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97 Things Every Data Engineer Should Know - by  Tobias Macey (Paperback) - 1 of 1

97 Things Every Data Engineer Should Know - by Tobias Macey (Paperback)

$49.99

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About this item

Highlights

  • Take advantage of today's sky-high demand for data engineers.
  • About the Author: Tobias Macey hosts the Data Engineering Podcast and Podcast.
  • 262 Pages
  • Computers + Internet,

Description



About the Book



"Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges."--



Book Synopsis



Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges.

Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers.

Topics include:

  • The Importance of Data Lineage - Julien Le Dem
  • Data Security for Data Engineers - Katharine Jarmul
  • The Two Types of Data Engineering and Data Engineers - Jesse Anderson
  • Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy
  • The End of ETL as We Know It - Paul Singman
  • Building a Career as a Data Engineer - Vijay Kiran
  • Modern Metadata for the Modern Data Stack - Prukalpa Sankar
  • Your Data Tests Failed! Now What? - Sam Bail



About the Author



Tobias Macey hosts the Data Engineering Podcast and Podcast.__init__ where he discusses the tools, topics, and people that comprise the data engineering and Python communities respectively. His experience across the domains of infrastructure, software, cloud, and data engineering allows him to ask informed questions and bring useful context to the discussions. The ongoing focus of his career is to help educate people, through designing and building platforms that power online learning, consulting with companies and investors to understand the possibilities of emerging technologies, and leading teams of engineers to help them grow professionally.

Dimensions (Overall): 9.0 Inches (H) x 6.0 Inches (W) x .55 Inches (D)
Weight: .79 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 262
Genre: Computers + Internet
Publisher: O'Reilly Media
Format: Paperback
Author: Tobias Macey
Language: English
Street Date: July 20, 2021
TCIN: 1007910576
UPC: 9781492062417
Item Number (DPCI): 247-34-5147
Origin: Made in the USA or Imported
If the item details aren’t accurate or complete, we want to know about it.

Shipping details

Estimated ship dimensions: 0.55 inches length x 6 inches width x 9 inches height
Estimated ship weight: 0.79 pounds
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Q: Who are some contributors to this book?

submitted by AI Shopping Assistant - 5 days ago
  • A: Contributors include professionals from Twitter, Google, Microsoft, LinkedIn, and Stitch Fix, sharing their real-world experiences.

    submitted byAI Shopping Assistant - 5 days ago
    Ai generated

Q: What is the format of the book?

submitted by AI Shopping Assistant - 5 days ago
  • A: The book is available in paperback format, making it easy to read and reference.

    submitted byAI Shopping Assistant - 5 days ago
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Q: What topics are covered in the book?

submitted by AI Shopping Assistant - 5 days ago
  • A: The book covers data lineage, data security, analytical data warehouses, and modern metadata among other essential data engineering topics.

    submitted byAI Shopping Assistant - 5 days ago
    Ai generated

Q: Who is the author of this book?

submitted by AI Shopping Assistant - 5 days ago
  • A: The book is authored by Tobias Macey, who also hosts the Data Engineering Podcast.

    submitted byAI Shopping Assistant - 5 days ago
    Ai generated

Q: What is the target audience for this book?

submitted by AI Shopping Assistant - 5 days ago
  • A: The book is aimed at current and aspiring data engineers, data architects, and related professionals seeking best practices.

    submitted byAI Shopping Assistant - 5 days ago
    Ai generated

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