Jet Global

SEPTEMBER 4, 2020

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. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Large, untested workloads run the risk of hogging all the resources.

OLAP 86

OLAP Data Lake Data-driven Online Analytical Processing 86

IBM Big Data Hub

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Customer churn prediction : OLAP can identify customers at risk of churn, enabling businesses to implement retention strategies.

OLAP 57

OLAP Slice and Dice Cost-Benefit Data Warehouse 57

AWS Big Data

AUGUST 1, 2024

Additionally, organizations must carefully consider factors such as cost implications, security and compliance requirements, change management processes, and the potential disruption to existing business operations during the migration. The data warehouse is highly business critical with minimal allowable downtime. Vijay Bagur is a Sr.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99