Build an "ELT simplified Stack" repository to pull Github data, put it into BigQuery, and play around with it using dbt and Prefect.

Build a full data stack that creates a table snapshot from a database and stores it in an Amazon S3 bucket as a JSONL file using Airbyte and then loads the snapshot file to a preferred data warehouse.

Learn how to use PyAirbyte to extract data from Github, followed by a series of transformations and analyses to derive meaningful insights from this data. In particular, we demonstrate PyAirbyte capabilities for extracting data incrementally.

Learn how to use PyAirbyte to extract data from Google Analytics 4, followed by a series of transformations and analyses to derive meaningful insights from this data.

Learn how to use PyAirbyte to extract cryptocurrency data from CoinAPI.io, followed by a series of transformations and analyses to derive meaningful insights from this data.

Learn how to use PyAirbyte to extract cryptocurrency data from CoinAPI.io, and load it to Snowflake, followed by a series of transformations and analyses to derive meaningful insights from this data.

Learn how to leverage PyAirbyte and use Postgres as a Cache, while running in a Google Colab only. It installs packages on the system and requires sudo access.

Streamline healthcare data integration with Airbyte's AI Assistant and FHIR API connector. Simplify workflows and improve insights.

Learn how to build a GitHub documentation chatbot with PyAirbyte and PG Vector for seamless data retrieval and enhanced user experience.

Discover how to build efficient knowledge management systems using PyAirbyte and vector databases for streamlined data access.

Learn to build efficient data pipelines using Airbyte, dbt, and DuckDB. A comprehensive guide for data engineers with practical implementation steps.