End-to-End Data Engineering Project

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Thalia Barrera

1:15:32

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01 - Introduction

01 - Transform complex data into insights.mp4

00:45

02 - What you should know.mp4

02:13

02 - 1. Project Overview and Preparation

01 - Project architecture overview.mp4

01:55

02 - Project setup.mp4

02:22

03 - Understanding the Big Star Collectibles database.mp4

03:59

04 - Setting up your data warehouse.mp4

04:45

03 - 2. Data Extraction and Loading

01 - Getting started with ELT tools An introduction to Airbyte.mp4

03:00

02 - Deploying Airbyte for data synchronization.mp4

02:02

03 - Setting up sources and destinations in Airbyte.mp4

03:43

04 - Establishing connections in Airbyte.mp4

03:16

05 - Synchronizing and navigating through data.mp4

03:09

04 - 3. Starting Data Transformation and Modeling

01 - Introduction to data modeling with dbt.mp4

04:03

02 - Understanding the structure of a dbt project.mp4

02:19

03 - Initiating your dbt project.mp4

03:05

04 - Configuring data sources in dbt.mp4

02:30

05 - Challenge Add a freshness check.mp4

01:00

06 - Solution Add a freshness check.mp4

01:11

05 - 4. Data Transformation and Modeling

01 - Creating and customizing your dbt models.mp4

01:54

02 - Reviewing and executing dbt.mp4

03:41

03 - Securing your data with dbt tests.mp4

04:07

04 - Challenge Add tests to the Marts model.mp4

00:50

05 - Solution Add tests to the Marts model.mp4

01:07

06 - Automating documentation in dbt.mp4

03:18

07 - Completing your dbt project A full development cycle.mp4

01:38

06 - 5. Data Orchestration

01 - Introduction to data orchestration with Dagster.mp4

02:20

02 - Integrating dbt models with Dagster assets.mp4

03:10

03 - Integrating Airbyte connections with Dagster assets.mp4

03:03

04 - Materializing assets using Dagit.mp4

01:52

05 - Challenge Add a schedule to your data pipeline.mp4

00:31

06 - Solution Add a schedule to your data pipeline.mp4

01:05

07 - Conclusion

01 - An evolving field.mp4

01:39

Description

The world of data engineering is ever-changing, with new tools and technologies emerging on a regular basis. Building an effective analytics platform can be a daunting task, especially if you’re not familiar with all the tools available. How do you turn scattered, complex data into a model that drives insights and decision-making? In this course, Thalia Barrera teaches data professionals how to implement an end-to-end data engineering project using open tools from the modern data stack. She touches on best practices such as data modeling, testing, documentation and version control and shows you how to efficiently extract, load, and transform data into a unified, analytics-ready format. Thalia shows you how to confidently select and use tools through practical examples—taking you through the construction of a robust data pipeline for a fictional ecommerce company—and how to implement best practices in data engineering.

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Data Science

Thalia Barrera

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Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.