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Workflows of Highly Functional App & Data Engineering Teams - Jerry Nixon
Discover workflows of highly functional app and data engineering teams for scalable, reliable data engineering infrastructure and accurate processing.
- Establish a clear definition of workflows for highly functional app and data engineering teams.
- Use a declarative approach when interacting with the database to ensure flexibility and maintainability.
- Use incremental deployments to overcome the limitations of traditional deployment methods.
- Focus on building a scalable and reliable ETL process rather than trying to prove every piece of data.
- Consider using a semantic renaming scheme to simplify database changes and reduce risk.
- Automate testing to reduce manual testing time and increase confidence in code changes.
- Use a data-driven approach to data processing to ensure accuracy and reliability.
- Consider using a data catalog or data dictionary to manage and track data assets.
- Focus on building a robust and scalable data engineering infrastructure to support data processing and analytics.
- Use visualization tools and dashboards to communicate complex data analysis insights to stakeholders.
- Emphasize the importance of collaboration and communication among team members to ensure successful project outcomes.
- Consider using a combination of automated and manual testing to ensure comprehensive testing coverage.
- Use a version control system to manage changes to the database schema and ensure versioning.
- Focus on building a data engineering team that is empowered to make decisions and take ownership of projects.
- Consider using a data science platform or tool to support data processing and analysis.