Many moons have passed since my last conference report: let’s do this. I will follow Steven Sinofsky’s style and try to keep this fact-based, saving a few more subjective thoughts for the end. I attended the INFORMS Big Data Conference in San Jose, representing Frontline Systems. At the conference we announced the release of the newest version of Analytic Solver Platform.
This was the very first INFORMS Big Data Conference. INFORMS was originally focused on “operations research” aka optimization aka prescriptive analytics. In recent years, it has embraced analytics more broadly: the spring “practice conference” was rebranded as a “Business Analytics” conference, an analytics professional certification program was rolled out, and last week INFORMS introduced an analytics maturity model for organizations. Holding a “big data” conference is a natural extension.
The conference was relatively small. There were between 15 and 20 exhibitors, including Frontline. The two biggest guns were SAS and FICO. There were several booths that were connected to academia: a couple of graduate programs and a booth for a company run by students. There were also several booths by smaller analytics and/or big data firms, mostly offering web-based experiences for authoring and visualizing predictive models. I think it is fair to say that the majority of the exhibitors have an analytics, as opposed to a big data, emphasis.
There were several technology workshops on Sunday, followed by two days of talks. Monday’s keynote was given by Bill Franks, Chief Analytics Officer at Teradata and author of Taming The Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics. Tuesday’s keynote was given by Michael Svilar of Accenture. The talks were divided into several tracks, among them Big Data 101, Case Studies, and Emerging Trends. The talks in the Big Data 101 track were generally well attended. The attendance in other tracks varied widely. In general, talks given by people from “cutting edge” Analytics 10.0 organizations such as Kaggle were quite popular.
Diego Klajban, the founding director of Northwestern University’s MS in Analytics, gave a nice overview of the basic Hadoop stack beyond basic Java-based MapReduce, in particular Pig and Hive. This talk, along with others in the “Big Data 101” track, functioned as mini “survey courses” in various aspects of practicing analytics on Big Data platforms. These talks were helpful for framing technologies and concepts, weaving them into a much more coherent totality.
Paul Kent, VP of Big Data at SAS, gave a talk in the “Emerging Trends” track titled “Big Data and Big Analytics – So Much More Gunpowder!” Paul’s talk focused on four themes: abundance, Hadoop, SAS on Hadoop, and Big Data ideas for organizations. We find ourselves in an “era of abundance” because the cost of storing information has become less than the cost of making the decision to throw it away. We can use this data to answer questions that have not even been formulated at the time of data collection. Paul summarized the Hadoop ecosystem which supports the collection and processing of such data. He went on to describe several SAS offerings which interact with Hadoop in various ways. It was interesting to me to learn how many SAS procedures are now supported “on node” for high performance, among them HPMIXED, HPNEURAL, HPFOREST, HPSVM, and so on. SAS’s continued investment in Hadoop is reflective of a more general challenge: how can organizations realize the potential of Big Data and “Big Data Analytics” when they often have large existing investments in “good old fashioned” storage and analytics.
Paul provided his own definition of Big Data: it is “the amount of data or complexity that puts you out of your comfort zone”. Indeed I heard several different definitions of Big Data at the conference. This variety is indicative of the buzz that surrounds Big Data, particularly among commercial organizations looking to position their offerings.
Frontline has long been in the business of providing analytics solutions to business analysts, and has had a strong presence at various INFORMS conferences for years. I spent a lot of time at the Frontline booth talking to students, professors, business analysts and consultants. Our booth had lots of traffic, and it was interesting to note both how many familiar “INFORMS faces” came by, as well as the number of people who had never heard of Frontline before. In this sense, the INFORMS Big Data conference achieved its mission of connecting the traditional analytics and big data communities. It was interesting to note how many questions there were about Excel’s capabilities. Many did not seem to realize that Excel’s row and column limits increased years ago, and that PowerPivot can bring in much larger data sets with ease – let alone features offered in the recently released Power BI. The hype cycle has largely left Excel behind.
In short, the conference was worth Frontline’s time. We were able to tell the story of not only our most recent release (go get it!) but also Frontline’s overall value proposition. INFORMS Big Data was a nice first bridge between two communities that really should be one. The conference, bluntly, should be much more interesting in a couple of years time, as hype diminishes and case studies increase.