24 - Exercise Summary

Learning Objective Coverage

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

   • Tabular data
   • Ontology data
   • Geospatial data
   • Time Series data

2. Choose the optimal Foundry applications for desired analytical outcomes.

   • Contour
   • Code Workbook
   • Object Explorer
   • Quiver
   • The Foundry Map

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

   • Tabular
   • Ontology
   • Geospatial
   • Time series

What you learned

• A time series is a collection of data points that can be measured over time.
• You should consider using Foundry’s time series capabilities when you have temporal data that is large-scale, high-frequency, and/or recorded over long periods of time.
• Time series datasets have at least three columns: series ID, value, and timestamp.
• A time series object type is created in the Ontology Manager application and is backed by a time series metadata dataset.
• Before a time series dataset can be accessed as time series, you or your colleagues must create and run a time series sync on that dataset.
• Quiver is Foundry’s core application for time series analytics.
• A dataset with data/time information is not necessarily a qualified time series dataset. Analysts can use Contour, Code Workbook, Quiver, and other Foundry analytical applications to analyze date and time information on tabular and Ontology event datasets without any additional configuration.