datapine

NOVEMBER 27, 2019

That way, any unexpected event will be immediately registered and the system will notify the user. However, businesses today want to go further and predictive analytics is another trend to be closely monitored. 4) Predictive And Prescriptive Analytics Tools. Prescriptive analytics goes a step further into the future.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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

Rocket-Powered Data Science

MARCH 19, 2021

The vast scope of this digital transformation in dynamic business insights discovery from entities, events, and behaviors is on a scale that is almost incomprehensible. Traditional business analytics approaches (on laptops, in the cloud, or with static datasets) will not keep up with this growing tidal wave of dynamic data.

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

CIO Business Intelligence

JULY 5, 2022

What is business analytics? Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. What is the difference between business analytics and business intelligence? Prescriptive analytics: What do we need to do?

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Rocket-Powered Data Science

MARCH 10, 2020

Entities are the nodes in the graph — these can be people, events, objects, concepts, or places. Each of those cases deeply involves entities (people, objects, events, actions, concepts, and places) and their relationships (touch points, both causal and simple associations).

Metadata 250

Metadata Machine Learning Prescriptive Analytics ROI 250

Rocket-Powered Data Science

JULY 19, 2023

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

CIO Business Intelligence

NOVEMBER 14, 2022

They generally leverage simple statistical and analytical tools, but Power notes that some OLAP systems that allow complex analysis of data may be classified as hybrid DSS systems. Commonly used models include: Statistical models. These models are used to establish relationships between events and factors related to that event.

Data mining 144

Data mining Data-driven Statistics OLAP 144