1) Metadata is defined as data recorded in IT tools that improves the business and technical understanding of data and data-related assets.
2) There are three actions people take with data: define, produce, and use data. Metadata helps improve these actions.
3) Metadata needs governance roles at the executive, strategic, tactical, and operational levels to ensure its quality and usability.
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Recognized Industry Leadership
Industry Awards and Accolades
erwin is a Leader in Metadata Management
(Gartner 2020)
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What Metadata Management Can Provide
VISIB ILITY, C ON TEXT, C ON TR OL & C OLLA B OR ATION
What data do we
have?
Where did it come
from?
Where is it now?
How has it changed
since it was first
captured?
How is it used?
How accurate
is it?
Is it sensitive?
What rules or
restrictions apply?
How can
I access it?
Who is accountable?
What do others say
about it?
DATA IN
CONTEXT
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Reliable DATA INSIGHTS don’t JUST HAPPEN
You know this because
you invested in
Enterprise Models
Leverage your
diligence into a
Data Intelligence
Program with
Auto Classification
Create your Data Intelligence Catalog
with pre-defined:
• Critical Data Elements
• PI Tags
• Sensitive Data
• Logical Data Definitions
• Logical Data Mappings
• Business Lineage
Begin immediately with the highest
caliber of Enterprise Data Standards
Data intelligence catalog jumpstart
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Three pivotal capabilities
A view into
Data Lineage
A focus on
Data Quality
Business-friendly
Asset Discovery &
Collaboration
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Why Has Metadata Management Been Difficult?
Traditionally, it’s been manual and tedious. AUTOMATION changes the equation for faster time to
value and greater accuracy.
Smart Data
Connectors for
Intelligent Lineage
• E2E Observability
• Code Generation
• Reverse Engineering
• Test and Validation
Smart Data Connector Capabilities
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Accessible, detailed data lineage
Fueled by automated metadata harvesting within erwin Data Intelligence, one central metadata repository
A single-source, understandable view of data
landscape metadata
All-inclusive visibility of systems, environments, tables
and columns across your entire data landscape
Discover, drill into and understand data sources using
interactive data lineage with logical and physical
naming and data quality scores
Provide the data visibility to work
smarter and confidently
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Integrated data quality
Automate the profiling and quality assessment of the data feeding your analytics and raise data quality visibility
Initiate and automate data profiling and data quality
assessment using data catalog metadata
Build data trust and understanding with data quality
visibility within the data catalog, and in lineage, impact
analysis, mind maps and more for all stakeholders