Tag Archives: Big Data

A recent article in Information Age named 10 attributes of data leader. Each of the experts quoted discussed just one attribute — in my case, it was separating hype from potential, which is critical when you’re dealing with advanced analytics. Here’s an excerpt of what I wrote for that article: “In the Big Data era, businesses have been told to save every scrap of data because it might turn out to be a valuable clue to customer understanding or business performance. While the cost of storing data has fallen dramatically, it doesn’t represent the true cost of data, which includes ensuring quality, maintaining freshness and mitigating the risk of a breach. “Data leaders are equally discerning about the hype and potential of the analytics used on their data. They focus on the problems the business needs to solve, and investigate new analytic techniques that can make their data “talk” in... [Read More]

Ever wonder how students use analytics to become entrepreneurs? At Georgetown University in Washington, D.C., Students of Georgetown, Inc. – commonly known as “The Corp” – is the largest entirely student-run non-profit corporation in the world, with seven subsidiary companies generating annual revenues in excess of $5 million. As participants in the FICO Academic Engagement Program, Georgetown students were given the opportunity to analyze Big Data from their seven storefronts using some of the industry’s most widely used analytics tools. Watch the video to find out how The Corp leveraged their findings from FICO analytics to monitor customer behavior and improve sales.

In many ways I think 2016 was the year that analytics hit the mainstream. At cocktail parties and in coffee shops, 2016 has been the year that we data scientists suddenly felt a bit like – dare I say it? – rock stars. A quick Google search provides a fascinating data point: “analytics 2015” returned 28.6 million hits “analytics 2016” returned 52.3 million hits Suffice it to say that in 2017, I believe that analytics, and the many domains it influences, will be a non-stop hit machine in terms of generating news headlines and ideas that fascinate us. Here are my predictions: 1. Security/IoT: Is your video cam no longer your friend?  In light of the recent Dyn attack, will 2017 be the year that your IoT device will turn on you? (Think Westworld, Humans, Terminator.) I think the answer is “yes.” In my recent blog, “Real talk: The imminent and... [Read More]

This blog is the final post in this series covering my FICO World keynote presentation, sharing the five steps organizations can take to improve their operational decision-making. 1. Capturing subject matter expertise 2. Intelligent solution creation 3. Faster insight to execution 4. Building institutional memory 5. Greater analytic accessibility In this blog I’ll cover the topic of greater analytic accessibility––which seems like it should be easy to achieve these days, but it is still elusive. In the age of the customer, Big Data is the key to intimately understanding customers’ desires and translating those desires into products, services and personalized experiences. This kind of differentiation is critical to companies’ achieving a competitive advantage. The challenge of Big Data is extracting meaningful, timely and actionable information from it at a reasonable cost. The complexities of doing so mean that two-thirds of businesses derive little or no tangible benefit from the information they hold. Only 4% of companies extract... [Read More]

Timo Berthold, a data scientist working in FICO’s Berlin research center, received the “GOR-Dissertationspreis 2015” prize this week for excellence in Ph.D. dissertations from the German Operations Research Society (GOR), at the society’s meeting in Vienna. GOR’s committee selected Berthold’s dissertation from among 18 worldwide that qualified for the annual award. Furthermore, Berthold’s dissertation was one of the “final four” in the biannual competition for the EURO Doctoral Dissertation Award (EDDA) 2015 presented by EURO, the European operations research society. Berthold describes his PhD research as “located at the intersection of operations research, computer science and applied mathematics.” He has been working on heuristic algorithms for mixed integer linear and nonlinear programming, and how to integrate them into mathematical optimization software to find provably optimal solutions. “I work on algorithms that try to rapidly construct a solution for a given system based on mathematical structures, collected statistics or empirical experience,” Berthold... [Read More]

How can you make best use of the explosion in the availability, complexity, variety and volume of data that occurred in the last decade, which is popularly known as Big Data?  Think!  Don’t be led, blindly, by the data, Big or otherwise. If you’re familiar with Big Data, you will be familiar with the four Vs of Volume, Velocity, Variety and Variability – five if you add Veracity.  The word Big focuses us on the V of volume and talk quickly turns to exabytes and zettabytes (1021 bytes or 1,000 exabytes). You’ll have been told that all those zettabytes offer you great opportunities to gain profitable insights.  But do they? There is an implicit assumption that more data means more information.  There is a danger that if you blindly apply statistical and data mining tools to massive data sets you will be doing little more than numerology.  Given enough data... [Read More]

The world runs on analytics. Every business decision is increasingly made based on data, and every application, service and solution will soon use data analysis to respond to what’s happening now and anticipate what will happen in the future. Yet, the pool of people capable of using and deploying Big Data analytics needs to expand beyond the “quants” – quantitative analysts, data scientists, analytic scientists and the like. Big Data Analytics Software (BDAS) needs to be accessible to all. Just as the desktop computer revolution made computers easy to use, and computer skills attainable for every worker in the ‘80s and ‘90s, the BDAS revolution will put analytics in the hands of every professional in the workplace of the future. Last year IDC reported in its “Trends in Enterprise Hadoop Deployments” that only 32 percent of enterprises had actually deployed Hadoop, with another 36 percent planning to do so in... [Read More]

Most of what we hear today about Big Data concerns the efforts of data scientists within institutions and corporations to leverage massive data sets and powerful analytics to make better operational decisions. But what about Big Data for you and me? Is it possible that we’re becoming data scientists ourselves, without realizing it? For example, if you’ve ever typed a city or ZIP code into Weather.com before taking a trip, you’ve run a sophisticated analytic model against an enormous data set to make a decision – in this case, a decision about whether to pack a swimsuit, an umbrella or a down puffer jacket. And weather analytics are nothing compared with the DIY Big Data analytics being used for fitness and nutrition. My Facebook newsfeed seems to be filled with Strava maps from people I kinda, sorta remember from high school, including analyses of the distances they’ve run, their average... [Read More]

As we settle down with our families to enjoy the winter holidays, many of us will be celebrating various traditions. For many, the culmination of the season is waking on December 25th to the excited cheers of their children as they see their Christmas horde waiting under the tree.  These children believe that Santa Claus, despite carrying what must be a massive load, manages to fly on a sleigh powered by eight reindeer to every home on the planet in one night. The jolly old elf climbs down the chimney and places each present carefully underneath the Christmas tree.  The children wake up on Christmas morning and, ta-da, there are presents. As it turns out, there is a word for this belief:  Apophenia.  According to Wikipedia, Apophenia is defined as the experience of seeing patterns or connections in random or meaningless data. Apophenia was first used to define the “unmotivated seeing of... [Read More]