Data Needs Management
Data is a foundational asset of every enterprise. Like other assets of the enterprise, data needs to be managed to ensure it is available for effective use and its quality is maintained. And to make certain that at end-of-life it is properly disposed of and does not become a liability.
What is Data Management?
The DAMA wheel provides a useful overview of the field of Data Management.
It is a simplification, but it clearly shows that Data Management is made up of a number of areas of expertise, all coordinated by Data Governance.
Together they make up the totality of Data Management.
It is a simplification, but it clearly shows that Data Management is made up of a number of areas of expertise, all coordinated by Data Governance.
Together they make up the totality of Data Management.
The DAMA Wheel copyright DAMA International
Nicola Askham The Data Governance Coach
Data Governance
I like the approach to Data Governance developed by Nicola Askham.
There are three phases:
There are three phases:
- Strategy
- Why are we doing this?
- What is the end goal?
- The roadmap
- Framework
- Policy - the approach to managing Data Quality
- Processes
- Roles and responsibilities
- Implementation
- People
- Phases
- Plans
Data Quality
To my mind each aspect of Data Management has Data Quality as its primary goal. So it seems odd that Data Quality is one of the areas of expertise within Data Management as depicted by DAMA. Nevertheless, when there is an awareness that Data Quality is an issue, it is useful to have a collection of tools to measure, repair and maintain the quality.
The Data Quality Workgroup of the Netherlands chapter of DAMA is working on a Data Quality Management System aligned with ISO 9001. It has two objectives and 25 elements that contribute to achieving these objectives.
The Data Quality Workgroup of the Netherlands chapter of DAMA is working on a Data Quality Management System aligned with ISO 9001. It has two objectives and 25 elements that contribute to achieving these objectives.
Licensed by DAMA NL under CC Attribution 4.0 International
Metadata
Metadata that defines the meaning of the data used by an enterprise is the foundation of Data Management. Good, accessible metadata ensures reliable interpretation of the data to provide information.
A mass of data with no definitions, and no means of finding definitions, is useless, and can be dangerous if users start trying to guess what the data means.
The DAMA Netherlands Data Quality Workgroup has a Factsheet on Metadata that describes metadata in a nutshell.
As mentioned in the Factsheet, there are other types of metadata, such as data lineage and operational metadata, that are also of importance in Data Management .
A mass of data with no definitions, and no means of finding definitions, is useless, and can be dangerous if users start trying to guess what the data means.
The DAMA Netherlands Data Quality Workgroup has a Factsheet on Metadata that describes metadata in a nutshell.
As mentioned in the Factsheet, there are other types of metadata, such as data lineage and operational metadata, that are also of importance in Data Management .
Open to freelance assignments in aspects of Data Management:
- Data Governance
- Data Quality
- Metadata development such as
- Data Models
- Business Glossaries
- Data Dictionaries
- Master Data Management
- Data mapping on interfaces