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You're reading from  Data Observability for Data Engineering

Product typeBook
Published inDec 2023
PublisherPackt
ISBN-139781804616024
Edition1st Edition
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Authors (2):
Michele Pinto
Michele Pinto
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Michele Pinto

Michele Pinto is the Head of Engineering at Kensu. With over 15 years of experience, Michele has a great knack for understanding how data observability and data engineering are closely linked. He started his career as a software engineer and has worked since then in various roles, such as big data engineer, big data architect, head of data and until recently he was a Head of Engineering. He has a great community presence and believes in giving back to the community. He has also been a teacher for Digital Product Management Master TAG Innovation School in Milan, Italy. His collaboration on the book has been prompt, swift, eager, and very invested.
Read more about Michele Pinto

Sammy El Khammal
Sammy El Khammal
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Sammy El Khammal

Sammy El Khammal works at Kensu. He started off as a field engineer and worked his way up to the position of product manager. In the past, he has also worked with Mercedes as their Business Development Analyst – Intern. He has also been an O'Reilly teacher for 3 workshops on data quality, lineage monitoring, and data observability. During that time, he provided some brilliant insights, very responsive behaviour, and immense talent and determination.
Read more about Sammy El Khammal

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Checklist to implement data observability

In this section, we will delve into a comprehensive list of considerations to keep in mind when you embark on the journey of implementing a data observability solution. These questions will not only guide you through your initial project into data observability but also prove invaluable as you progress to more advanced implementations. By carefully addressing these considerations, you will be able to establish a robust foundation for your data observability initiative, one that not only aligns with your organization’s objectives but also harnesses its full potential for maximum benefit.

The questions we need to answer are the following:

  • Which pipeline should I select to start with the implementation?
  • How many applications should I include in the scope?
  • What criteria are important to select the observability tool?
  • How do we define the set of metrics we want to track?
  • How will alerts and notifications be configured...
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Data Observability for Data Engineering
Published in: Dec 2023Publisher: PacktISBN-13: 9781804616024

Authors (2)

author image
Michele Pinto

Michele Pinto is the Head of Engineering at Kensu. With over 15 years of experience, Michele has a great knack for understanding how data observability and data engineering are closely linked. He started his career as a software engineer and has worked since then in various roles, such as big data engineer, big data architect, head of data and until recently he was a Head of Engineering. He has a great community presence and believes in giving back to the community. He has also been a teacher for Digital Product Management Master TAG Innovation School in Milan, Italy. His collaboration on the book has been prompt, swift, eager, and very invested.
Read more about Michele Pinto

author image
Sammy El Khammal

Sammy El Khammal works at Kensu. He started off as a field engineer and worked his way up to the position of product manager. In the past, he has also worked with Mercedes as their Business Development Analyst – Intern. He has also been an O'Reilly teacher for 3 workshops on data quality, lineage monitoring, and data observability. During that time, he provided some brilliant insights, very responsive behaviour, and immense talent and determination.
Read more about Sammy El Khammal