Jet Global

APRIL 20, 2020

This practice, together with powerful OLAP (online analytical processing) tools, grew into a body of practice that we call “business intelligence.” Past performance and current conditions are critically important; but without a view to the road ahead, business leaders risk being blindsided by unexpected developments.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

IBM Big Data Hub

SEPTEMBER 25, 2023

Large, untested workloads run the risk of hogging all the resources. As a result, they continue to expand their use cases to include ETL, data science , data exploration, online analytical processing (OLAP), data lake analytics and federated queries. In some cases, the queries run out of memory and do not complete.

OLAP 86

OLAP Data Lake Data-driven Online Analytical Processing 86

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. Dashboards Response time Service level for data refresh.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

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

Sisense

FEBRUARY 16, 2021

Data warehouses provide a consolidated, multidimensional view of data along with online analytical processing ( OLAP ) tools. OLAP tools help in the interactive and effective processing of data in a multidimensional space. Jinja provides a powerful automatic HTML escaping feature. Sandboxing.

Modeling 52

Modeling OLAP Data Warehouse Cost-Benefit 52

Sisense

SEPTEMBER 3, 2019

First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). For example, if you are using Redshift solely for analytics purposes, you can scale the cluster up with more nodes when this happens and resume work once it is complete.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78