Is Big Data Good or Evil?

By Bill Franks, Jul 09, 2014

With all of the lawsuits working through the courts and all of the scary possibilities being discussed in the media, it has led some people to assume that big data is inherently evil. Once you believe that big data is evil, a natural response is to try and shut down the collection and analysis of big data to the maximum extent possible. While big data certainly has risks, it would be a classic case of throwing out the baby with the bathwater if the use of big data is shut down.

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What should be considered when establishing relationships between analytics teams and IT resources and partners?

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Bill Franks, an IIA faculty member and Chief Analytics Officer for Teradata, was recently featured in a webinar discussing approaches to making big data more actionable and profitable by utilizing data visualization tools and strategies. The talk highlighted the important opportunities and level of insight that big data and analytics can provide organizations and shared how visualization tools can better support decision making and lead to discovery of new insights.

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Pursuing innovative analytics through a portfolio funding model isn’t about removing accountability or financial discipline. It is about applying accountability and financial discipline in a way that accounts for the realities of the situation. It is also about providing leeway to the analysts tasked with discovery and innovation to truly try new approaches to improving a business through analytics.

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Quick! Invest in this CBIMBDMLAAS Company

By Bill Franks, May 08, 2014

The new company will be focused on Cloud-Based In-Memory Big Data Machine Learning Analytics as a Service (CBIMBDMLAAS). I challenge readers to find another premise to build a business around that captures as many of the hot trends in the market today as that term does. Just being able to say that mouthful with a straight face is almost certainly worth a first round of funding in the low millions of dollars today as long as even a cursory business plan and light prototype is used to support it. I will have those soon (I promise), but I need your money first to develop the idea further.

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When Machine Learning Isn’t Learning

By Bill Franks, Apr 10, 2014

Terms come in and out of vogue on a regular basis. In recent years, the use of the term Machine Learning has surged. What I struggle with is that many traditional data mining and statistical functions are being folded underneath the machine learning umbrella.

There is no harm in this except that I don’t think that the general community understands that, in many cases, traditional algorithms are just getting a new label with a lot of hype and buzz appeal. Simply classifying algorithms in the machine learning category doesn’t mean that the algorithms have fundamentally changed in any way.

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Big Data’s Big Flip-Flop

By Bill Franks, Mar 13, 2014

It wasn’t too long ago that many people espoused the decline, if not death, of the SQL language and relational database technology in general. As a level set, remember that relational technology stores data into rows and columns and that the way to access relational data is through Structured Query Language (SQL). For a couple of years, there was a full frontal assault on relational approaches from the Hadoop and non-relational crowds. The overhead of placing data into pre-defined rows and columns was deemed too great, compared to storing data within a non-relational environment.

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Hacked by the Internet of Things

By Bill Franks, Feb 12, 2014

The Internet of Things (IOT) has a lot of promise. The data it generates can provide insights into many aspects of our lives that haven’t had data in the past. The applications that run on top of the IOT will be varied and many will have a large analytic component. Just like the value of the Internet itself wasn’t really understood until it was in place, I suspect that we’ll all be surprised at how fast the IOT becomes a part of our lives and how much we value it. However, there is an underbelly to the IOT that has the potential to severely disrupt how much of its potential is realized.

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Analytics Matters!

By Bill Franks, Jan 07, 2014

As we enter 2014, we are in the middle of a fundamental transformation in the way businesses view analytics. Analytics are now seen as core to a business. Analytics matters. I am extremely pleased to see this happen and that people like me no longer have to fight to make the value of analytics visible. We are just starting to see analytics used as the basis for new products and revenue streams. The breadth of decisions analytics support is increasing every day. The next few years are going to provide a lot to blog about and I am looking forward to it.

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Many organizations attempt to achieve “data nirvana” by having 100% complete information for any given business decision. In the customer analytics space, this is sometimes referred to as a “360 degree view of the customer.” However, we really never know everything about our customers. What we call a 360 degree view is really just the most complete view we have at any given time. All of the information we are missing must be inferred or assumed through analytics. The more complete our picture, the less we have to infer, but realistically we are usually inferring far more information than what we have in our possession.

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