Who are the best NFL players and why? This is a question that NFL teams want to answer, or perhaps they just want confirmation. NFL teams spend a lot of money on scouts to find the best future players, and on staff to determine if their current players are up to par. Teams already have sources to tell them who are the best players and why. So why are some teams beginning to hire data scientists to analyze a players stats to determine his value? How does data science help determine whether a player is good or not?
With football being perhaps the most popular, talked about, and drama filled sport in America, NFL teams invest a lot of money to become the team that everyone talks about, pays to watch, pays to be endorsed by, and generally just pays. The best way to do this is to win a Super Bowl (or have Tim Tebow on your team).
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Data Science in the NFL: Finding the Right Players and Strategies
New Addition to the CAN Offices
In the past 7 months Contemporary Analysis has expanded from 4 to 20 employees, and will easily expand past 50 employees within the next year. To accommodate that growth we have had to expand out offices at 1209 Harney St. Here is an updated look at our offices. (more…)
Innovate with CAN
At Contemporary Analysis, we want help you to be able to innovate. We allow our clients the ability to do this while allowing them to focus on the present, minimize risks, and reach out of thier department. When business’ try to do something in house, instead of leaving it to professionals, it usually results in distraction. When you allow CAN to come in and be a vendor in our area of expertise, it allows your business the freedom to innovate. We want to help you make your company be the company you want it to be. We want to help you work smart.
The Future of Enterprise IT: Tasks & Tools vs. Command & Control
In the past 7 months CAN has expanded from 4 to 20 employees. We have always been focused on providing our employees with the tools they need to accomplish their tasks. We want them to love working and helping other people work smart.
As I plan for CAN’s growth I have been having a lot of conversations about CAN’s IT strategy with vendors and employees. I have come to realize that a conversation about technology is a conversation about how people work, and that Traditional Enterprise IT doesn’t understand the future of work. (more…)
Formula 1 and Predictive Analytics
A couple weeks ago, I discussed the use of predictive analytics in the transportation industry, specifically the use of acoustic bearing monitors to predict bearing failures on Union Pacific freight trains. Today the conversation turns to predictive analytics in a very different type of transportation, Formula One (F1) racing. Download our Case Study on Mechanical Failure and Predictive Analytics.
F1 is to many the pinnacle of motor sports. F1 has the most technologically advanced cars, the most skilled drivers (some compensated $50+ million per year), the most exotic race locations, and yes, the most beautiful paddock girls. Formula One is a closely sanctioned “space race” creating and refining innovative and ground breaking technologies including traction control, anti-lock brakes, direct injection, synthetic oil, kinetic energy recovery systems (KERS), carbon fiber, and computational fluid dynamics (CFD). Many advancements made in technology by F1 teams have contributed to the efficiency and safety of everyday vehicles. (more…)
What Is Data?
We get asked all the time at CAN “what is data?” “Data” is a term to describe facts, processes, or events that are able to be recorded and measured. Whether descriptive or quantitative, nearly anything can be converted into data. Facebook profiles, sales numbers, interest rates, zip codes, twitter tweets, emails, DNA sequences, and flight tracking information are all examples of data – and we have a lot of it. Data is collected from many different places, and while humans can collect data, machines and technology can collect far more and do it quicker. Computing systems are designed to collect massive amounts of data on the processes they observe or facilitate, yet most of this is never used. Data sits idle because no one has figured how to use it. Technology on the processing side and collecting side have nearly caught up and this is starting to make all the difference.
Thanks to these advances in computer processing power and storage capacity, 90% of the data available to humankind were nonexistent 2 years ago. Think about that for a minute. In other words, data are this age’s most abundant raw material. (more…)
How Big Data Can Bring Big Sales / Insurance Industry See Vanlue in Analytics
How Big Data Can Bring Big Sales: The holy grail of retail has been to anticipate what consumers need even before they realize they need it. … Take printer cartridges, for example. There’s nothing worse than having to print a boarding pass with the taxi waiting outside and realizing you’re out of ink. Today, office supply retailers are able to track purchases of customers’ in-store credit cards and rewards cards and, based on purchase history, anticipate when a consumer might need to reorder a product. Marketing can send an email offer for printer cartridges as well as an accompanying promotion for paper, with a guaranteed delivery time of 24 hours. (ZDNet) http://goo.gl/grqOZ
Massachusetts Big Data Initiative: The initiative will lead to a grants-matching program for research and development into big data, create internships, and launch the Massachusetts Big Data Consortium. That group will bring together academia, industry, and government to foster new big data tools and technologies. And [Governor Deval] Patrick has tasked the Commonwealth to work with the consortium ‘to see how data analytics and applications can help improve the efficiency and effectiveness of government programs and services.’” (IT World) http://goo.gl/mr4x8
— “Chief among the initiatives is MIT’s new big data research center, known as bigdata(at)CSAIL, which will be run out of the school’s Computer Science and Artificial Intelligence Laboratory. The center will focus on data collections that are too big for current information technology systems and will call on industry, government and academic leaders to develop techniques to process, share, store and manage the large amount of data.” (AP) http://goo.gl/TZJJo
Data Driven Knowledge vs. Expert Knowledge: “…data-driven knowledge, as its name suggests, is based upon data—usually, lots of it. A few decades ago, a series of statistical techniques emerged with the intent of uncovering data patterns typically hidden to the human eye. Given that we capture data in an ever-increasing volume today, these techniques are proving indispensable to extracting value from data, making processes repeatable and accurate.”
