Introduction to Data Analysis in Foundry8. Exercise Summary
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8 - Exercise Summary

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Learning Objective Coverage

  1. Review primary data types available for analysis in Foundry.

    • Tabular data
  2. Choose the optimal Foundry applications for desired analytical outcomes.

    • Contour
    • Code Workbook
  3. Check on the lineage, freshness, usage, and health of the following Foundry data types:

    • Tabular
    • Ontology
    • Geospatial
    • Time series

What You Learned

  • A Foundry dataset is a collection of columns, rows, schema, and values built with user-defined logic.
  • When dataset build logic runs, it executes one of several transaction types to produce a tabular structure common to most data platforms in the industry.
  • The Dataset Preview application gives you access to a dataset's build history and details, among other important information.
  • You can use the Dataset Preview's preview table to understand the data structure and to quickly explore dataset values.
  • Foundry enables you to construct data transformation pipelines that execute on a schedule that can be monitored for freshness, quality, and other measures. As an analyst, you can review these health checks to validate the data you're working with.
  • Contour is a low-code/no-code interface for analysis and dashboarding of large-scale tabular data that is not mapped to the Ontology.