Analyzing your data

Data analysis within kdb Insights Enterprise is facilitated from the UI primarily through use of the Query Window. Aimed principally at data scientists and data engineers it provides an isolated location where you can prototype analytics and explore available data in an area which will not impact production workloads.

The scratchpad provides you with a location to analyze data you have queried from the database. Analysis can be completed in Python or q allowing you to to create functions for use throughout kdb Insights Enterprise, interrogate your data to learn more about its properties or to prototype pipelines prior to deployment to production environments. Querying the database is completed through use of a query builder, SQL or via q allowing you flexibility in choosing how you access your data. During analysis users can inspect their data via a console output, a table formatted return or through generation of visualization in the visuals tab.

Use the guides below to discover how to use the Query Window to query data, generate analytics and produce visualization using those analytics:

• Querying Data from the database
• Developing Python code within the scratchpad
• Developing q code within the scratchpad
• Visualizing output graphically and in the console.