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Fundamentals of Analytics Engineering

You're reading from Fundamentals of Analytics Engineering

Product type Book

Published in Mar 2024

Publisher Packt

ISBN-13 9781837636457

Pages 332 pages

Edition 1st Edition

Languages

Concepts

Authors (7):

Dumky De Wilde

Fanny Kassapian

Jovan Gligorevic

Juan Manuel Perafan

Lasse Benninga

Ricardo Angel Granados Lopez

Taís Laurindo Pereira

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Table of Contents (23) Chapters

Preface

1. Prologue

2. Part 1:Introduction to Analytics Engineering

3. Chapter 1: What Is Analytics Engineering?

4. Chapter 2: The Modern Data Stack

5. Part 2: Building Data Pipelines

6. Chapter 3: Data Ingestion

7. Chapter 4: Data Warehousing

8. Chapter 5: Data Modeling

9. Chapter 6: Transforming Data

10. Chapter 7: Serving Data

11. Part 3: Hands-On Guide to Building a Data Platform

12. Chapter 8: Hands-On Analytics Engineering

13. Part 4: DataOps

14. Chapter 9: Data Quality and Observability

15. Chapter 10: Writing Code in a Team

16. Chapter 11: Automating Workflows

17. Part 5: Data Strategy

18. Chapter 12: Driving Business Adoption

19. Chapter 13: Data Governance

20. Chapter 14: Epilogue

21. Index

22. Other Books You May Enjoy

Summary

Data governance refers to any task you must do to make your data compliant, secure, accurate, available, and useful. Even though organizations often ignore it, it sets mature data teams apart. It enables you to work towards your strategic goals and reduce the hours wasted maintaining and fixing existing data assets.

In this chapter, we discuss some key topics in governance, such as ownership, data quality, managing data assets, training, and data modeling. A recurrent theme is that building governance roadmaps from scratch is generally not your responsibility. However, analytics engineers are in a privileged position to understand issues with the data and have enough technical knowledge to correct them at the source.

Working on data governance is never going to be easy. You will face resistance to change and need to get buy-in from your stakeholders to ensure the success of your initiatives. However, any goal you achieve will translate into a much better experience for...

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Authors (7)

Dumky De Wilde

Dumky is an award-winning analytics engineer with close to 10 years of experience in setting up data pipelines, data models and cloud infrastructure. Dumky has worked with a multitude of clients from government to fintech and retail. His background is in marketing analytics and web tracking implementations, but he has since branched out to include other areas and deliver value from data and analytics across the entire organization.

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Fanny Kassapian

Fanny has a multidisciplinary background across various industries, giving her a unique perspective on analytics workflows, from engineering pipelines to driving value for the business. As a consultant, Fanny helps companies translate opportunities and business needs into technical solutions, implement analytics engineering best practices to streamline their pipelines, and treat data as a product. She is an avid promoter of data democratization, through technology and literacy

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Jovan Gligorevic

Jovan, an Analytics Engineer, specializes in data modeling and building analytical dashboards. Passionate about delivering end-to-end analytics solutions and enabling self-service analytics, he has a background in business and data science. With skills ranging from machine learning to dashboarding, Jovan has democratized data across diverse industries. Proficient in various tools and programming languages, he has extensive experience with the modern data stack. Jovan enjoys providing trainings in dbt and Power BI, sharing his knowledge generously

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Juan Manuel Perafan

Juan Manuel Perafan 8 years of experience in the realm of analytics (5 years as a consultant). Juan was the first analytics engineer hired by Xebia back in 2020. Making him one of the earliest adopters of this way of working. Besides helping his clients realizing the value of their data, Juan is also very active in the data community. He has spoken at dozens of conferences and meetups around the world (including Coalesce 2023). Additionally, he is the founder of the Analytics Engineering meetup in the Netherlands as well as the Dutch dbt meetup

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Lasse Benninga

Lasse has been working in the dataspace since 2018, starting out as a Data Engineer at a large airline, then switching towards Cloud Engineering for a consultancy and working for different clients in the retailing and healthcare space. Since 2021, he's an Analytics Engineer at Xebia Data, merging software/platform engineering with analytics passion. As a consultant Lasse has seen many different clients, ranging from retail, healthcare, ridesharing industry, and trading companies. He has implemented multiple data platforms and worked in all three major clouds, leveraging his knowledge of data and analytics to provide value

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Ricardo Angel Granados Lopez

Ricardo, an Analytics Engineer with a strong background in data engineering and analysis, is a quick learner and tech enthusiast. With a Master's in IT Management specializing in Data Science, he excels in using various programming languages and tools to deliver valuable insights. Ricardo, experienced in diverse industries like energy, transport, and fintech, is adept at finding alternative solutions for optimal results. As an Analytics Engineer, he focuses on driving value from data through efficient data modeling, using best practices, automating tasks and improving data quality

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Taís Laurindo Pereira

Taís is a versatile data professional with experience in a diverse range of organizations - from big corporations to scale-ups. Before her move to Xebia, she had the chance to develop distinct data products, such as dashboards and machine learning implementations. Currently, she has been focusing on end-to-end analytics as an Analytics Engineer. With a mixed background in engineering and business, her mission is to contribute to data democratization in organizations, by helping them to overcome challenges when working with data at scale

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