Using NSDA to understand query workloads
We are all aware of the inherent value of customer data within the databases that support our applications. This data identifies customers, accounts, transactional interactions and other patterns that are important for understanding customer behaviors and habits – all of which are useful for improving business processes and customer satisfaction. But what about the value of data about the data processing workloads? Is there value in understanding the processing workloads of our customers? What could we do with workload information if we had the ability to easily organize workload data into meaningful categories and groups, and view the dynamics of the processing patterns over time?
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