Those who can, do; those who can't, get certified.
Regular AllAnalytics.com readers might recognize this phrasing from our current Point/Counterpoint debate blog on the value of analytics-related certification. Scott Larsen, an independent consultant, exhorted readers, "Go and do something valuable instead of studying for a certification exam." Harkening back to his days as a data analyst at Google, he explained:
When I participated in hiring committees at Google, lots of certifications was generally considered a negative signal. Usually this came from a feeling a mal-prioritized time -- is there nothing better the job candidate could have done with his or her time? Why not accomplish something? You learn so much more by actually getting dirty doing things than you do studying for a test -- show us where you got dirty and what you learned and what you contributed.
Larsen's advice smacked me upside the head as I read about two data-mining competitions GE recently launched on Kaggle. Could participation in such competitions end, or at least diminish, reliance on certifications as a measure of knowledge? I like this idea -- a lot.
As we've previously explained, Kaggle is a data science marketplace that brings together companies or organizations with business challenges and folks with the desire to tackle them. These challenges are always about bringing out-of-the-box thinking to bear, whether to solve society's thorniest issues, address major industry gotchas, or just have a bit of fun with numbers.
In one new challenge, for example, GE aims sky high -- literally. In tandem with Alaska Airlines, it launched the Flight Quest challenge to address what it says is a $22 billion-a-year problem airlines face in managing efficiency. As a GE Aviation director explains in the video below, the goal is to develop an algorithm that delivers real-time flight profiles pilots can use for en-route decision-making. When pilots have such insight at their fingertips, they can make flights more efficient and reliably on time, or at least that's the stated intent.
The second of GE's latest quests deals with a more down-to-earth concern: healthcare. In its Health Quest, GE is working in partnership with Ochsner Health System to "promote an improved health care system experience for patient and family." But this challenge is about operational improvement, not medical care. The aim is to figure out ways to reduce the "$100 billion wasted annually in healthcare inefficiencies, distracting facilities from their primary focus -- patient care," GE said on the challenge site.
These are but two of many examples of the data-mining competitions going on right now on Kaggle, not to mention other venues. I call them out for their newness -- GE launched each within the last week -- and not because there's anything especially compelling about putting your mind to work in solving flight or healthcare inefficiencies. Neither is a bad goal, to be sure, but my point is that either could provide a great showcase for your talent. Even if you don't win a competition, being able to play around with the big-data sets available to contestants could be well worth the effort.
Next time you're tempted to sign up for a certification class, perhaps you ought to first take a gander at Kaggle. It'll make a great addition to your résumé -- and, who knows, you just might end up with some prize money, too.
Do you have any experience with data-mining competitions, of any size or scope? Share below.
Kq writes Such competitions surely can't hurt. Of course, in reality they're a clever marketing avenue for the sponsor. Geting the company name out there for free in press releases is great advertising.
I'd expect that just about anything a big company does these days has marketing in mind, at least partially, to help justify the expense of the public effort. However, given the examples of competitions sponsored by SAS and others mentioned in this thread, I'd presume that the sponsors expect some kind of valuable output from the competition itself.
... Which leads to my next qustion: I'd wonder if there are examples of actual analytics products now deployed, addressing real-world data challenges, that have been developed through these competitions.
Such competitions surely can't hurt. Of course, in reality they're a clever marketing avenue for the sponsor. Geting the company name out there for free in press releases is great advertising. Whether competitions trump certifications is another matter. Both should be advantageous it would seem.
That's a good question, I don't know. The Netflix and Heritage Health contests were corporate-sponsored, but open to all interested parties, academic, corporate, or (moonlighting?) individuals. Because of their length, those two marathons probably did not get many "student teams" participating as a formal part of their classwork, as some of the shorter duration contests do.
@Doug_Dame, your point is well taken. Do you think it'd be fair to call it the largest data mining competition in academia (vs. the corporate world)? I don't know the answer myself, but think there's a distinction worth nothing here.
Although prestigous and senior in tenure, I don't think it's accurate to refer to the Data Mining Cup as "the world's largest data mining competition."
The Netflix competition lasted almost 3 years, at the 8-month mark had 20,000 teams registered of which 2,000+ had made entries, and paid out prizes in excess of $1 million US.
The ongoing Heritage Health Prize, hosted on Kaggle, is a 2 year contest with a max payout of $3,230,000 and a minimum of $730,000 if the grand target is not achieved. It has more than 1400 teams registered and eligible to compete in the current final segment.
@Beth Kaggle does feature most interesting competitions to get smart people involved in solving data problems. I discovered that NASA does it, too. In October it announced the Launch Big Data Challenge Series for U.S. Government Agencies:
The Big Data Challenge series will apply the process of open innovation to conceptualizing new and novel approaches to using "big data" information sets from various U.S. government agencies. This data comes from the fields of health, energy and Earth science. Competitors will be tasked with imagining analytical techniques and software tools that use big data from discrete government information domains. They will need to describe how the data may be shared as universal, cross-agency solutions that transcend the limitations of individual agencies.
Booz Allen Hamilton data science experts Josh Sullivan and Ezmeralda Khalilwill share their lessons learned and best-practices advice for building a data science team and data-driven culture during this A2 Radio episode.
