AWS Big Data

JUNE 21, 2023

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. These types of queries are suited for a data warehouse.

Data Warehouse 82

Data Warehouse Data Lake OLAP Cost-Benefit 82

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 135

Data mining Data-driven Statistics OLAP 135

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. Lastly, it’s billed in a pay-for-what-you-use model, and provisioning is straightforward and quick.

Big Data 68

Big Data Data Warehouse Advertising OLAP 68

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Jet Global

NOVEMBER 5, 2020

That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. For more powerful, multidimensional OLAP-style reporting, however, it falls short. OLAP reporting has traditionally relied on a data warehouse.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74