This document discusses how metadata management automation can help with data governance efforts. It notes that data governance depends on quality metadata and that automation can help with metadata collection, analysis, and delivery processes. The document outlines what to look for in a metadata management tool, how such a tool can increase metadata usage, and the various roles that would benefit from improved metadata automation, such as data stewards, users, and managers.
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Metadata Management Automation
for the Governance Minded
Introductions
Robert S. (Bob) Seiner
KIK Consulting & Educational Services (KIKconsulting.com)
The Data Administration Newsletter (TDAN.com)
Non-Invasive Data Governance & Non-Invasive Metadata Governance
Gal Alon
Octopai
Senior Director of Business Development
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Metadata Management Automation
for the Governance Minded
Topics for Today!
● Data Governance’s dependency on quality metadata
● Automation of metadata collection and management processes
● What to look for in a metadata management tool and how it will help
● How a great tool will lead to increased use of your metadata assets
● People that will benefit from improved metadata automation and delivery
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Metadata Management Automation
for the Governance Minded
Data Governance’s dependency on quality metadata
● If you plan on being non-invasive, automation is important
● Manual tasks require formal accountability
● Data understanding, usage and value improve with quality metadata
● The metadata will not govern itself
7. ● Extract and Centralize all data layers from across your environment
○ Reporting - Physical layer + Semantic layer + Presentation layer
○ Cross systems visibility - even if they are from different vendors
(e.g. Tableau, Power BI, Informatica, Oracle, SSIS etc.)
○ Include Logical and Calculated data items
● And…make sense of it
● And…inject analyzed metadata into your governance tool
How to take Data Governance
to the Next Level with Automation
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8. One source of the truth for the business
● Eliminate futile tasks, focus on core value of governance projects
● Save time and money (replace manual with automation)
● Increase accuracy with continuous, up-to-data metadata
● Common business language
● Improve self-service BI
● Increase company-wide consistency & data integrity
What happens when you automate
Metadata Management?
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Metadata Management Automation
for the Governance Minded
What to look for in a metadata management tool and how it will help
● Effective metadata definition, production, usage.
● Efficient metadata analysis and navigation.
● Automation to enhance metadata collection.
● Metadata presentation and delivery.
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Metadata Management Automation
for the Governance Minded
Automation of metadata collection and management processes
● Database Sources
● ETL Tools
● Data Warehouse and MDM Platform and Tools
● Reporting and Analysis Tools
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Metadata Management Automation
for the Governance Minded
How a great tool will lead to increased use of your metadata assets
● Resources for consistent tool management.
● Automation decreases resource requirement.
● Automation results in accurate metadata collection.
● Automated Metadata Analysis results in improved metadata consumption.
12. DB Sources
Marketing
CRM
ERP
Finance
HR
Other Sources
ETL Tools
Informatica
DataStage (IBM)
SSIS (MS)
Others
(ODI, Talend, etc.)
Data Warehouse
Oracle
Others
(Hadoop, etc.)
SQL Server(MS)
Teradata
Vertica HP
Reporting & Analysis
Tools
Cognos (IBM)
BO (SAP)
Power BI
Tableau
OBIEE (Oracle)
Others (Qlik, etc)
SSAS-OLAP,
TABULAR
Complete data lineage to and from reports
OCTOPAI AUTOMATED METADATA MANAGEMENT
13. Boosting Data Governance with automated
metadata management
DG + BI teams are using Octopai to locate their data instantly, and toquickly and accurately
visualize and understand the entire data journey for various use cases:
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Data Governance Business Intelligence Operations
Data
Catalog
Lineage
for Audit
Data
Discovery
Automated
Business
Glossary
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Metadata Management Automation
for the Governance Minded
People that will benefit from improved metadata automation and delivery
● Data Definers – Integration and Project Management
● Data Stewards – Data Producers and Users
● Data Users – Business and Technical Communities
● Data Managers – Owners and Subject Matter Experts