CDW Research Hub

MARCH 22, 2019

The analytics solutions set the stage for better business outcomes by: providing a new level of data custody enabling analysis and reporting on critical information. empowering franchisees to use data for business decision-making, and. establishing a foundation for future predictive and prescriptive analytics.

Data Warehouse 66

Data Warehouse Prescriptive Analytics Statistics Big Data 66

IBM Big Data Hub

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. Prescriptive analytics: Prescriptive analytics predicts likely outcomes and makes decision recommendations. It can also be challenging to operationalize data analytics models.

Data Science 85

Data Science Data Analytics Prescriptive Analytics Analytics 85

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 127

Data mining Data-driven Statistics OLAP 127

CIO Business Intelligence

FEBRUARY 16, 2023

The company’s orthodontics business, for instance, makes heavy use of image processing to the point that unstructured data is growing at a pace of roughly 20% to 25% per month. Advances in imaging technology present Straumann Group with the opportunity to provide its customers with new capabilities to offer their clients.

Unstructured Data 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

FineReport

JULY 28, 2021

Definition: BI vs Data Science vs Data Analytics. Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Cloudera

MARCH 2, 2018

And entirely new utility start-ups such as Drift use machine learning technologies to provide customers with cheaper wholesale energy prices by more accurately predicting consumption. In the nonprofit sector, early applications of data analytics and machine learning have mostly focused on improving fundraising and marketing.

Data-driven 42

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 42