What are the 5 Pillars of Data Observability?
In a data-driven era, companies need correct and efficient data as their decision-making tool. Nevertheless, data quality and reliability cannot be solved with occasional checks; they need strong data observability. Data observability creates a complete view of information well-being and the condition of the pipeline.
Key Pillars of Data Observability
Data observability is one of the fundamentals of data analysis. Below are the five main pillars of data observability that you should know.
Freshness
Freshness is concerned with the degree of currency of your data. It assists companies in identifying any lag in data pipes so that it can guarantee that stakeholders are operating using the latest and appropriate information.
Data freshness is important since it is used in time-based applications such as real-time data analytics, reporting, and decision-making.
Distribution
The pillar will concentrate on the statistical features of your information, including the range, averages, and frequency of your data. …
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