color

Black

Vendor

Mechanix Wear

Standard Description

Glove – Synthetic Leather, Black, size:
Large, Cuff Style: Elastic Velcro, UltraGrip, Mechanix Wear

Input Data
Glove ultra grip profit 2.3 large black
synthetic leather elastic with Velcro
Mechanix Wear

© 2011 SAP AG. All rights reserved.

31
Key Software Components of
SAP BusinessObjects Information Steward

Data Profiling
DQ
Monitoring

New functionality
added to
metadata
management

© 2011 SAP AG. All rights reserved.

Metadata
Analysis

Cleansing
Rules

Existing SAP
BusinessObjects
Metadata
Management
capabilities

Part of SAP
BusinessObjects
Data Services
and DQM
functionality
surfaced on IS

Business
Term
Taxonomy

Existing SAP
BusinessObjects
Metadata
Management
capabilities

32
Use Cases for Metapedia
Business term encyclopedia

Key Drivers




Enable business users to understand data
attributes used in
BI environments with business user
oriented descriptions



Central location for defining
standard business vocabulary (words,
phrases, or business concepts)



© 2011 SAP AG. All rights reserved.

Promote proactive data governance with
common understanding and agreement
on business concepts

Organize business terms into categories
that align with business subject matter or
lines of business

33
Why SAP?
The best choice for EIM

One place for data stewards and business
analysts to collaborate and govern their
data asset
First and only integrated solution - metadata
management, business glossary, data quality
assessment, data quality monitoring, and
cleansing package builder solution
Various perspectives to understand and
analyze trustworthiness of data

Easy and secure access to a rich set of
metadata data sources

© 2011 SAP AG. All rights reserved.

35
Information Steward Services - Migration
For the migration from Data Insight to Information Steward we have created
three migration packages at fixed fee & fixed scope.*
Small Complexity

Medium Complexity

High Complexity

• Number of sources < 3
• Number of column
queries <10
• Referential Integrity Test
= 10
• Custom queries = 0

• Number of sources < 10
• Number of column
queries <100
• Referential Integrity Test
= 10
• Custom queries < 30
• Various complexity

• Number of sources <25
• Number of column
queries <300
• Referential Integrity Test
= 10
• Custom queries < 70
• Various complexity

15 days

50 days

120 days

* Pricing being finalized. Meta Data Management upgrade not included.

© 2011 SAP AG. All rights reserved.

36
Information Steward Services – Quick Start

Our Quick Start Package is design for green-field implementations to assist our
customers to quickly take advantage of IS 4.0; fixed fee and fixed scope.*
Quick Start Package
• Install IS environment
• Knowledge transfer
• Setup and execute data profiling jobs
• One data domain from two source systems
• Configure CPB dictionaries based on the profiles
• Design DQ and other dashboards

10 days

* Pricing being finalized.

© 2011 SAP AG. All rights reserved.

37
Further Information


SAP Community Network
Business Analytics community
http://www.sdn.sap.com/irj/boc

EIM page
http://www.sdn.sap.com/irj/boc/nw-informationmanagement
EIM discussion forums
http://forums.sdn.sap.com/index.jspa#4



Social Media
Twitter
http://twitter.com/sapmdmgroup
http://twitter.com/sapcommnet
Facebook
https://www.facebook.com/sapcommunitynetwork



Upcoming Webinars
Business Analytics Webinar Series
http://www.sdn.sap.com/irj/scn/business-analytics-webinars

© 2011 SAP AG. All rights reserved.

38
Thank You!
Contact information:

Michael J Briles
Senior Solution Manager – Enterprise Information Management
E-mail: michael.briles@sap.com

