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According to DataKitchen’s 2024 market research, conducted with over three dozen data quality leaders, the complexity of data quality problems stems from the diverse nature of data sources, the increasing scale of data, and the fragmented nature of data systems.
It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. AWS Glue Data Quality generates a substantial amount of operational runtime information during the evaluation of rulesets. Athena provides simple queries to assist you with this task.
In our modern architectures, replete with web-services, APIs, cloud-based components and the quasi-instantaneous transmission of new transactions, it is perhaps not surprising that occasionally some data gets lost in translation [5] along the way. I explore some similar themes in a section of Data Visualisation – A Scientific Treatment.
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