article thumbnail

Can Data-Driven Accounts Receivable Management Strengthen Client Relationships?

Smart Data Collective

The benefits of data analytics in accounts receivable was first explored by a study from New York University back in 2007. Identify routinely tardy customers with predictive analytics. Companies can use their predictive analytics models to decide how to resolve issues with tardiness.

article thumbnail

Make Every Sprint Count with DevOps Analytics

Sisense

DevOps first came about in 2007-2008 to fix problems in the software industry and bring with it continuous improvement and greater efficiencies. And it’s called DevOps analytics. DevOps analytics is the analysis of machine data to find insights that can be acted upon. But is that really true?

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Modernize Using The BI & Analytics Magic Quadrant

Rita Sallam

Like when Oracle acquired Hyperion in March of 2007, which set of a series of acquisitions –SAP of Business Objects October, 2007 and then IBM of Cognos in November, 2007. Q4: Are we going to discuss Predictive types of Analytics in this discussion? In BI we have had our seminal moments too.

article thumbnail

A Big Data Imperative: Driving Big Action

Occam's Razor

All the way back in 2007, I was evangelizing the value of moving away from the "small data" world of clickstream data to the "bigger data" world of using multiple data sources to make smarter decisions on the web. Here's the "bigger web analytics data" picture from 2007… Multiplicity!

Big Data 127
article thumbnail

Knowledge

Occam's Razor

Accuracy, Precision & Predictive Analytics. Multiplicity: Succeed Awesomely At Web Analytics 2.0! Rethink Web Analytics: Introducing Web Analytics 2.0. Data Mining And Predictive Analytics On Web Data Works? Web Analytics Demystified. 2007 Predictions: Web Analytics.

KPI 124
article thumbnail

How to Choose the Best Analytics Platform, and Empower Business-Driven Analytics

Grooper

These requirements include fluency in: Analytical models. Technology – i.e. data mining, predictive analytics, and statistics. Data is crucial to the success of business analytics. Getting Started with Business Analytics. Streamline and strengthen core operations by achieving insight-driven analytics projects.

article thumbnail

Web Analytics: Frequently Asked Questions And Direct Answers

Occam's Razor

The latter, except in rare cases, is hard to do predictive analytics on unless you are a stagnant business. Alex Cohen: How to optimize with sparse data! Oh, and don't be one of the jackhammers who snoops your customer's browser history and does other sub-optimal stuff. or non-U.S.),