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Sap information steward

  • 1. SAP BusinessObjects Information Steward Michael Briles Senior Solution Manager Enterprise Information Management SAP Labs LLC June, 2011
  • 2. Agenda  Challenges with Data Quality and Collaboration  Product Vision & Value Proposition  Solution Today – Key Capabilities  Demonstration  Q&A © 2011 SAP AG. All rights reserved. 2
  • 3. Challenges with Data Quality and Collaboration
  • 4. Business Challenges with Data Quality and Data Integration Projects Today No environment for business users to collaborate with IT regarding data issues Not sure what the business definition is No consistent repeatable way to measure and score data quality No clear strategy and discipline for improving data quality IT No ability to analyze data dependencies across systems Lack of visibility to where the numbers or data is coming from Minimal reuse of data assets; lots of data duplication © 2011 SAP AG. All rights reserved. and many more… BUSINESS USER 4
  • 5. Introducing SAP BusinessObjects Information Steward Product Vision & Value Proposition
  • 6. Business Analytics Solutions from SAP Most complete offering Analytic Applications By Industry Enterprise Performance Management Strategy Management Planning, Budgeting, and Forecasting Profitability and Cost Management By LoB Financial Services Public Sector and Healthcare Manufacturing Consumer Products Retail and Telco Utilities and more…. Service, Sales, and Marketing Procurement Supply Chain Finance Sustainability IT, HR, and more… Financial Consolidation Governance, Risk, and Compliance Enterprise GRC Access Risk Management Global Trade Services Continuous Transaction Monitoring Disclosure Management Enterprise Information Management Business Intelligence Reporting and Analysis Dashboards and Visualization Data Services Master Data Management Data Exploration Mobile Event Processing Content Management Information Governance BI Platform Data Warehousing Enterprise Data Warehousing © 2011 SAP AG. All rights reserved. High-performance Analytic Solutions Data Mart Solutions 6
  • 7. SAP BusinessObjects Information Steward Product Overview Empower data stewards with a single environment to discover, assess, define, monitor, and improve the quality of their enterprise data asset Discover SAP BusinessObjects Information Steward Define Define business terms, validation rules, cleansing rules, models Discover & understand enterprise data (Data profiling, Metadata management) Define data ownership: Assign Catalog data assets data ownership, accountability, and roles Monitor & Remediate Monitor data quality © 2011 SAP AG. All rights reserved. Surface data quality score in business user applications Workflows to resolve data quality issues 7
  • 8. SAP BusinessObjects Information Steward Single solution, multiple benefits Collaborative environment for your IT and business users EMPOWER SAP BusinessObjects Information Steward GOVERN IMPROVE © 2011 SAP AG. All rights reserved. 8
  • 9. Target Personas for Information Steward Data Analyst/IT Data Steward   Reviews data quality scorecard  Defines rules  Creates a project  Reviews data quality dashboards  Creates a connection  Defines user security  Configures Information Stewards application  Schedules a task Analyzes Scorecard  Defines a scorecard  Analyzes profiling result  © 2011 SAP AG. All rights reserved. IT Administrator Adds sources to the project 9
  • 10. SAP BusinessObjects Information Steward Value propositions Improve information governance and quality EMPOWER GOVERN IMPROVE © 2011 SAP AG. All rights reserved. Empower Business Users Bridge gap between business and IT with collaborative solution for driving information management initiatives Govern Enterprise Information Enable effective data governance with the industry’s first combined data profiling, metadata management, and data quality monitoring solution Improve Information Transparency Give instant visibility into data quality levels and origins with end-to-end impact analysis and data lineage 10
  • 11. Empower Business Users What’s new with SAP BusinessObjects Information Steward No other competitor offers a single business user-oriented solution for metadata management, data profiling and data quality monitoring EMPOWER   Share information regarding governance and data quality metrics while also tracking progress toward quality goals  View data quality reports via dashboards and scorecards, or via sophisticated inquiries into data origins and lineage  Enable business users to visualize how data quality is impacting business  © 2011 SAP AG. All rights reserved. View how information measures up against information governance rules and standards Increase efficiency and reduce costs with one solution for data profiling, metadata management, and data quality monitoring 11
  • 12. Govern Enterprise Information What’s new with SAP BusinessObjects Information Steward Good data governance depends on creating consistent rules and guidelines about who can access, change, add, share, or integrate enterprise information GOVERN   Help pinpoint error hot spots, which often indicate areas in which governance controls must be refined or adjusted  Trace data lineage all the way from a report down to a source, gaining a better understanding of your complete business intelligence environment  © 2011 SAP AG. All rights reserved. Define data ownership in accordance with your organization’s needs, roles, and accountability principles Create business term glossary with “metapedia”. Integrates and consolidates metadata from many sources, linking business terms with data elements so business people can better understand data definitions 12
