Geek Sync Webcast : ER/Studio Enterprise Team Edition

Data model change management refers to managing and implementing changes to data models in a controlled and systematic manner. This process ensures that changes to data models are planned, documented, and communicated to all relevant stakeholders, minimizing disruption and maintaining data integrity and consistency.

Data model change management is important for several reasons:

• Maintain data quality: Changes to data models can affect data quality if not managed well. A systematic approach to change management ensures that data quality is maintained throughout the change process.
• Reduce risks: Unplanned or mis-managed changes can introduce risks, such as data loss or corruption. Change management helps mitigate these risks by implementing a structured process for making changes.
• Facilitate collaboration: Effective change management promotes communication and coordination among stakeholders, ensuring that everyone is aware of changes and their implications.
• Adapt: Organizations need to adapt to developing business requirements and technologies. Data model change management enables organizations to respond to these changes while maintaining the stability and integrity of their data models.

In today’s development environments, it is of critical importance to ensure that data models and databases are aligned to the user stories and tasks being created. Data architects must proactively collaborate with DBAs and designers, and take the initiative to track data model changes and correlate them against development and database updates.

Join IDERA and Joy Ruff in this webinar to learn about these trends and considerations for implementing model change management in your enterprise.

About Joy Ruff:
Joy was the product marketing manager for ER/Studio, IDERA’s flagship data modeling and architecture platform, plus several database management and security products. With nearly 25 years of experience in high-tech hardware and software, Joy enjoys communicating product value to customers.