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 77

Data Science Data Analytics Prescriptive Analytics Analytics 77

CIO Business Intelligence

JANUARY 20, 2023

Trusted and governed data: Modern BI platforms can combine internal databases with external data sources into a single data warehouse, allowing departments across an organization to access the same data at one time.

Business Intelligence 135

Business Intelligence Dashboards Data mining OLAP 135

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

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 43

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 43

Jet Global

MAY 1, 2023

Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52