Remove Analytics Remove Business Objectives Remove Online Analytical Processing
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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

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. The following diagram is a conceptual analytics data hub reference architecture. External processes are the spokes feeding data to and from the hub. Data repositories represent the hub.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

Each data entity provides an abstract representation of business objects within the database, such as, customers, general ledger accounts, or purchase orders. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

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The Future of AI in the Enterprise

Jet Global

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

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

AWS Big Data

As data volumes continue to grow exponentially, traditional data warehousing solutions may struggle to keep up with the increasing demands for scalability, performance, and advanced analytics. The data warehouse is highly business critical with minimal allowable downtime.

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The Future of AI in the Enterprise

Jet Global

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

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

AWS Big Data

StarTree is a managed alternative that offers similar benefits for real-time analytics use cases. We highlight the key distinctions between open-source Pinot and StarTree, and provide valuable insights for organizations considering a more streamlined approach to their real-time analytics infrastructure.