Analytics

We follow a two-pronged approach for application analytics at LS&T. First, we configure a pipeline to retrieve the data from the application’s database. This pipeline will retrieve the database data, store it in an S3 bucket, and then create metadata for it in AWS Glue. This data can then be queried using AWS Athena. We have a self-deployed instance of Apache Superset where we create analytics dashboards for the applications. Ask in the #ravana-data Slack channel for access to Superset to create your dashboards.

stats-monorepo

This is where the ETL tasks that retrieve data from LS&T application databases live. For more information about the architecture of this project, visit the repo.

Apache Superset

This is where the visualizations of the application data live.