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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 Visualise 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’ behavioural 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
  • Visualise - Visualise the modeled data with Streamlit
  • 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 visualisation
gantt dateFormat HH-mm axisFormat %M section 1. Upload 1h :upload, 00-00, 1m section 2. Model 1h :model, after upload, 1m section 3. Visualise 1h :visualise, after model, 1m section 4. Track 2h :track, after visualise, 2m section 5. Enrich 1h :enrich, after track, 1m section 6. Next steps 2h :next steps, after enrich, 2m

Prerequisites

Modeling and Visualisation

  • dbt CLI installed or dbt Cloud account available
    • New dbt project created and configured
  • Python 3 Installed
  • Snowflake or Databricks 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 and Databricks will be used for illustration but the snowplow-web dbt package also supports BigQuery, Postgres and Redshift. Further adapter support for this accelerator coming soon!


What you will build

Advanced Analytics for Web Dashboard - with Streamlit or Databricks

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