In previous posts we gave an overview of business analytics ("The Basics of Business Analytics"-- Part 1 and Part 2) and described how model-driven prescriptive analytics can maximize profit by ...

Analytics has evolved from the basics -- visualizations, historicals and dashboards -- to the more complex with recommendations and predictions of outcomes. Now it's time to step it up and get ...

Understanding your customers when there’s only a handful isn’t too difficult. But as your company grows and the number of customers expands rapidly, it can be overwhelming to keep up with the change.

This ebook, based on the latest ZDNet / TechRepublic special feature, explores how you set up an analytics infrastructure that sees around corners and gives you options to avoid a head-on crash. Read ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. Amilcar has 10 years of FinTech, blockchain, and crypto startup ...

Forbes contributors publish independent expert analyses and insights. Exploring Cloud, AI, Big Data and all things Digital Transformation. Analytics is probably the most important tool a company has ...

Business analytics is the science of using data to build mathematical models and arrive at decisions that have value for a company or organization, Bertsimas says. This is relevant in nearly every ...

Prescriptive analytics is the final stage of business analytics. Learn more and read tips on how to get started with prescriptive analytics. Technology has given us the ability to forecast enterprise ...

To most people familiar with the Salesforce product family, the name Einstein is synonymous with artificial intelligence. But the Einstein brand also encompasses the analytics products, even when ...

Opinions expressed by Entrepreneur contributors are their own. A Boeing 787 aircraft generates half a terabyte of data on an average flight. That’s an enormous amount. Though it’s filled with ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...