IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

Cloudera

MARCH 2, 2018

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models.

Data-driven 42

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 42

CIO Business Intelligence

JANUARY 20, 2023

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Intelligence 141

Business Intelligence Dashboards Data mining OLAP 141

Sisense

JUNE 30, 2020

When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations. Analytics acts as the source for data visualization and contributes to the health of any organization by identifying underlying models and patterns and predicting needs.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Predictive, the Up but Not Coming Over time, analytics grow and level up. Diagnostic Analytics: No longer just describing.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52