Coding in Dataiku

READ DATASHEET
  • Code
  • Python, R, and SQL
    interactive notebooks
  • Create reusable
    Python or R components
  • Code
  • Python, R, and SQL
    interactive notebooks
  • Create reusable
    Python or R components
Product screenshot showing the interactive python, R and SQL notebooks

Interactive Python, R, and SQL notebooks

  • Discover and plot data with interactive (REPL) notebooks.
  • Integrates Jupyter for advanced syntax coloring and completion (Python and R).
  • Create your own updatable custom reports.
  • Use pre-templated Notebooks to speed up your work.
  • Interactively query databases or data lakes through SQL Notebooks (support for Hive).
Product screenshot showing how to code your own recipes

Code and share your own recipes

  • Use your favorite (big data) programming languages to add arbitrary custom logic.
  • Code your own recipes in Python, R, SQL, Shell, Hive, Impala, Pig, Spark SQL, Spark Scala, PySpark, SparkR or sparklyr.
  • Save your most useful code snippets and share them with other users.
  • Scale your code by submitting Python or R jobs to Kubernetes clusters.
Computer showing a visualization

Code your own visualizations

  • Create your own web-based visualizations using the best Javascript libraries (d3.js, Leaflet, plot.ly, ...).
  • Create advanced web applications with a Python backend.
  • Use Bokeh or Shiny to create compelling interactive visualizations.
  • Keep all your custom web applications secure with API keys management.
Product screenshot showing how to store Python code.

Create reusable components and environments

  • Reuse existing code assets through shared Python or R libraries.
  • Extend native Dataiku capabilities by developing Plugins using R or Python.
  • Create R or Python code environments to ensure reproducibility and compatibilty.
  • Create Python-based custom steps for your Dataiku scenarios.