# 2.2 - ETL Pipelines in Kestra: Detailed Walkthrough

This week, we're gonna build ETL pipelines for Yellow and Green Taxi data from NYC’s Taxi and Limousine Commission (TLC). You will:

1. Extract data from [CSV files](https://github.com/DataTalksClub/nyc-tlc-data/releases).
2. Load it into Postgres or Google Cloud (GCS + BigQuery).
3. Explore scheduling and backfilling workflows.

This introductory flow is added just to demonstrate a simple data pipeline which extracts data via HTTP REST API, transforms that data in Python and then queries it using DuckDB. For this stage, a new separate Postgres database is created for the exercises.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
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```

The question should be specific, self-contained, and written in natural language.
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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.