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Fundamentals of Analytics Engineering

Fundamentals of Analytics Engineering

By : Dumky De Wilde, Kassapian, Gligorevic, Juan Manuel Perafan, Lasse Benninga, Ricardo Angel Granados Lopez, Taís Laurindo Pereira
4.7 (3)
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Fundamentals of Analytics Engineering

Fundamentals of Analytics Engineering

4.7 (3)
By: Dumky De Wilde, Kassapian, Gligorevic, Juan Manuel Perafan, Lasse Benninga, Ricardo Angel Granados Lopez, Taís Laurindo Pereira

Overview of this book

Written by a team of 7 industry experts, Fundamentals of Analytics Engineering will introduce you to everything from foundational concepts to advanced skills to get started as an analytics engineer. After conquering data ingestion and techniques for data quality and scalability, you’ll learn about techniques such as data cleaning transformation, data modeling, SQL query optimization and reuse, and serving data across different platforms. Armed with this knowledge, you will implement a simple data platform from ingestion to visualization, using tools like Airbyte Cloud, Google BigQuery, dbt, and Tableau. You’ll also get to grips with strategies for data integrity with a focus on data quality and observability, along with collaborative coding practices like version control with Git. You’ll learn about advanced principles like CI/CD, automating workflows, gathering, scoping, and documenting business requirements, as well as data governance. By the end of this book, you’ll be armed with the essential techniques and best practices for developing scalable analytics solutions from end to end.
Table of Contents (23 chapters)
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1
Prologue
Free Chapter
2
Part 1:Introduction to Analytics Engineering
5
Part 2: Building Data Pipelines
11
Part 3: Hands-On Guide to Building a Data Platform
13
Part 4: DataOps
17
Part 5: Data Strategy
21
Index

Summary

Working on code together in a team can be challenging; you have seen the complexity of topics such as project organization, task tracking, version control, code formatting, and review and documentation. Your code base is like a living organism, and therefore, maintaining the health of your code base to ensure continuity and consistency in quality can be challenging.

In this chapter, we discussed team member responsibilities, issue and task tracking tools, version control, coding standards, code review, and documentation. You now have a better understanding of the importance of these concepts to ensure proper code quality and make collaborating with team members a lot easier and more error-prone. You also got to know certain tools that can help us to better manage team resources, time, code quality, and the easy onboarding of new users.

In the next chapter, we will have a more detailed look into continuous integration/continuous deployment and delivery, which helps to...

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