Business Objectives OLAP Optimization 
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. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age. Data Lakes.
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AWS Big Data
AUGUST 1, 2024
This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, business intelligence (BI), and ML. The data warehouse is highly business critical with minimal allowable downtime.
Jet Global
AUGUST 14, 2019
Enterprise businesses cannot survive without robust data warehousing—data silos can rapidly devour money and resources, and any business still trying to make sense and cobble together ‘business intelligence’ from multiple reports and inconsistent data is rapidly going to lose ground to those businesses with integrated data and reporting.
Jet Global
MARCH 5, 2019
Business intelligence, by definition, “includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance” in a business environment. What are some of the core components of business intelligence?
AWS Big Data
MARCH 7, 2023
They should also provide optimal performance with low or no tuning. 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.
Jet Global
OCTOBER 2, 2019
Enterprise businesses cannot survive without robust data warehousing—data silos can rapidly devour money and resources, and any business still trying to make sense and cobble together ‘business intelligence’ from multiple reports and inconsistent data is rapidly going to lose ground to those businesses with integrated data and reporting.
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