With the solstice upon us today, we're officially into summer -- the season for sunshine, barbecues, and… predictive modeling.
"Predictive modeling?" you're no doubt wondering. That topic may be frequently on your mind, but it does not typically come up in a list of summer essentials. So imagine my surprise to see it sandwiched between "Theater on the Lake" and "Dining in the Park" in a recent personal email I received from the Chicago Park District (CPD) about things I ought to know as I plan my summertime activities.
Naturally, I couldn't help but click on the Predictive Modeling link. And so I landed on a YouTube episode of Chicago@Play telling me all about how the city is using advanced analytics to measure water quality at 16 of its 24 designated Lake Michigan swim beaches.
The CPD continuously collects data from buoys in the water and weather stations up on light poles to measure factors like rainfall, the water's cloudiness, and wave height, Cathy Breitenbach, the park district's director of lakefront operations, says in the Chicago@Play program. It then runs the streamed data through predictive models to determine whether to declare the water safe for swimming (via green flags on the beaches), issue swimming advisories (yellow flags), or ban swimming (red flags).
The predictive modeling was successfully tested in the offseason and is new for the 2012 beach season, Breitenbach says. "Over the winter, we did statistics work to see if we could… predict bacteria levels using our dataset from the tests that we took -- and it worked!"
With the predictive modeling, the CPD is making its swim safety decisions based on real-time data, not on yesterday's bacteria test results. Previously, Breitenbach says, it took the CPD 18 hours to get results from the lab, "so we were constantly playing catch-up." Now when Chicagoans or visitors head to the beaches and see the green flags waving invitingly, they can wade in with confidence.
Watch the "Predictive Modeling at Beaches" episode for yourself below, and let us know how the cities where you live and work are using predictive modeling to improve life. Share on the message board below.
when it comes to sports, my point is that the human element is perhaps too much for modeling to handle.
I had a mother-in-law once who made a good living by playing the horse races in New Jersey. She kept amazing data records on all the horses and jockeys, and made lots of smart bets (including hedge bets) based on her own mostly mental calculations and intuitions from the horse and jockey data.
Wonder what she'd do today with a knowledge of analytics ... Maybe make her fortune by inventing a killer app?
It'll be helpful to have advance info, too -- rather than arriving for a day at the beach only to discover the yellow or red flag waving. I think a lot of other cities along the Lake Michigan and other lakefronts could earn points from their beachgoers, too, if they set up similar systems.
Very interesting focus article, Beth. Combines my previously stated interests in applications of analytics in the public sector and weather prediction (actually, using weather data to predict water quality).
Can you imagine what we can do with this type of data analysis all over the world. Imagine societies that are wholely dependent on the rain fall to plant crops. This type of measurement might help developing societies know when to fish, what types of fish to catch, what types of crops to plant, especially in areas that experience large drought.
@Callmebob, that Olympic report reminds me of the stuff that comes out before the Super Bowl, World Series, etc....where they "play" the game 1,001 times to come up a prediction on a winner -- and most of the time, the other team wins. OK, maybe not "most of the time," but when it comes to sports, my point is that the human element is perhaps too much for modeling to handle.
Interesting @callmebob! We'll have to see how the predictions play out. I haven't read the PwC piece yet, but definitely will. I wonder if the athletes know the predictions? Could provide some incentive to do better and belie the models.
@Parda, so true. It'll be helpful to have advance info, too -- rather than arriving for a day at the beach only to discover the yellow or red flag waving. I think a lot of other cities along the Lake Michigan and other lakefronts could earn points from their beachgoers, too, if they set up similar systems.
I forwarded the link to several cities in my area that my family visits to play in the water. Although the types of water a bit different I thought maybe it would get them thinking about how predictive modeling could help them with issues like rip tides on the ocean side and the wonder amoeba everyone worries about in the lakes. I'm sure they do the monitoring but I really wonder if they've ever done any modeling.
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
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.
Elizabeth Barth-Thacker, a BI and informatics technology manager at Humana, tells us how her team is creating data transparency and building engagement with the business – with the help of an internal collaboration portal called Humanalytics.
Whether working in major league sports, financial services, or healthcare, analytics, and data, professionals are checking out how visual analytics and high-performance technologies can help them optimize their environments, shrink their cycle times, and improve decision making, as attendees at the recent SAS Executive Briefing in New York share with us.
Jim Davis, SVP and CMO at SAS, talks with us at a recent SAS Executive Briefing about how high-performance analytics and visual analytics take away the concerns over big-data and let companies get down to business with their data.