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Solution overview OnlineAnalyticalProcessing (OLAP) is an effective tool for today’s data and business analysts. It helps you see your mission-critical metrics at different aggregation levels in a single pane of glass. You can remove this filter in your test to view data for all regions.
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. The success criteria are the key performance indicators (KPIs) for each component of the data workflow.
OnlineAnalyticalProcessing (OLAP) is crucial in modern data-driven apps, acting as an abstraction layer connecting raw data to users for efficient analysis. Business metrics – Providing KPIs, scorecards, and business-relevant benchmarks. Anomaly detection – Identifying outliers or unusual behavior patterns.
If the exploratory work needs to move on to testing and production, they can plan appropriately. As a result, they continue to expand their use cases to include ETL, data science , data exploration, onlineanalyticalprocessing (OLAP), data lake analytics and federated queries.
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