AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Consumption This pillar consists of various consumption channels for enterprise analytical needs. The focus is on the ease of consumption and integration with consuming services.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

Jet Global

AUGUST 14, 2019

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.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Jet Global

OCTOBER 2, 2019

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.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

AWS Big Data

JUNE 21, 2023

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 online analytical processing (OLAP) query.

Data Warehouse 80

Data Warehouse Data Lake OLAP Cost-Benefit 80