🎉🎉🎉 Best Data Observability tools 2024: RANKED
In this article we dive into the leaders in Data Observability Catageory, What Are Observability Tools and compare them across price and feature completeness.
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🎉 Introduction
The term “Data Observability” really took off as a sector in around 2021 as organi sations had too much money and needed a quick and dirty solution to data quality and monitoring.
That said, the overarching idea with a data collection tool is to ensure that data being used in production has a high degree of “quality”. Quality iself is split into a few different areas. Some of these are accuracy, completeness, normality and well-definition.
I’ve never liked the phrase “Data Quality”. It feels like something an organisation has/prioritises/focuses on but has no definition. By contrast, the above sub-terms are much more concrete and have definitions anyone can understand.
For example, you might say data is “well-defined” if metrics are calculated accurately. In this case, the revenue displayed in a dashboard corresponds to a definition of it, rather than some erroneous calculation. You might say data is complete if all data points included in a dataset reflect all those in reality.
In this article, we’ll dive into the architecture and features of the Top Data Observability Tools. We’ll examine how these features relate, not to “data quality” as a whole but to these explicit components of data quality. We’ll also compare pricing.
