Remove Online Analytical Processing Remove Optimization Remove Snapshot
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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

Uber’s DNA as an analytics company At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B. With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price.

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Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

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 data warehouse is highly business critical with minimal allowable downtime.

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Financial Intelligence vs. Business Intelligence: What’s the Difference?

Jet Global

This practice, together with powerful OLAP (online analytical processing) tools, grew into a body of practice that we call “business intelligence.” Such BI methodologies are built on a snapshot of what happened in the past. It enabled finance professionals to view, filter, and analyze their data along multiple dimensions.

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Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. An optimal design choice is to use a dimensional model. Building a dimensional model A dimensional model optimizes read performance through efficient joins and filters.