You're reading from Machine Learning with the Elastic Stack - Second Edition

Product typeBook

Published inMay 2021

Reading LevelBeginner

PublisherPackt

ISBN-139781801070034

Edition2nd Edition

Languages

Python

Tools

Elasticsearch

Concepts

Machine Learning

Authors (3):

Rich Collier

Camilla Montonen

Bahaaldine Azarmi

View More author details

Organizing data for better analysis

One of the nicest things about ingesting data via the Elastic Agent is that by default, the data collected is normalized using the Elastic Common Schema (ECS). ECS is an open source specification that defines a common taxonomy and naming conventions across data that is stored in the Elastic Stack. As such, the data becomes easier to manage, analyze, visualize, and correlate across disparate data types – including across both performance metrics and log files.

Even if you are not using the Elastic Agent or other legacy Elastic ingest tools (such as Beats and Logstash) and are instead relying on other, third-party data collection or ingest pipelines, it is still recommended that you conform your data to ECS because it will pay big dividends when users expect to use this data for queries, dashboards, and, of course, ML jobs.

Note

More information on ECS can be found in the reference section of the website at https://www.elastic.co/guide...

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Machine Learning with the Elastic Stack - Second Edition

Published in: May 2021Publisher: PacktISBN-13: 9781801070034

Authors (3)

Rich Collier

Rich Collier is a solutions architect at Elastic. Joining the Elastic team from the Prelert acquisition, Rich has over 20 years' experience as a solutions architect and pre-sales systems engineer for software, hardware, and service-based solutions. Rich's technical specialties include big data analytics, machine learning, anomaly detection, threat detection, security operations, application performance management, web applications, and contact center technologies. Rich is based in Boston, Massachusetts.
Read more about Rich Collier

Camilla Montonen

Camilla Montonen is a Senior Machine Learning Engineer at Elastic.
Read more about Camilla Montonen

Bahaaldine Azarmi

Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Read more about Bahaaldine Azarmi

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