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This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, business intelligence (BI), and ML. This makes sure the new data platform can meet current and future business goals.
Nonetheless, many of the same customers using DynamoDB would also like to be able to perform aggregations and ad hoc queries against their data to measure important KPIs that are pertinent to their business. Deriving business insights by identifying year-on-year sales growth is an example of an onlineanalyticalprocessing (OLAP) query.
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