CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.

Data Analytics 131

Data Analytics Diagnostic Analytics Management Analytics 131

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics.

Data Science 85

Data Science Data Analytics Prescriptive Analytics Analytics 85

CIO Business Intelligence

NOVEMBER 14, 2022

Bayer Crop Science has applied analytics and decision-support to every element of its business, including the creation of “virtual factories” to perform “what-if” analyses at its corn manufacturing sites. Commonly used models include: Statistical models. Clinical DSS. These systems help clinicians diagnose their patients.

Data mining 132

Data mining Data-driven Statistics OLAP 132

IBM Big Data Hub

JANUARY 25, 2024

Many managers in asset-intensive industries like energy, utilities or process manufacturing, perform a delicate high-wire act when managing inventory. Consider these questions: Do you have a platform that combines statistical analyses, prescriptive analytics and optimization algorithms? What’s at stake?

Optimization 82

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 82

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve. appeared first on IBM Blog.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts. 2) Data Discovery/Visualization. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Andrew White

JANUARY 11, 2021

As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. As such any Data and Analytics strategy needs to incorporate data sovereignty as per of its D&A governance program. See: Tool: A Living Library of Real-World Data and Analytics Use Cases.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52