Tag Archives: #analytics

Today’s real-time data, tomorrow’s forgotten dream

David Bowie releases his new album, The Next Day, this week. I’ve not had a chance to listen to it yet but the title itself was provocative enough for this post. The disciplines of Big Data and real-time predictive analytics present organizations with the ability to understand behaviour at a relentless pace and also predict […]

Continue Reading

Big data should lead to big dreams

Organizations are collecting more and more data every single minute of every day. It’s no secret that Facebook, for example, processes 2.5 billion pieces of content and over 500 terabytes of data each day, pulling in 2.7 billion Likes and 300 million photos per diem. Facebook also scans a whopping 105 terabytes of data each half […]

Continue Reading

When big data just happens

We hear all of the time about big data as a source of “key insights” but we hear less often about big data as something that truly changes how we live our lives. If you consider that big data involves high volumes, velocity and variety of data, you have to believe that information is coming […]

Continue Reading

The cure for Big Data headaches

Pharmaceutical drug discovery can become highly problematic when a company has over a decade worth of test data that needs to be analyzed. How can you expect to visualize 10 years of pharmaceutical test data all at once? Allergan does it everyday. And it matters. All around the world, whenever people meet up for holidays, festivities, […]

Continue Reading

Is your predictive analytics strategy “playing to the gallery”?

I have been managing a few personal blogs for close to a decade now. I have traffic monitoring tools and Google Analytics configured, but I don’t monitor or analyze stuff there often enough. My excuse, though bad, is that I blog as a hobby, not for any business benefit. Plus, I haven’t found the idea […]

Continue Reading

The data gold rush is officially on

Selling data is nothing new. Marketers have engaged in a brisk trade in personal information for many years. The growing ubiquity of data, however, combined with new ways to analyze massive, diverse and fast-moving information increases the value of data significantly. Data is the the fuel for the modern analytics engine. Suddenly, the only thing […]

Continue Reading

Big Data comes in three flavors

In our love affair with all things Big Data we easily forget the nuances that make it more about ubiquitous data than anything else. The oversimplification of the term is what frustrates many. Just last weekend Forrester’s John Rymer penned Big Data: The Worst Category Name Ever. Strong words? Not really. The term Big Data […]

Continue Reading

Big Data must not be an elephant riding a bicycle

Forrester’s John Rymer sums up his opinion succinctly when he says, “Big Data: The worst category name ever.” It certainly has challenges in name and how people conceive of it. Big Data as the hype would have it, I call, “The elephant riding the bicycle.” I’ll give you the seven things you need to consider, […]

Continue Reading

7 career secrets to success as a data scientist

Do a search for “data scientist” in a job search engine, and you’ll find the title is one of the hottest in IT today. With Indeed.com reporting 15000% growth for the role, is the sky the limit for these so-called data scientists? According to the Harvard Business Review-yes. Thomas Davenport and D.J. Patil deemed “data scientist” as […]

Continue Reading

What’s hiding in your data?

I was invited to speak at Forrester’s Digital Disruption Conference in Orlando this week and finished up my time on stage this morning. I was brought in by Forrester Senior Analyst Mike Gualtieri to speak alongside Terradata’s Chris Twogood about the meaning and impact of Big Data. Before taking the stage, the three of us […]

Continue Reading