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You're reading from  Data Observability for Data Engineering

Product typeBook
Published inDec 2023
PublisherPackt
ISBN-139781804616024
Edition1st Edition
Concepts
Data Processing
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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
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

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Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

anomaly detection 128

multiple indicators deterministic cases 129

simple indicator deterministic cases 129

time series analysis 130

anomaly detection case study 130, 131

multiple indicators deterministic cases 133, 134

residuals and anomaly detection 136

seasonality analysis 136

simple indicator deterministic cases 131-133

time series analysis 135, 136

trend analysis 136

application analysis 52

application analyzer method

advantages 56

disadvantages 56

application lineage example 121

data observability method, advantages 128

impact analysis 123

issue, detecting 122

issues, preventing 127

root cause analysis 124-126

troubleshooting 127

application observability 34

application run 75

log 76, 77

applications 72

data...

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Data Observability for Data Engineering
Published in: Dec 2023Publisher: PacktISBN-13: 9781804616024
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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

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