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Master  Data  Management  (MDM)  and  Data  Quality  with  SAP  Information  Steward

Kevin HuttoConsultancy by Kingfisher

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In This Session

• Learn how Enterprise Information Management helps to empower data stewards with a single environment to discover, define, monitor, and improve the quality of their enterprise data asset

• Use Information Steward to monitor the quality of data• Drive information governance and standardizations for Master Data

Management (MDM) enforced by Information Steward tools such as scorecards, dashboards, and data quality cleansing packages

• Link data quality metrics to drive business data ownership

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What We’ll Cover

• Information Steward and Enterprise Information Management Overview

• Metadata Management Overview and Demo• Data Insight• Quality Scorecards• Data Cleansing and Data Services• Wrap-up

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Data Issues

• The causes of poor data can be hard to identify and fix

⬧ Data resides in incompatible sources

⬧ No consistent, repeatable way to measure data quality

⬧ No ability to analyze data dependencies across systems

⬧ No clear strategy for improving data quality

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Data Governance Objectives

• Get full visibility into the reliability, origins, and lineage of your data• Reduce the risk of propagating bad data with comprehensive data

profiling• Consolidate, integrate, and audit your metadata to create a central

glossary• Determine the origin of data quality problems – and evaluate their

net impact• Monitor data quality continuously by validating rules against data

sources

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Next Generation DI Report

60%

52%

41%

17%

0% 15% 30% 45% 60% 75%

Business  and  technical  people  speak  different  languages

Lack  of  a  business-­friendly  view  of  data

Current  tools  lack  functions  for  business  people  to  use

Collaboration  is  not  an  issue  for  us

Information Steward addresses these challenges

Source:  TDWI Checklist Report // Taking IT to the Next Level: Next-Generation Data Integration

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Enterprise Information Management

Information  Lifecycle  Management

Before After

A

C

D B

Data  Quality

Master  Data  Management

Content  Management

Data  Modeling

Data  Integration

GOVERN

Source:  SAP

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MonitorQuality

continuously  

ImproveData  quality

andgovernance

Single Solution, Multiple Benefits

Empower business and IT users with a single environmentto manage the quality of their enterprise data assets

DiscoverUnderstandand  catalogenterprise  data

AssessOverall

data  quality

DefineRules  andownership

Source:  SAP

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Data Integration and Quality Opportunities

• CIOs struggle to empower knowledge workers to make better decisions and improve business operations

$8,200,000is the annual average estimated loss due to data quality issues

46%of organizations cited the need for betteraccess and analysis of real-time dataas one of the top data management objectives in next 12 months

Source:  TDWI Checklist Report // Taking IT to the Next Level: Next-Generation Data Integration

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Why Use Information Steward?

Empower Business UsersBridge gap between business and IT with collaborative solution for driving information management initiatives

Govern Enterprise InformationEnable effective data governance through combined data profiling, metadata management, and data quality monitoring

Improve Information TransparencyGive instant visibility into data quality levels and origins with end-to-end impact analysis and data lineage

Adopt one solution for data stewardship

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Information Steward Solution

Data  ProfilingDQ  Monitoring

Metadata  Analysis

CleansingRules

BusinessTerm

Taxonomy

Source:  SAP

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What We’ll Cover

• Information Steward and Enterprise Information Management Overview

• Metadata Management Overview and Demo• Data Insight• Quality Scorecards• Data Cleansing and Data Services• Wrap-up

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Metadata ManagementInformation You Can Trust

EDW

How  will  this  change  impact  my  reports?

“Where  did  this  number  come  from?”

R1

R2

R3

Rn

?

?Transformation / Enrichment / Standardization

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Full lineage map from source to report

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Metapedia Overview

• Promote proactive data governance with a common understanding and agreement on concepts and terms

• Enable users to understand data used in BI with business user descriptions

• Central location for defining standard business vocabulary

• Organize business terms into categories that match with lines of business

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Metapedia Demo

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Information Steward Overview

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What We’ll Cover

• Information Steward and Enterprise Information Management Overview

• Metadata Management Overview and Demo• Data Insight• Quality Scorecards• Data Cleansing and Data Services• Wrap-up

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Data Insight: Scorecard

Full Scorecard views of your information

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Categorized view with performance indication against set thresholds

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Validation of data to point to rules not meeting criteria.

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Ability to create and validate rules within the same interface.

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What We’ll Cover

• Information Steward and Enterprise Information Management Overview

• Metadata Management Overview and Demo• Data Insight• Quality Scorecards• Data Cleansing and Data Services• Wrap-up

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Quality Scorecards

Central screen for all related workspaces and scorecards

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Quality Scorecards

Quality of data over time

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Rules to be added for validation of information

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Validation Rules

Standardize the information based on patterns

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Full view of all failed data from rules in place

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What We’ll Cover

• Information Steward and Enterprise Information Management Overview

• Metadata Management Overview and Demo• Data Insight• Quality Scorecards• Data Cleansing and Data Services• Wrap-up

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Create Cleansing Packages

Jeff/Jeffrey Smith can be standardized

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Data Standardization

McDonalds/McDonald’s same company and classified as FIRM.

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Cleansing Package Builder

Define Standards and variations on free-form text

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Data Services: Cleansing

Advanced Workflow

Workflow builds in Data Services to cleanse information as it is loaded.

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Data Quality: Transformations

Full use of data quality transforms

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Enterprise Information Management

Information  Lifecycle  Management

Before After

A

C

D B

Data  Quality

Master  Data  Management

Content  Management

Data  Modeling

Data  Integration

GOVERN

Source:  SAP

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What We’ll Cover

• Information Steward and Enterprise Information Management Overview

• Metadata Management Overview and Demo• Data Insight• Quality Scorecards• Data Cleansing and Data Services• Wrap-up

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Where to Find More Information

• http://scn.sap.com/docs/DOC-8751⬧ Comprehensive Product Tutorials

• http://scn.sap.com/community/information-steward⬧ Information from the Enterprise Information Management Community

• http://help.sap.com/bois⬧ Documentation and deployment documents

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7 Key Points to Take Home

• Regulations across all industries are driving data governance • Enterprise Information Management should be a priority to all

organizations• Good data is key to any Business Intelligence solution• Lineage of data to determine impact analysis on analytics can save

valuable time• Visibility into the data to decide if corrective action is critical• Tools have generally been IT-driven, but now need input from the

business• Business terminology should be cohesive and something easily

understood across the organization

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Your Turn!

How to contact me:Kevin Hutto

Kevin.Hutto@kingfisherinc.com

Please remember to complete your session evaluation

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