> For the complete documentation index, see [llms.txt](https://docs.tailer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tailer.ai/tutorial-create-a-first-data-pipeline/introduction.md).

# Introduction

## :map: Overview

In this example, we want to process and analyze data from a fictional retailer called "Iowa Liquor". These data are organized in CSV files named according to a specific pattern including a timestamp, and are streamed at regular intervals into a Google Cloud Storage bucket. We'll first transfer them to a bucket located in a different Google Cloud project, load the data into a BigQuery table, and then prepare the data in order to analyze them with an AI model.

## :man\_student: What you'll learn

* How data flows through a Tailer Platform data pipeline
* Creating JSON configuration files for data operations
* Deploying data operations with Tailer SDK
* Checking information in Tailer Studio

## :tools: What you'll need

* Tailer SDK installed on your local machine (see [Prepare your local environment for Tailer](/getting-started/prepare-your-local-environment-for-tailer.md) and [Install Tailer SDK](/getting-started/install-tailer-sdk.md))
* GCP configured for use with Tailer SDK (see [Set up Google Cloud Platform](/getting-started/set-up-google-cloud-platform.md)) and credentials required to transfer files safely (see [Encrypt your credentials](/getting-started/encrypt-your-credentials.md))
* Access to two projects in GCP on which you have the appropriate permissions
* A terminal to run commands
* CSV files to process (provided at next step)