Published: 20 July 2023
Data observability goes beyond traditional monitoring and detection. It also provides robust, integrated visibility over data and data landscape. Data and analytics leaders should adopt this practice and technology that can alert them to issues with their data before they multiply.
Distributed data landscapes, diversity of datasets and high requirements in data quality increase the need for better observability over data quality and data pipelines.
Traditional monitoring tools suggest that you know what you’re looking for. They are insufficient to address new issues that were not previously understood or detected. Data observability technology learns what to monitor and provides insights into unforeseen exceptions.
Data observability is the market spotlight, but it has no standard accepted definition. This has resulted in vendors offering a range of different capabilities branded as data observability, which causes confusion in the market and leads to
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