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Quickstart - Analyzing your Data

The purpose of this quickstart guide is to provide you with an understanding of how to query data from the UI for analysis and how to complete this analysis in q/Python and produce basic visualizations of this data.

Pre-requisites

Before you begin, make sure you have:

  • A running instance of kdb Insights Enterprise
  • Followed the Ingesting Data quickstart guide here or have data stored in a queryable database.

Retrieve Data from a Database

In order to make the most of the analytics functionality provided within the Explore Tab you must first retrieve some data stored within your system, this is facilitated in three ways

  • Querying the data using a form based API
  • Querying the data using SQL
  • Querying the data using q
  • Choose an assembly
  • Choose ½ parameters to modify
  • Name the output appropriately
  • Hit Get Data
  • Choose an assembly
  • Define a basic query with ½ conditions
  • Name the output appropriately
  • Hit Get Data
  • Choose an assembly
  • Choose an instance of the db to query
  • Define a basic q query with ½ conditions
  • Name the output appropriately
  • Hit Get Data
Best
  • Include links out to sections around query semantics re. labels etc

You will now have a variable defined within your code editor named based on your defined output variable above

Explore your data

Exploration of your data is facilitated in both Python and q through the use of a code editor with outputs displayed in associated Console, Table and Visual tabs.

The use-case completed with the explore tab should include the following:

  1. An example of applying a number of functions against the data retrieved from the database to derive statistics about the data.
  2. Using this derived data to create a visualization within the visuals tab using Python or q.
  • Create a number of functions to compute interesting statistics/histograms etc about the dataset retrieved
  • Apply the functions to the retrieved datasets within the explore tab
  • View the data in console, table and visual tabs under various conditions
  • Create a number of Python and q functions to via PyKX to compute interesting statistics/histograms about the data retrieved.
  • Make sure to use Python libraries that are included within the explore tab for this
  • View and comment on the data retrieved in the console, table and visual tabs under various conditions