Welcome to the Advanced Analytics for Web accelerator. Once finished, you will be able to build a deeper understanding of customer behaviour on your website and use your data to influence business decisions.
Here you will learn to:
- Model and Visualize Snowplow data
- using the snowplow-web dbt package and Streamlit
- using our sample data for Snowflake or Databricks (no need to have a working pipeline)
- Set-up Snowplow Tracking and Enrichment
- Apply what you have learned on your own pipeline to gain insights
Who is this guide for?
- Data practitioners who would like to get familiar with Snowplow data.
- Data practitioners who want to learn how to use the snowplow-web dbt package and set-up tracking using their companies website or single page application, to gain insight from their customers’ behavioral data as quickly as possible.
What you will learn
In approximately 8 working hours you can achieve the following:
- Upload data - Upload a sample Snowplow events dataset to your warehouse
- Model - Configure and run the snowplow-web data model
- Visualize - Visualize the modeled data with Streamlit or Databricks notebook
- Track - Set-up and deploy tracking to your website or single page application
- Enrich - Add enrichments to your data
- Next steps - Gain value from your own pipeline data through modeling and visualization
Modeling and Visualization
- dbt CLI installed or dbt Cloud account available
- New dbt project created and configured
- Python 3 Installed
- Snowflake, Databricks, or BigQuery account and a user with access to create schemas and tables
Tracking and Enrichment
- Snowplow pipeline
- Web app to implement tracking
Please note that Snowflake, Databricks, or BigQuery will be used for illustration but the snowplow-web dbt package also supports Postgres and Redshift.
What you will build
Advanced Analytics for Web Dashboard - with Streamlit or Databricks