dbt-customer-journey-analysis
trino_data_mesh
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| dbt-customer-journey-analysis | trino_data_mesh | |
|---|---|---|
| 1 | 1 | |
| 9 | 8 | |
| - | - | |
| 0.0 | 1.8 | |
| 3 months ago | almost 3 years ago | |
| MIT License | - |
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dbt-customer-journey-analysis
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Customer Session Analysis Using dbt and RudderStack
dbt_project.yml - Every dbt project has a dbt_project.yml file. These are written in YAML and define common conventions and properties. For our project, the highlights from this page include the name, version and that we want our models to be materialized as views.
trino_data_mesh
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What even is data mesh
Not central to the main ideas of this article, but if you want to have a data mesh that is self-service, why force folks to use a particular storage medium like a data warehouse? That still requires centralization of the data.
Why not instead have a tool like Trino (https://trino.io) that allows you to let different domains use whatever datastore they happen to use. You still would need to enforce schema, but this can be done in tools like schema registry as mentioned in the article along with a data cataloging tool.
These tools facilitate the distributed nature of the problem nicely and encourage healthy standards to be discussed and the formalized in schema definitions and catalogs that remove the ambiguity of discourse and documentation.
Nice example is laid out in this repo of how Trino can accomplish data mesh principles 1 and 3 (https://github.com/findinpath/trino_data_mesh).
What are some alternatives?
dbt-sessionization - Using DBT for Creating Session Abstractions on RudderStack - an open-source, warehouse-first customer data pipeline and Segment alternative.
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
lightdash - Self-serve BI to 10x your data team ⚡️
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
dbt-spotify-analytics - Containerized end-to-end analytics of Spotify data using Python, dbt, Postgres, and Metabase