Data Warehouse Automation
Data warehouse automation (DWA) is the automation of each and every part of the entire data warehouse lifecycle.
Updated: December 5, 2023
Data warehouse automation (DWA) is the automation of each and every part of the entire data warehouse lifecycle. The numerous tasks that is done by a data warehouse including discovery, designing, developing, deploying, provisioning, and scaling are automatically managed by using DWA.
These automation tools require less amount of time to manage it by automating every step of the data warehouse lifecycle. Therefore, more time can be spend on critical tasks instead of managing the data warehouse 24/7.
Increased productivity and ROI, Increased business agility, Better data quality, Improved data management processes, More time for developers and Standardization and compliance are benefits of using data warehouse automation.
A BI analyst can access clean, prepared, and processed data with DWA tools that would help them make data-driven decisions wherever possible. These tools can also be used to move warehouse data into other systems, such as data visualization and cloud-based BI tools. DWA can be used by business users to provide data-driven business insights. Analytic models can be build by data warehouse users to help achieve fast and accurate business intelligence reporting. It would take weeks or months to deliver insights without DWA, which would be inaccurate since the data is not real time anymore.
Users should ensure DWA offers checkpoint support, support different deployment types and ensure code re-usability to make DWA work.
Benefits of using data warehouse automation
- Increased Development Speed
- Reduced Development Costs
- Improved Consistency
- Enhanced Collaboration
- Efficient Metadata Management
- Adaptability to Changes
- Version Control
- Accelerated Deployment
- Scalability
- Code Reusability
- Easier Maintenance
- Rapid Prototyping
