Predictive Analytics

Big Data journey / shutterstock

While much around big data remains hype, many companies are in the fledging stages of drawing value from their big data corpus, and given an army of discussions and opinions around the topic, it’s still hard to find a clear roadmap to arrive at the Big Promise.[read more]

Real-time predictive analytics

In my presentation to the Strata Santa Clara 2013 conference earlier this year, my goal was to give a succinct (under 20 minutes!) explanation of three terms that are too often used as mere buzzwords: predictive analytics, real time, and big data. Here's an excerpt.[read more]

Big Social Data

From eating and drinking to watching entertainment to reading, just to name a few, the social conversations of consumers often reveal tremendous insight on their interests, activities, likes, dislikes, attitudes and behaviors simply as a byproduct of their ‘off-line’ engagements while engaging online.[read more]

perception gap

Consumers believe Sears is just for tools and electronics; is this the perception Sears wants to portray? What is Kroger doing better than others are? Walmart tweets way more frequently than other brands, and consumers reciprocate. 4 brands, 1 week and 100,000 Tweets: this infographic lays it all out for you.[read more]

Facebook & big data analytics

Facebook has massive data analytics capabilities and it has a lot of data - big data. It has our personal details, our likes, our updates, our pictures and videos. However, my big question here is: are they overstepping the mark by exploiting this (even very personal) data?[read more]

Predictive analytics whiz: Dr. Eric Siegel

In this interview, Social Media Today's Henry Spethmann speaks with Dr. Eric Siegel -- author of the new book "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die" -- about what predictive analytics is and how it can be applied to a number of different disciplines.[read more]

Anthony Goldbloom, Founder and CEO of Kaggle (Image courtesy of Kaggle.com)

What do brilliant data scientists, roller derby enthusiasts, and Prince William lookalikes have in common? You can find all three at Kaggle, a company whose mission is to bring together the top data scientists in the world to solve complex problems. Anthony Goldbloom is the company’s founder and CEO.[read more]

Predictive analytics for retail (Image Source)

Here's a true business success story that sheds bright light on the awesomeness of big data. It substantiates the notion that you should store every last iota of data – because you don’t know every pattern [read: opportunity] that might be found or explored.[read more]

long-range planning details / shutterstock

Research shows that one useful improvement is integrating long-range planning with the budgeting process. Our research shows that companies that incorporate individual capital projects and major business initiatives as discrete elements of the long-range plan get better results.[read more]

big data security

Today's security systems still have long ways to go before being fully integrated in true Big Data sense. Security professionals need to be able to get increasing value from the data they already collect and analyze, on top of the data they still are not getting. Here are some key considerations.[read more]

predictive analytics / shutterstock

A couple of weeks ago I attended Predictive Analytics World (#PAWCON), where much of the discussion surrounded “big data” and how to leverage analytics within environments that contain large, complex, and real-time related data. Here are some of the takeaways.[read more]

big data sources / shutterstock

Why is big data valuable? Because it’s big? Not really. The value of any dataset is determined by the quality of information you can extract from it. The key to value in big data is the detail. In other words, the value of big data is in the small stuff.[read more]

one-number forecasting

You can't have the supply chain building to X, the sales force selling to Y, and the financial folks counting on revenue of Z. This is an invitation for disaster. But is the imposition of a single forecast number across the whole organization any less insane?[read more]

Predictive modeling / shutterstock

Anyone can build a bad model, but to build a good model, don’t we need to know what the algorithms are doing? The answer, of course, depends on the role of the analyst. I contend, however, that for most predictive analytics projects, the answer is “no.” But that's not the whole story.[read more]

Big Data & CRM / shutterstock

In November of 1998, when the IT revolution in Enterprise Solutions was about to take off and companies had started investing in ERP or CRM systems in a major way, I thought it was just a matter of time before Predictive Analytics went mainstream. I was wrong. Is 2013 the year?[read more]