Whitepaper : ER/Studio Enterprise Team Edition
Five Data Modeling Tips for Better Data Governance
Author: Karen López
Share This:
Are your data models truly supporting data governance?
Most data professionals have been involved in some way in data governance programs at some point in our careers. These programs range from light governance to fully staffed, well-funded C-level offices to ensure data quality and data protection for the enterprise.
No matter what level of data governance you have been involved with, data models provide a vital resource for successful governance programs. In this work, Karen Lopez looks at the data modeling features that need to be part of an enterprise’s data modeling portfolio to ensure compliance with better data governance processes.
Here are some advantages of better data models for better data governance:
- Data governance tasks are completed faster with better data models: When teams are working toward the same goal, both individual and collaborative tasks are completed faster. Logical data models that have had strong engagement data stewards comprise hundreds of hours of decisions made by business users and data professionals. The results can save a significant amount of data governance time.
- Collaborative tasks are easier: When there is less contention and more trust among team members, tasks are easier to complete because there are fewer distractions. Happier teams have better outcomes.
- Data model quality is data quality: The quality of data models has a direct impact on data quality. Data models, as requirements and specifications for data, are the standards against which we measure data quality. Barebones data models, often just diagrams of databases, do not aid in better data governance.
Register to read the full whitepaper.
Karen Lopez has more than 20 years of database design experience. She specializes in the practical application of design approaches, balancing development time frames with the need to deliver solutions that will support business agility and data quality needs. She’s known for her fun and engaging speaking and teaching style. She tweets about data, space exploration and her travel experiences at @datachick. Karen blogs at datamodel.com.
Topics :
Data Governance,Data Modeling,
Products :
ER/Studio Data Architect,ER/Studio Enterprise Team Edition,
Author: Karen López
Share This:
Are your data models truly supporting data governance?
Most data professionals have been involved in some way in data governance programs at some point in our careers. These programs range from light governance to fully staffed, well-funded C-level offices to ensure data quality and data protection for the enterprise.
No matter what level of data governance you have been involved with, data models provide a vital resource for successful governance programs. In this work, Karen Lopez looks at the data modeling features that need to be part of an enterprise’s data modeling portfolio to ensure compliance with better data governance processes.
Here are some advantages of better data models for better data governance:
- Data governance tasks are completed faster with better data models: When teams are working toward the same goal, both individual and collaborative tasks are completed faster. Logical data models that have had strong engagement data stewards comprise hundreds of hours of decisions made by business users and data professionals. The results can save a significant amount of data governance time.
- Collaborative tasks are easier: When there is less contention and more trust among team members, tasks are easier to complete because there are fewer distractions. Happier teams have better outcomes.
- Data model quality is data quality: The quality of data models has a direct impact on data quality. Data models, as requirements and specifications for data, are the standards against which we measure data quality. Barebones data models, often just diagrams of databases, do not aid in better data governance.
Register to read the full whitepaper.
Karen Lopez has more than 20 years of database design experience. She specializes in the practical application of design approaches, balancing development time frames with the need to deliver solutions that will support business agility and data quality needs. She’s known for her fun and engaging speaking and teaching style. She tweets about data, space exploration and her travel experiences at @datachick. Karen blogs at datamodel.com.
Topics : Data Governance,Data Modeling,
Products : ER/Studio Data Architect,ER/Studio Enterprise Team Edition,