–“The movie Moneyball exemplifies that really well. In the movie, a group of experienced recruiting agents offer their first-hand knowledge and hunches on which players should be pursued to be part of the team. That is contrasted with a data-driven approach in which knowledge is extracted from the data already available for each player, and a team assembled from that. Although Moneyball chooses one type of knowledge over another, in most cases, we should and do use expert knowledge and data-driven knowledge together.” (Smart Data Collective) http://goo.gl/OGBcL
Salesforce Intros Radian6 Insights for Social Big Data: “Acquired roughly 18 months ago, Radian6 is now expanding with this new platform to tackle sentiments, intents, demographics and more key metrics found within the most commonly used social media channels. The idea is to then convey this information in a way that will better enable business customers to optimize their marketing, customer service, and lead techniques.” (ZDNet) http://goo.gl/OZSXI
Top 10 Categories For Big Data Sources and Mining Technologies: “Since every answer will be different, this means there’s no one-size-fits-all solution. Success lies in recognizing the different types of Big Data sources, using the proper mining technologies to find the treasure within each type, and then integrating and presenting those new insights appropriately according to your unique goals, to enable your organization to make more effective steering decisions.” See the top 10 list here (ZDNet)
Insurance Industry See Vanlue in Analytics: “‘Insurers are investing in analytics, with the survey showing that North American insurers spend about nine percent of their IT budgets on data and analytics,’ says Mark Breading, partner with SMA. ‘What is even more interesting is that business units outside of IT are spending approximately the same amount. All together this represents almost $10 billion in spending each year.'” (Property Casualty 360) http://goo.gl/5X4si
Diapers, Beer, and Data Science in Retail
When asked for white papers or case studies on how predictive analytics works, I often give a few stories on how different industries use analytics to find patterns in their data and then apply that knowledge to their existing data to predict what future trends are going to happen. Learn about how we applied predictive analytics to politics.
I get asked specifically about legends that roam the retail world: the study that found that milk is the most purchased item so it is always in the back of the store, making you walk by everything thing else they have before you get there, the fact that women’s shoes are always on the way to men’s clothes, and the fact that bananas are at the front of stores because they are found to be an impulse buy. The one that seems to get the most requests though is the one that men who buy diapers for their kids are most likely to have beer also in their carts.
It doesn’t seem that far-fetched. (more…)
Big Data In The Travel Industry and More
How To Make The Most Of ‘Big Data’ In The Travel Industry: “There is a ‘big data’ revolution underway in the travel and hospitality industry but travel companies need to be clear about the challenges. … Data analytics is an interesting prospect for the travel sector as so many data streams can be combined. … Business analytics pulls insights from vast databases commonly referred to as ‘big data’. To be successful and maximise the value of this, firms need to be very focused and disciplined.”
— As firms plan to take the plunge, here are some expert recommendations: “Focus on areas where an impact can be made … Understand how to engage with consumers more efficiently … Identify patterns that can lead to insights around consumer acquisition, retention and marketing.” (Hospitality Net) http://goo.gl/Q7dwU
“Business analytics should itself be adaptive and regularly refined by new data that users feed back into the system as that is the whole purpose of predictive modeling…” [Brenda] Dietrich explained that data analysis allows companies to extrapolate outcomes linearly and decide what appropriate action to take next. Those actions also generate new data, which should be fed back into the analytics model so it is continuously refined, improved, and accurate, she said. …This notion of constantly ‘learning from the data’ is a new and exciting development in the analytics space, because it means a company can see, as time progresses in reality, whether it is moving toward X or Y, and decide the next step it should take, she said.” (ZDNet) http://goo.gl/23kaW
“Why is data science relevant?” “Benjamin Franklin is alleged to have said in response to the questioning of the value of the first hot air balloons, ‘What is the value of a newborn baby?’ Actually, data science is probably a long way from the newborn baby stage, although it still has a long way to go before it achieves full maturity.” (Network Computing) http://goo.gl/QdvJ3
Dell Provides Schools and Universities with Predictive Analytics: Schools and universities are turning to Dell’s Education Data Management (EDM) solution, a decision support system, to help personalize student learning, increase retention and graduation rates while improving planning, management and reporting. The solution integrates student performance and operational data with predictive analytics to help educators monitor student progress and intervene when needed to improve success. It tracks each student’s data between schools and over multiple years to help parents and educators monitor student progress and respond to developmental needs or hone in on specific interests and aptitudes. (EON) http://goo.gl/hE3y1
The Hadoop bone’s connected to the SQL bone: “Microsoft has been working with Hortonworks to build a distribution of Hadoop for Windows Azure, its cloud platform, and for Windows Server. Right now the service is available as a cloud service in a by-invitation beta that just entered its third release. … Why would Microsoft be so bullish on technology that is open source, Java-based and largely Linux-facing in pedigree? Most likely it’s because Microsoft runs Bing. By some counts, Bing and Yahoo Search (which is Bing-powered) together have about 30% search market share and Turner announced in his keynote that Bing is now leading Google in search relevance. (ZDNet) http://goo.gl/e8k3N
Adding Second-Tier analysis To Harness Big Data: The real challenge with Big Data is in going from individual siloes of data analytics to a bigger picture that successfully and meaningfully puts those analytics into the full-enterprise context. It’s how we map these analytical islands to each other that ultimately provides the support we need for improved quality in our decisions. … It is important that business and operational metrics be aligned to improve decisions and help ensure business survivability.
— A useful second-tier analysis effectively describes key business functions or processes and business assets, and then correlates operational reports and metrics to them. For example, linking accounts receivable to technology assets to operational practices and metrics can help expose significant enterprise risk. (SC Magazine) http://goo.gl/mPXg7
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