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Open-Source Data Observability with Elementary — From Zero to Hero (Part 1)

6 min readSep 10, 2024

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Data observability and its importance have often been discussed and written about as a crucial aspect of modern data and analytics engineering. Many tools are available on the market with various features and prices. In this 2 part article, we will focus on the open-source version of Elementary, one of these data observability platforms, tailored for and designed to work seamlessly with dbt. We will start by setting up from zero and aiming to understand how it works and what is possible in different data scenarios by the end of part 2. Before we start, I also would like to disclose that I have no affiliation with Elementary, and all opinions expressed are my own.

In part 1, we will set up the Elementary and check how to read the Elementary’s daily report. If you are comfortable with this part already and interested in checking different types of data tests and which one suits bests for which scenario, you can directly jump into part 2 here:

I have been using Elementary for quite some time and my experiences as a data engineer are positive, as to how my team conceives the results. Our team uses Elementary for automated daily monitoring with a self-hosted elementary dashboard. Elementary also has a very convenient cloud platform…

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TDS Archive
TDS Archive

Published in TDS Archive

An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

Sezin Sezgin-Rummelsberger
Sezin Sezgin-Rummelsberger

Written by Sezin Sezgin-Rummelsberger

Data Engineer | Writing articles on Data & Analytics Engineering | MSc | https://de.linkedin.com/in/sezinsezgin

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