Watson Studio on Cloud Pak for Data as a Service
Watson Studio is one of the core services in Cloud Pak for Data as a Service.
Watson Studio provides you with the environment and tools to solve your business problems by collaboratively working with data. You can choose the tools you need to analyze and visualize data, to cleanse and shape data, or to build machine learning models.
This illustration shows how the architecture of Watson Studio is centered around the project. A project is a workspace where you organize your resources and work with data.
You can have these types of resources in a project:
- Collaborators are the people on the team who work with the data. Data scientist tasks include analyzing data and building models. Data engineer tasks include preparing and integrating data.
- Data assets point to your data that is either in uploaded files or accessed through connections to data sources.
- Operational assets are the objects you create, such as scripts and models, that run code to work with your data.
- Tools are the software you use to work with data. These tools
are included with the Watson Studio service:
- Data Refinery: Prepare and visualize data.
- Jupyter notebook editor: Code Jupyter notebooks.
- RStudio: Code Jupyter notebooks in R and R Shiny apps.
- SPSS Modeler: Automate the flow of data through a model with SPSS algorithms.
- Decision Optimization model builder: Optimize solving business problem scenarios.
Other project tools require additional services. See the lists of supplemental and related services.
Watson Studio projects fully integrate with the catalogs and deployment spaces:
- Catalogs are provided by the Watson Knowledge Catalog service
- You can easily move assets between projects and catalogs.
- Catalogs and projects support the same types of data assets.
- Data protection rules are enforced on catalog assets that you add to projects.
- Deployment spaces are provided by the Watson Machine Learning service
- You can easily move assets between projects and deployment spaces.
You can also bring in data, some types of operational assets, and projects from the Gallery.
You can extend the functionality of Watson Studio with these supplemental services, which require Watson Studio to be installed.
|Analytics Engine Powered by Apache Spark||
Automatically spin up lightweight, dedicated Apache Spark clusters to run analytical and machine learning jobs.
These related services are often used with Watson Studio and provide complementary features, but they are not required.
|Watson Knowledge Catalog||
Create catalogs of curated assets with this secure enterprise catalog management platform that is supported by a data governance framework.
|Watson Machine Learning||
Build, train, and deploy machine learning models with a full range of tools.
|Cognos Dashboard Embedded||
Use sophisticated visualizations in an project to identify patterns in your data so you can make timely and effective decisions.
Compatible data sources
See Connection types for a list of data source services that are compatible.