Organizational Aspects of Data Management

9 important questions on Organizational Aspects of Data Management

What is the role of metadata?

Concepts of data modeling can also be applied to metadata. Metadata is stored in catalog, which constitutes the heart of the database system, can be part of DBMS or a standalone component. Also an important source of information

Provides
- an extensible metamodel
- import/export facilities
- support for maintenance and reuse of metadata
- monitoring of integrity rules
- facilities for user access
- statistics about the data and its usage for the DBA and query optimizer

What is metadata modelling?

Metamodel is data model for metadata
A database design process can be used to design a database storing metadata
Design a conceptual model of the metadata: EER or UML

Intrinsic data dimensions?

Accuracy: certified, error free, correct, flawless, reliable
Objectivity: unbiased, unprejudiced, facts, impartial
Reputation: highly regarded in terms of source or content
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Contextual data dimensions?

Completeness: not missing, covers needs, sufficient
Appropriate: volume is enough
Value-added: provides advantages from use
Relevance: applicable and helpful
Timeless: sufficiently up-to-date
Actionable: ready for use

Representation data dimensions?

Interpretable: appropriate languages, symbols are clear
Easily-understandable: comprehension
Consistency: presented in the same format
Concisely-represented: compact, well presented, organized, and formatted
Alignment: reconcilable
-

Access data dimensions?

Accessibility: available, easily retrievable
Security: wether data restricted to maintain security
Traceability: traceable to the source

What are common causes of bad data quality?

- multiple data sources: consistency
- subjective judgment in data production: objectivity
- limited computing resources: accessibility
- volume of data: accessibility
- changing data needs: relevance
- different processes updating the same data: consistency

Decoupling of data producers and consumers contributes to data quality problems

What is data governance?

To manage and safeguard data quality: clear roles and responsibilities. Manage it as an asset rather than a liability

Wang frame
Define, Measure, Analyze and Improve

Most efforts are mostly reactive and adhoc. Also annotate the data with data quality metadata as a short term solution??

What roles are the in data management?

Information Architect
Database designer
Data owner
Data steward
Database administrator
Data scientis

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