2014 VA Interactive Roadshow -- BostonThe 2014 VA Interactive Roadshow will feature SAS® Data Management and SAS® Visual Analytics experts covering topics like prepping data for VA and VA integration with SAS® Office Analytics. This year's events will keep presentations at a minimum and focus on giving attendees hands-on exposure to the latest version of VA.
Data Exploration & Visualization Get hands-on training that focuses on the critical steps in the process of analyzing data: accessing and extracting data, cleaning and preparing data, exploring and visualizing data. This INFORMS course will use several of the most popular software tools intensively, and provide an overview of the range of software options.
Foundations of Modern Predictive Analytics In this INFORMS course, learn about modern predictive analytics, the science of discovering and exploiting complex data relationships. This course will give participants hands-on practice in handling real data types, real business problems and practical methods for delivering business-useful results.
2014 VA Interactive Roadshow -- AtlantaThe 2014 VA Interactive Roadshow will feature SAS® Data Management and SAS® Visual Analytics experts covering topics like prepping data for VA and VA integration with SAS® Office Analytics. This year's events will keep presentations at a minimum and focus on giving attendees hands-on exposure to the latest version of VA.
LEADERS FROM THE BUSINESS AND IT COMMUNITIES DUEL OVER CRITICAL TECHNOLOGY ISSUES
The Current Discussion
Visual Analytics: Who Carries the Onus? The Issue: Data visualization is an up-and-coming technology for businesses that want to deliver analytical results in a visual way, enabling analysts the ability to spot patterns more easily and business users to absorb the insight at a glance and better understand what questions to ask of the data. But does it make more sense to train everybody to handle the visualization mandate or bring on visualization expertise? Our experts are divided on the question. The Speakers: Hyoun Park, Principal Analyst, Nucleus Research; Jonathan Schwabish, US Economist & Data Visualizer
The hospitality industry gathers massive amounts of customer data, and mining that data effectively can yield tremendous results in terms of improved CRM, better-targeted marketing spend, and more efficient back-end processes. Roger Ares, vice president of analytics at Hyatt Corp., discusses the ways he and his staff use big data.
Charged with keeping track of travel assets, including employees, iJET International relies on data management best-practices and advanced analytics to keep its clients in the know on current and potential world events affecting travel, Rich Murnane, Director of Enterprise Data Operations & Data Architect, told All Analytics in an interview from the 2014 SAS Global Forum Executive Conference.
Jason Dorsey, chief strategy officer for the Center for Generational Kinetics and keynote speaker at last month's SAS Global Forum 2014, describes how Gen Y professionals are enhancing the makeup of multigenerational analytics organizations.
From analytics talent development to the power of visual analytics, All Analytics found a variety of common themes circulating throughout the exhibition floor and session discussions at the 2014 SAS Global Forum and SAS Global Forum Executive Conference events held last month in Washington, DC.
Talking with All Analytics live from the 2014 SAS Global Forum Executive Conference, Eric Helmer, senior manager of campaign design and execution for T-Mobile, discussed the importance of customer data -- starting internally -- in devising the mobile operator's marketing plans.
The big-data analytics market can be a confusing place. Among the vendors vying for your dollars are traditional database management providers, Hadoop startup services, and IT giants. In this video, All Analytics editors Beth Schultz and Michael Steinhart sit down in a Google+ Hangout on Air with Doug Henschen, executive editor of InformationWeek. Henschen discusses use cases for big-data analytics, purchase considerations, and his recent roundup of the top 16 big-data analytics platforms.
At the National Retail Federation BIG Show last month, All Analytics executive editor Michael Steinhart noted a host of solutions for tracking and analyzing customer activity in retail stores. From Bluetooth beacons to RFID tags to NFC connections to video analytics, retailers must find the right combination of tools to help optimize the shopper experience, streamline operations, and boost revenues.
The days when historical shipment trends and gut feelings were enough to forecast retail demand accurately are long over. SAS chief industry consultant Charles Chase outlines the benefits of pulling real-time sales information from point-of-sale and product scanner systems, then flowing that data into dynamic forecasting tools from SAS.
With today's advanced visual analytics tools, you can stream data into memory for real-time processing, provide users the ability to explore and manipulate the data, and bring your data to life for the business.
Dynamic data visualizations let analysts and business users interact with the data, changing variables or drilling down into data points, and see results in a flash. Advance your use of data visualization with tools that support features like auto-charting, explanatory pop-ups, and mobile sharing.
No doubt your enterprise is amassing loads of data for fact-based decision-making. Hand in hand with all that data comes big computational requirements. Can traditional IT infrastructure handle the increasing number and complexity of your analytical work? Probably not, which is why you need a backend rethink. Big data calls for a high-performance analytics infrastructure, as Fern Halper, a partner at the IT consulting and research firm, Hurwitz & Associates, discusses here.
Redbox's bright-red DVD kiosks are all but ubiquitous these days, located in more than 28,000 spots across the country. Jayson Tipp, Redbox VP of Analytics and CRM, provides an insider's look at how the company has accomplished its phenomenal nine-year growth.
InterContinental Hotels Group (IHG), a seven-brand global hotelier, has woven analytics into the fabric of its operations. David Schmitt, director of performance strategy and planning, shares IHG's analytics story and his lessons learned.