Introduction

Predictive Analytics and Machine Learning are two related areas that are not mutually dependent, whereas Predictive Analytics can be introduced with or without Machine Learning. The differences between these two options are significant in what it can offer to benefit companies in the Business or…

Predictive analytics, prescriptive analytics and the fairly recent offshoot-- discovery analytics-- can all support business decision making. Although the three tools are very similar in that they build off the same analytic foundation, the types of decisions they support are quite different. This one picture explains the differences between the three methods.…

Predictive analytics is a wide field of techniques that share a common goal of predicting future behavior. Choosing the right prediction modeling method is perhaps the most important step in the process, because predictive models are the driving force behind predictive analytics. This picture summarizes six of the most popular methods:…

Generally speaking descriptive analytics is the process of making some sense or adding some structure to a data set, which at times can be very large. For this reason, most discussions referring to “analytics” in business are actually talking about descriptive analytics (Bertolucci, 2013). The most obvious example is when we run descriptive statistics at the beginning of a study, and look at things like the range, mean, median, quartiles, skew and kurtosis.…

Summary:  The annual Burtch Works salary survey tells us a lot about which industries are using the most data scientists and the difference between higher and lower skilled data scientists.  Salary increases show us whether demand is increasing, and finally we take a shot at determining which skills are most in demand.

 …

The Next Generation of Data Science

Quite literally, I am stunned.

I have just completed my survey of data (from articles, blogs, white papers, university websites, curated tech websites, and research papers all available online) about predictive analytics.

And I have a reason to believe that we are standing on the brink of a revolution that will transform everything we know about data science and predictive analytics.

But before we go there,…

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Hold on to your hats data scientists, you're in for another wild ride.   A few months ago, our beloved field of predictive analytics was taken down a peg by the 2017 Hype Cycle for Analytics and Business Intelligence.    In the latest report, predictive analytics moved from the “Peak of Inflated Expectations” to the “Trough of Disillusionment”.  Don't despair, this is a good thing!   The transition means that the silver bullet seekers are likely moving on to the…

Summary:  Over the last eight years predictive analytics has become a fully mature technology with wide adoption among the largest and most successful companies.  The Advanced Analytic Platforms we have to make our work more effective and efficient also show substantial improvement.

Predictive analytics combines the core disciplines of…

Predictive Analytics can be very helpful: algorithms can help retailers decide what quantities of items to order, detect instances of financial fraud or help allocate resources to control the spread of a disease. However, while these predictive tools are helping change lives for the better and provide meaningful insights, we must remember not to let the…

CIO recently published an article that highlighted a survey that was revealing. The survey, conducted in April and May, included 150 executives, from large companies of over 5,000 employees, with responsibility for making business decisions influenced by big data. The survey reports that 98 percent said their company encourages its employees to ground business…

Predictive analytics continues to be a top priority for all types of organizations. And IBM SPSS Modeler continues to be the predictive analytics workbench leading businesses rely on to make predictions with confidence.

IBM is partnering with survey research firm TechValidate to gain a better understanding of how organizations are using SPSS Modeler to help them make…

Summary:  Every year the Strata+Hadoop conference offers a unique opportunity to look into the future and see what trends will dominate our profession in the near term.  Here’s my take.

I’m just back from the Strata+Hadoop Conference in San Jose last week and I’m charged up.  This is a traditionally sold-out crowd of 5,000 Big Data and data science practitioners meeting in the heart of the Silicon Valley once a year to…

Summary:  Predictive analytics are increasingly important to Supply Chain Management making…

Summary:  Higher education has been a little slow on the uptake to use advanced analytics to improve student success but now with the technology that allows us to marry and analyze structured and unstructured data, including streaming data, a number of successful…

The role of predictive analytics in business

Data is everywhere. We generate data when using an ATM, browsing the Internet, calling our friends, buying shoes in our favourite e-shop or posting on Facebook. Companies collect this data en masse in order to make more informed business decisions, such as:

• Which customers should participate in our promotional campaign…

Here's a different angle on a much analyzed question at the heart of our professional activities.  In this article, Steve Miller of Inquidia tackles how NoSQL has changed our traditional understanding of Predictive Analytics and Data Science.  You might also look back at our previous post How NoSQL Fundamentally Changed Machine Learning.

Here's the beginning…

This 30 minute video aims to demystify predictive analytics and present the IBM SPSS predictive analytics portfolio. The contents of the video are as follows:

• Evolution of Analytics 5:45
• Why is Predictive Analytics Important? 11:35
• Demystifying Predictive Analytics 21:30
• IBM…