Scenario: An organization wants to implement version control for its data modeling projects to improve collaboration and ensure data model integrity. What steps would you recommend for setting up version control in this scenario?
- Choose a version control system, Define branching and merging strategies, Train team members, Regularly review and merge changes
- Implement version control after project completion, Trust team members without control measures, Assume no conflicts will occur, Ignore version control updates
- Skip version control, Focus only on data modeling tools, Keep all team members isolated, Avoid documentation
- Use a version control system only for code, Ignore team collaboration, Rely solely on manual documentation, Trust in verbal communication
The recommended steps for setting up version control in this scenario include choosing a version control system, defining branching and merging strategies, training team members, and regularly reviewing and merging changes. This comprehensive approach ensures collaboration, data model integrity, and effective use of version control throughout the project lifecycle.
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