Post on 09-May-2018
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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
36
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
37
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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Disclaimer
SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. All other product and service names mentioned are the trademarks of their respective companies. Wellesley Information Services is neither owned nor controlled by SAP SE.