Remove Business Intelligence Remove Insurance Remove Online Analytical Processing
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Simplify Online Analytical Processing (OLAP) queries in Amazon Redshift using new SQL constructs such as ROLLUP, CUBE, and GROUPING SETS

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. In this post, we discuss how to use these extensions to simplify your queries in Amazon Redshift.

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Build a real-time analytics solution with Apache Pinot on AWS

AWS Big Data

Online Analytical Processing (OLAP) is crucial in modern data-driven apps, acting as an abstraction layer connecting raw data to users for efficient analysis. It organizes data into user-friendly structures, aligning with shared business definitions, ensuring users can analyze data with ease despite changes.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Consumption This pillar consists of various consumption channels for enterprise analytical needs. It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers.

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Reduce IT Dependence for SAP S/4HANA Reporting

Jet Global

As the first in-memory database for SAP, HANA was revolutionary, bringing together the best characteristics of both traditional online transaction processing and online analytical processing.

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Deploy real-time analytics with StarTree for managed Apache Pinot on AWS

AWS Big Data

Like Pinot, StarTree addresses the need for a low-latency, high-concurrency, real-time online analytical processing (OLAP) solution. Raj provided technical expertise and leadership in building data engineering, big data analytics, business intelligence, and data science solutions for over 18 years prior to joining AWS.