Data Governance Framework
Data Governance Framework
Each vendor has their own opinion about the best framework for Data Governance, here I try to explain in quick and globally, ideally the best framework must be modified to comply with the company regulation and culture.
DAMA approach with the framework is very complex and detailed and it is not a ‘blog size’ content. To understand detailed about the framework, consider to buy the book : The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK) Print Edition
This is the Data Management Functional Framework version 3
According to DAMA, Data Governance is 1 of the 10 main subject of Data Management. Please note that DAMA differentiate the term Data Management and Data Governance.
Data Governance itself is only SOP, Policy, Rules, Standard, and Evaluation about overall Data Management practice (the other 9 subjects)
Well according to my opinion, what I am talking about Data Governance is actually Data Management, since that this is my blog, so you will follow me to use Data Governance term instead of Data Management :D
The DMBOK itself will tell you detailed about the 10 main subjects of Data Management and some info about the CDMP certification.
The framework described in the book is telling you that all data activity :
- Data Architecture management : plan the data model and data architecture
- Data Development : do the data model and design implementation
- Database Operation Management : do the day by day database operation, which include performance monitoring, performance tuning, backup, archive, recovery
- Data Security Management : create the security rules and do the security audit
- Reference & Master Data Management : manage the ‘Golden Record’ of data (will talk about this in my future post)
- Data Warehousing & Business Intelligence Management : manage the data flow from and to Data Warehouse and also monitor the cube usage for Business Intelligence. Note that since DW and BI are very big things in company, some company will differentiate the database operation and datawarehouse operation into 2 separate organization
- Document & Content Management : Manage the digital imaging of document.
- Metadata management : manage and maintain the overall data flow from source to target, and also to reporting service
- Data Quality Management : manage the data quality, do the mitigation plan for any dirty data impact. Will talk with business user directly regarding the data cleansing plan
Here is the exact word as taken from the DAMA explanation itself:
When you search for the term “data governance”, more likely this DGI website will come up at the first. In internet marketing world, this is the perfect example between niche word and domain word. Ok before it goes to far to internet marketing world, DGI has more “flow like” framework, while DAMA hides the small components like stakeholder and stewards, here DGI put it as main component.
This is the colorful framework from DGI
In DGI, you can go to here to get the detailed info about it. The concept here started from the 2 sides : Business and Information Technology; separate the Information and Technology, and we get “information” as the main subject here.
Data governance will talk about this “Information” aspect.
Here’s the drawing taken from DGI :
Take a look at the framework, DGI divide it easily into 3 main domains :
People :
7. Data Stakeholders
8. A Data Governance Office (DGO)
9. Data Stewards
Process :
10. Proactive, Reactive, and Ongoing Data Governance Processes
Technology or maybe Rules is the correct word:
1. Mission and Vision
2. Goals, Governance Metrics and Success Measures, and Funding Strategies
3. Data Rules and Definitions
4. Decision Rights
5. Accountabilities
6. Controls
Due to copyright issue, I cannot put the framework in web, if you want to get detailed, contact me and I can put you the right people from Accenture to contact you J
Let me try to put the word to describe the framework. Accenture describe Data Management as core of the data lifecycle from creation to retirement.
Data management controls it by configuring 6 elements of data management :
- Data Governance : the policy and procedure
- Data Structure : the model + taxonomy
- Data Architecture : storage, migration, archiving, retention architecture
- Master data + Metadata : clear enough from the name
- Data Quality : same as Data Quality Management in DAMA
- Data Security : same as Data Security Management in DAMA
Comments
Post a Comment