Frameworks can contribute on many levels.
A competent framework should be the foundation for any data management solution but it also makes sense to lay a good foundation for all of your machine learning and analytics use cases. Create an agile but robust foundation to accelerate all of your use cases.
But we can also use frameworks for non-technical aspects of our work such as how to work with data governance and security as well as how we create analytical products and manage them.
- Understand how frameworks can be used to accelerate technical implementations
- Understand how non-technical frameworks such as data governance framework or requirement framework can be utilized to speed up all of the work around the technical implementation.
- Understand how to work with frameworks without creating bottlenecks and rigid structures.