Rocket-Powered Data Science

OCTOBER 6, 2023

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. What is the point of those obvious statistical inferences? How does that work in practice?

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

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 134

Data Analytics Diagnostic Analytics Management Analytics 134

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 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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. 2 Unless your demand forecasting is accurate, adopting a reactive approach might prove less efficient. What’s at stake? trillion, up from USD 864 billion in 2019 to 2020.

Optimization 81

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 81

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. Forecasting models. Analytics, Data Science Clinical DSS.

Data mining 137

Data mining Data-driven Statistics OLAP 137

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.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

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. But we are seeing increasing data suggesting that broad and bland data literacy programs, for example statistics certifying all employees of a firm, do not actually lead to the desired change.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52