The document discusses the complexities of metadata modeling in data architecture, led by Karen López. It covers terminology, misconceptions, and the various aspects related to metadata such as compliance, data lineage, and standards. The content aims to provide insights into existing and new technologies, as well as the evaluation and deployment processes in data modeling.

1. Big Challenges in Data Modeling: Metadata Modeling
Karen López
@datachick

2. Karen Lopez
InfoAdvisors.com
@datachick
Senior Project Manager & Architect
Love Your Data

3. POLL: Who Are You?
2014 - NoSQLNow! - D'Antoni / Lopez
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4. What we will be doing
Terminology, Foundations and Thoughts.
What is Metadata and Metadata Modeling?
Myths and Gotchas
Q&A

5. What would you like to do?

6. Outcomes
•Concepts
•Features
What
•Existing Tech
•New Tech
•Hybrid
Where
•Evaluate
•Pilot
•Production
When
•Benefits
•Trade-offs
Why
•Architects
•Devs
•DBAs
Who
•Modeling
•Dev
•Test
How
•Costs
•Trade-offs
How much
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7. Terminology and Thoughts
Because we need a vocabulary to share ideas

8. Compliance
Metadata
Data Lineage
Metadata Extraction
Repository
Glossaries
Regulatory
Data format
Meta-data
Meta data
Workflow
Data Lifecycle

9. Metadata standards

10. What

11. Why

12. Who

13. How

14. Where

15. When
Project Initiation
Architecture and Infrastructure Design
SW + Data Requirements
Development
Deployment

16. Myths

17. Q&A