Good for large teams with large data reiterating on their data projects in various steps.
Use Cases and Deployment Scope
Collaboration is the key aspect in whatever projects we do at our organization. We have people from web development, data science, and ML teams working on projects involving all three domains in a single project. IBM Watson Studio on Cloud Pak for Data is a great asset for the data science team where we work on individual tasks, collaborate with teammates, and share findings and insights. It has all the basic tools required for visualization and modeling the algorithm. The IBM cloud Pak has numerous examples for various use cases.
Pros
- The R studio which is very flexible more than any IDE.
- Testing and developing the model locally before finally publishing.
- Collaborating with teammates on same data.
Cons
- Watson Studio is a little complex for beginners to get started. Paid courses explain them well to beginners.
- Many features that small teams might not use.
Likelihood to Recommend
It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
