📄️ Introduction
An essential part of any customer data setup is shaping the data schema and enriching the customer data with third-party sources. While real-time enrichment is vital for certain datapoints like email quality, for less urgent or aggregate data, using an ETL process—comprising of extraction, transformation, and load steps—works just as well.
📄️ Motivation
Omni ETL runs in your own cloud environment, avoiding costly subscriptions of traditional cloud platforms as data volumes rise. You control the infrastructure, allowing for potential savings by reserving instances. Additionally, Omni ETL operates efficiently even on modest hardware setups due to its minimal resource requirements.
📄️ Installation
Omni ETL provides a separate Dockerized application for each data source. While the installation process remains consistent across all applications, minor custom steps may be required due to special needs in the configuration of individual data sources. Currently all ETL apps write to BigQuery instances. This document will guide you through the deployment of an Omni ETL instance, providing links to tool-specific configurations as necessary.
📄️ Config: Google Search Console
Here you will find specific details related to enabling the Omni ETL micro-application to run regular data syncs from Google Search Console.