  • 13. Improve Information Transparency What’s new with SAP BusinessObjects Information Steward Gain reliable insight in your Enterprise information quality and integrated transparency on bad data root cause and usage IMPROVE  Comprehensive visibility into data quality at all levels of the information management landscape  Scorecard visualizations of data quality from various perspectives and levels  High-level data quality scorecards  Validation rules oriented dashboard  Table/column data quality dashboard   © 2011 SAP AG. All rights reserved. Analyze root cause with drill down capability from scorecards and dashboards to rules, data profile, data and business terms Impact analysis that allow you to assess the merits of changes in your data structures and sources, resulting in reduced risk and improved data quality 13
  • 14. Available Today SAP BusinessObjects Information Steward 4.0 Key Capabilities
  • 15. How can Business and IT Users Leverage SAP BusinessObjects Information Steward? Apply “balanced scorecard” towards data quality performance Measure and track data quality performance against metrics Anticipate and spot data quality weakness Data Profiling Analyze if data matches business definitions and expectations Validate data completeness, sparseness, redundancy, pattern distribution Analyze cross system data dependencies using business views Validation Rules Work with IT to define data validation rules Apply validation rules against sources to continuous monitor data quality Reuse validation rules in data migration and integration Metapedia Work with business users to define and agree on business terms Link business terms to data elements to assist business users understand data definitions Metadata management SAP BusinessObjects Information Steward Data Quality Scorecard Trace data lineage from BI reports to data sources Assess impact of data quality or changes Reuse data assets that is available © 2011 SAP AG. All rights reserved. 15
  • 16. Key Software Components of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 16
  • 17. Key Software Components of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 17
  • 18. Use Cases for Data Insight Data profiling and data quality monitoring Key Drivers Improve information trustworthiness  Continuously improve data quality  Provide visibility into quality of data Reduce risks for propagating bad data  Find data anomalies and remediate data issues Easily understand data and its relationships  Create data mapping rules for data integration  Define data cleaning and validation rules Show ROI for data quality initiatives  Quantify impact of poor data on business  Speed up data integration projects with better DQ information  Validate governance controls are effective on data quality (for example: investment in MDM) © 2011 SAP AG. All rights reserved. 18
  • 19. Visualization of Data Quality High-level balanced data quality scorecard Drill into scorecard details Scorecard to measure DQ from a Data Steward’s perspective Key Quality Dimensions (KPI for data) Latest quality score Data quality score metrics © 2011 SAP AG. All rights reserved. Quality trend 19
  • 20. Visualization of Data Quality Validation rules oriented dashboard Select Key data domain, Quality dimension, Rule, and Rules binding to analyze data quality based on any combination of these attributes View validation rule definition Switch to Workspace to profile data and create validation rules Analyze sample failed data Analyze impact of failed data © 2011 SAP AG. All rights reserved. 20
  • 21. Visualization of Data Quality Data quality scores and trend at table, column, and rule level Table level score measures number of rows that passed all rules Column level score measures number of rows that passed all rules for this column Rules level score measures rows that passed this rule Detailed statistics of number of failed and total rows © 2011 SAP AG. All rights reserved. Data quality trend over different time ranges Sample failed rows for analysis of the last rule execution 21
  • 22. Interactively Identify Data Quality Problems Multi-column data profiling Address profiling measure % valid addresses, % invalid addresses, % can be corrected © 2011 SAP AG. All rights reserved. Dependency profiling measures the degree to which two sets of values are related on one another Redundancy profiling measures the degree of data overlap between two data sets Uniqueness profiling measures the degree of uniqueness of one or more columns of a table 22
  • 23. Interactively Identify Data Quality Problems Table/column data profiling Summary indicators for low cardinality, uniqueness and sparseness Tools for analyzing sample profiling result rows © 2011 SAP AG. All rights reserved. View column properties, value, string, completeness, and distribution profiling statistics Drill from profiling result to into value distribution Drill from value distribution to sample profiling result rows 23
  • 24. Interactively Identify Data Quality Problems Data redundancy There can be multiple advanced profiling tests (tasks) for a table Visualize data relationship Drill into sample data © 2011 SAP AG. All rights reserved. 24
  • 25. Key Software Components of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 25
