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 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

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

CIO Business Intelligence

FEBRUARY 16, 2023

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration.

Unstructured Data 104

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 104

AWS Big Data

MARCH 26, 2024

Unified customer profile Graph databases excel in modeling customer interactions and relationships, offering a comprehensive view of the customer journey. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Sisense

JUNE 30, 2020

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. Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. Visualizations: past, present, and future.

Visualization 93

Visualization Analytics Dashboards Data-driven 93