FineReport

JUNE 24, 2021

Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. All BI software capabilities, functionalities, and features focus on data.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

CIO Business Intelligence

NOVEMBER 14, 2022

They emphasize access to and manipulation of large databases of structured data, often a time-series of internal company data and sometimes external data. Model-driven DSS use data and parameters provided by decision-makers, but Power notes they are usually not data-intensive. Model-driven DSS.

Data mining 140

Data mining Data-driven Statistics OLAP 140

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 Lakes.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

JUNE 21, 2023

A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. To house our data, we need to define a data model.

Data Warehouse 94

Data Warehouse Data Lake OLAP Cost-Benefit 94

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 in Amazon S3 can be easily queried in place using SQL with Amazon Redshift Spectrum.

Analytics 82

Analytics Data Warehouse Data Lake Metadata 82