Page tree
Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 24 Next »

Full access to the Datalake offers all stored COVID-19 Datalake data while allowing the researcher to use whatever analysis framework they so choose with their own compute resources. This level offers the fastest startup time while ensuring access to all data. Once you learn how to query data in C3, that data can be streamed to your compute resources where you can use your language and tools of choice.

Pros:

  • Full access to C3 Datalake.
  • Ability to use any language and tools of your choosing.

Cons:

  • C3 credentials and tenant/tag required.
  • All data must be streamed to your local compute resources.

Getting Started

Please see the DTI Readiness checklist. If you pass the checklist, you're ready to start learning!

Training Curriculum:

Once you have completed the DTI Readiness checklist, you're ready to start learning.

These hands on resources give you an in-depth guide on how to start using C3 immediately followed by explicit examples showing how to use C3 Documentation, Types, Timeseries, and Metrics. Each of these examples is grounded in the C3 Covid-19 Datalake. Additionally, links to appropriate official C3.ai Documentation and Videos are dispersed throughout the quickstart guide.

These C3.ai created materials give more information

  • C3 Getting Started Guide
    • Not all sections of the Getting Started Guide are necessary.
      We list the necessary sections here:
      • Introduction to C3 AI Suite
      • Architecture

        • Basics
        • Understanding Clusters, Tenants, and Tags
        • Model-driven Architecture
          • Types
          • Fields and Methods

          • Type Inheritance

      • Time Series Data Section
      • Metrics Section

Optional Resources/Training:

Some users may find these additional resources helpful at this stage.

Challenge Problems

This set of problems exercises the concepts defined under the 'Level 2' header. You should be able to solve these problems by fetching types, executing existing Metrics, creating new Metrics, and may require processing outside of the C3 platform for instance, to produce plots.

  • What is the age distribution of coronavirus patients? Does this vary by location?
  • How does likelihood of death change with age and sex?
  • Do coronavirus case reporters agree with each other on how many new cases a given US county or state have? How often do they disagree?
  • Is there a seasonality to case reporting data? What period is it?


  • No labels