Business Objectives OLAP Online Analytical Processing 
AWS Big Data
AUGUST 6, 2024
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.
Jet Global
SEPTEMBER 4, 2020
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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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.
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.
AWS Big Data
MARCH 7, 2023
Data repository services Amazon Redshift is the recommended data storage service for OLAP (Online Analytical Processing) workloads such as cloud data warehouses, data marts, and other analytical data stores. Data subscription and access is fully managed with this service.
AWS Big Data
AUGUST 1, 2024
The data warehouse is highly business critical with minimal allowable downtime. A successful migration can be accomplished through proactive planning, continuous monitoring, and performance fine-tuning, thereby aligning with and delivering on business objectives.
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