  • 26. Use Cases for Metadata Management BI-centric metadata management “Where did this number come from?” Key Drivers  Understand entire BI environment  Trace data lineage from a report to sources  Change impact analysis for source to reports and users  Manage metadata from various data sources, data integration technologies, and BI systems  Lower “How will this change in the source impact my BI reports?” © 2011 SAP AG. All rights reserved. TCO by tracking usage and promote reuse of data and reports  Improve decision making and regulatory compliance 26
  • 27. SAP BusinessObjects Metadata Management Overview Consolidate, Integrate, Audit, and Trust your Metadata BI Systems Metadata Integrators Metadata Repository  Consolidates Analysis Central Repository metadata from various BI related sources  Integrates Databases Consolidate Audit metadata in a central metadata repository  Relates ETL Integrate Modeling Tools ■ ■ ■ ■ ■ Custom Attributes Annotations, Metapedia  Supplements metadata with custom attributes, annotations  Creates Business Metadata © 2011 SAP AG. All rights reserved. Impact Usage Lineage Trends Search metadata to enable auditing, usage, change impact, and data lineage analysis Universe Creation universe from relational objects 27
  • 28. Metadata Integrators Metadata Management Integration to: BI Systems Metadata Integrators bundled with Information Steward Databases Metadata Integrators SAP Software: BI Platform, Data Services, Data Federator and SAP NEtWeaver BW NON SAP Software: CWMXML (CWM), RDBMS: MSSQL Server, DB2, Teradata and JDBC Sources Other Metadata Integrators available * ETL Modeling Tools Altova Borland CA COBOL Embarcadero EMC Gentleware Silverun Knightbridge (HP) IBM Informatica Micsosoft MicroStrategy NoMagic OMG Oracle SELECT SPARX Systems SUN Sybase Teradata Tigris Visible Systems Corp W3C * Other metadata integrators available via Meta Integration Technology, Inc. (MITI) © 2011 SAP AG. All rights reserved. 28
  • 29. Key Software Components of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 29
  • 30. Cleansing Package Builder (CPB) Key Drivers  Empowers data stewards/domain experts to develop custom data cleansing solutions for any data domain  Cleansing Package Builder is available within Information Steward © 2011 SAP AG. All rights reserved. 30
  • 31. Why Do We Need Cleansing Package Builder? Unique data for ‘non-party’ data elements Parsed Output Product Category Glove Size Large Material Synthetic Leather Trademark Pro-Fit 2.3 Series Cuff Style Elastic Velcro Palm Type Ultra-Grip Color Black Vendor Mechanix Wear Standard Description Glove – Synthetic Leather, Black, size: Large, Cuff Style: Elastic Velcro, UltraGrip, Mechanix Wear Input Data Glove ultra grip profit 2.3 large black synthetic leather elastic with Velcro Mechanix Wear © 2011 SAP AG. All rights reserved. 31
  • 32. Key Software Components of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 32
  • 33. Use Cases for Metapedia Business term encyclopedia Key Drivers   Enable business users to understand data attributes used in BI environments with business user oriented descriptions  Central location for defining standard business vocabulary (words, phrases, or business concepts)  © 2011 SAP AG. All rights reserved. Promote proactive data governance with common understanding and agreement on business concepts Organize business terms into categories that align with business subject matter or lines of business 33
  • 34. Why SAP? The best choice for EIM One place for data stewards and business analysts to collaborate and govern their data asset First and only integrated solution - metadata management, business glossary, data quality assessment, data quality monitoring, and cleansing package builder solution Various perspectives to understand and analyze trustworthiness of data Easy and secure access to a rich set of metadata data sources © 2011 SAP AG. All rights reserved. 35
  • 35. Information Steward Services - Migration For the migration from Data Insight to Information Steward we have created three migration packages at fixed fee & fixed scope.* Small Complexity Medium Complexity High Complexity • Number of sources < 3 • Number of column queries <10 • Referential Integrity Test = 10 • Custom queries = 0 • Number of sources < 10 • Number of column queries <100 • Referential Integrity Test = 10 • Custom queries < 30 • Various complexity • Number of sources <25 • Number of column queries <300 • Referential Integrity Test = 10 • Custom queries < 70 • Various complexity 15 days 50 days 120 days * Pricing being finalized. Meta Data Management upgrade not included. © 2011 SAP AG. All rights reserved. 36
  • 36. Information Steward Services – Quick Start Our Quick Start Package is design for green-field implementations to assist our customers to quickly take advantage of IS 4.0; fixed fee and fixed scope.* Quick Start Package • Install IS environment • Knowledge transfer • Setup and execute data profiling jobs • One data domain from two source systems • Configure CPB dictionaries based on the profiles • Design DQ and other dashboards 10 days * Pricing being finalized. © 2011 SAP AG. All rights reserved. 37
  • 37. Further Information  SAP Community Network Business Analytics community http://www.sdn.sap.com/irj/boc EIM page http://www.sdn.sap.com/irj/boc/nw-informationmanagement EIM discussion forums http://forums.sdn.sap.com/index.jspa#4  Social Media Twitter http://twitter.com/sapmdmgroup http://twitter.com/sapcommnet Facebook https://www.facebook.com/sapcommunitynetwork  Upcoming Webinars Business Analytics Webinar Series http://www.sdn.sap.com/irj/scn/business-analytics-webinars © 2011 SAP AG. All rights reserved. 38
  • 38. Thank You! Contact information: Michael J Briles Senior Solution Manager – Enterprise Information Management E-mail: michael.briles@sap.com