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

AWS Big Data

MARCH 7, 2023

Consumption This pillar consists of various consumption channels for enterprise analytical needs. It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

Jet Global

OCTOBER 22, 2020

Power BI provides users with some very nice dashboarding and reporting capabilities. Unfortunately, it also introduces a mountain of complexity into the reporting process. It updates a dedicated database against which you can perform reporting and analytics. Within the data warehouse paradigm, there are two divergent approaches.

Modeling 52

Modeling OLAP Reporting Sales 52

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

CIO Business Intelligence

JANUARY 20, 2023

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Business intelligence examples Reporting is a central facet of BI and the dashboard is perhaps the archetypical BI tool.

Business Intelligence 142

Business Intelligence Dashboards Data mining OLAP 142

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. Live models run queries directly against the data source.

Modeling 52

Modeling OLAP Data Warehouse Cost-Benefit 52

Jet Global

MAY 4, 2021

As the first in-memory database for SAP, HANA was revolutionary, bringing together the best characteristics of both traditional online transaction processing and online analytical processing.

Reporting 52

Reporting IT Finance Data Warehouse 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

IBM Big Data Hub

SEPTEMBER 25, 2023

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. It can ingest data from offline batch data sources (such as Hadoop and flat files) as well as online data sources (such as Kafka).

OLAP 90

OLAP Data Lake Data-driven Snapshot 90