Data science

With Watson Studio, after you set up a project and add data to it, you can start analyzing and visualizing your data:

  • If you want to analyze data by writing code, create notebooks.
  • Develop applications in RStudio.
  • If you want to visualize your data without coding, create analytic dashboards.

Jupyter notebooks

Jupyter notebooks give you a lot of flexibility in coding, visualizing, and computing. With notebooks, you run small pieces of code that process your data, and you can immediately view the results of your computation. When you create notebooks in Watson Studio, you can:

  • Choose the runtime environments that best suit your needs or create customized environments.
  • Use any of the many pre-installed libraries and packages that are included in the runtime environment you select, like:
    • Spark libraries
    • Visualization libraries
    • SPSS predictive analytics algorithms
    • Decision Optimization APIs
  • Install any other libraries you need.
  • Code in Python, R, or Scala.
  • Schedule notebooks to run automatically.
  • Share or publish your notebooks.

See Notebooks.


RStudio is an IDE for analyzing data with the R statistical analysis and machine-learning package within Watson Studio. See RStudio.

Analytic dashboards

With analytic dashboards, you can build sophisticated visualizations of your analytics results without writing code. You create analytic dashboards by combining these types of elements on a canvas:

  • Data assets in the project.
  • Graphs to format the display of your data.
  • Widgets such as text, media, web pages, images, and shapes.

You can share a view of your dashboards with anyone. See Analytics Dashboards.

Learn more