From the course: End-to-End Data Engineering Project

Getting started with ELT tools: An introduction to Airbyte

From the course: End-to-End Data Engineering Project

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Getting started with ELT tools: An introduction to Airbyte

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- Have you ever struggled with manually extracting and loading data from one system to another? Today I'm going to introduce you to a game changer, ELT tools. Let's begin by understanding what ELT tools are and why they are crucial. ELT stands for Extract, Load, and Transform. These tools help you extract data from a multitude of sources like databases or APIs, and load it into a target system like a data warehouse or a data lake, so then you can transform the data as needed. ELT tools are a core piece of the modern data stack because they replace ad hoc scripting, simplifying the extraction, loading, and optional transformation processes, thereby minimizing errors and maintenance efforts. Now let's focus on one specific tool, Airybyte. Airbyte allows you to extract data from various sources and load it into a wide range of destinations, simplifying the creation and maintenance of data pipelines. Airbyte operates around connectors, which handle the extraction from a source and then loading into a destination. Imagine your company stores data across different platforms like Salesforce CRM, a MySQL database, a Postgres database, and you want to aggregate all of this data for insightful analysis. Well, in this case, Airbyte can provide you with out of the box connectors for all of these and many other systems, enabling you to easily set up a comprehensive data pipeline. For this project, we will focus on using Airbyte to move data from the Big Star collective of Postgres into our data warehouse in BigQuery. Now, how do you get Airbyte up and running? Airbyte uses docker containers, which can be easily managed and scaled. You can deploy the open-source version on your own infrastructure, like on on-premises servers or on Cloud virtual machines. But for the purpose of this course, we will be deploying the open-source version of Airbyte on your local machine. Airbyte also has a Cloud version, which is fully managed, so you don't have to worry about managing the resources yourself. As you can see, ELT tools like Airbyte automate data extraction and loading, allowing data engineers and analysts to focus on tasks that add more value, like data architecture, modeling and analysis. Are you ready to give Airbyte a try? As you can see, tools like Airbyte automate data extraction and loading, allowing data engineers to focus on tasks that add more value, like architecture, modeling, and analysis. Are you ready to give Airbyte a try?

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