Published: 28 April 2022
As data management architectures evolve and move increasingly to the cloud, data and analytics technical professionals continue to struggle with delivering quality data. Use this research to understand what data quality means and how data management tools work together to achieve high-quality data.
Data and analytics governance platforms can leverage and orchestrate multiple technical capabilities and provide opportunities to automate tasks that align to data quality objectives for accessibility, timeliness, relevance and accuracy.
Data quality is viewed by IT in terms of a narrow definition of data accuracy, as supported by data quality tools. This causes data and analytics technical professionals to lose sight of what data consumers require from data architectures in terms of data quality.
Numerous data quality dimensions can be used to assess data. Organizations that do not understand how to implement and prioritize these dimensions in the context of
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