As more and more enterprises create Data Lakes and expand their collections of dynamic and static data, it is becoming more apparent the value that Data Governance brings. Dataanalytics.com’s proven Data Governance Framework has been adopted by multiple organisations to improve the quality, reliability, deployability, security and value of their data, data products and data services. This quick 20 minute overview explains how your organisation can significantly improve the management and governance of your data.
Categories
2 replies on “Avoid the Data Swamp: An overview of Data Analytics’ Data Governance Framework”
The Data Swamp is a term used to describe the dilemma organizations face when their data management practices can no longer keep up with the rate and volume of data being generated. The Data Swamp is characterized by data sprawl, anarchy, and overload. As data volumes continue to grow, organizations need to take a proactive approach to data governance to avoid the Data Swamp.
The Data Analytics’ Data Governance Framework is a five-step approach to data governance that can help organizations avoid the Data Swamp. The five steps are:
1. Define the business problem that the data will be used to solve.
2. Collect the right data for the problem.
3. Organize the data so that it can be used effectively.
4. Analyze the data to find insights.
5. Take action based on the insights.
The Data Swamp is a term used to describe the dilemma organizations face when their data management practices can no longer keep up with the rate and volume of data being generated. The Data Swamp is characterized by data sprawl, anarchy, and overload. As data volumes continue to grow, organizations need to take a proactive approach to data governance to avoid the Data Swamp.
The Data Analytics’ Data Governance Framework is a five-step approach to data governance that can help organizations avoid the Data Swamp. The five steps are:
1. Define the business problem that the data will be used to solve.
2. Collect the right data for the problem.
3. Organize the data so that it can be used effectively.
4. Analyze the data to find insights.
5. Take action based on the insights.
http://ribotek.in/