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Posts Tagged ‘analytics’

Data Analysis, Predicting the Weather, and Business Decisions

ThunderstormMany people believe that weather impacts us only when it is severe. However, weather impacts people and businesses in a myriad of other ways.

Some of the ways that weather impacts business are obvious. For example, food prices go up after a rash of bad hail, drought, or extreme heat.

Some of those impacts are less obvious. Retail sales can plummet when the weather is bad because nobody wants to be out in the middle of a storm.

The science of weather prediction itself is getting better. National Geographic outlined NOAA’s improved hurricane forecasting software quite recently.

Business is finding ways to turn improved weather data to its advantage. This CNBC report titled “Big Data Companies Try to Outwit Mother Nature’s Chaos” outlines some of those methods.

“While it’s still virtually impossible to predict an event like [the Oklahoma tornado,] the models and forecasts from big data companies can be extremely valuable to a variety of businesses, ranging from retailers to insurers, as they plan ahead.

Earth Risk, for example, focuses on the energy trading market. By focusing in on probability models for extreme heat and extreme cold it can help investors profit in the futures market.

[John Plavan, co-founder and CEO of Earth Risk Technologies] points to the winter of 2011-12, which many traders in the natural gas market expected to be cold, driving up futures prices. Earth Risk’s models, though, showed that the atmosphere wasn’t setting itself up for a high probability of cold weather, letting clients position themselves to make money when natural gas prices declined.”

Some private weather prediction models may even have an edge on NOAA. For example, IBM’s “Deep Thunder” draws its data from multiple sources, including NOAA itself. It also uses Earth Networks, NASA, and the U.S. Geological Survey.

If weather has an impact on your business it is a good idea to learn more about data mining and its many uses. TMA offers a variety of data analytics training courses to help companies learn how to use these powerful tools. Get started with TMAs’ free webinar today.

Solving Municipal Issues with Data Analytics

ChicagoEvery city faces problems and challenges. According to Information Week: Government, Chicago is beginning to turn to basic predictive analysis to solve some of those challenges.

They’re starting small, targeting the variables that lead to garbage cart thefts. The thefts create a surprisingly large drain on city finances.

Data analysis says that the thefts are more likely to occur in areas where alley lights are broken. City officials are responding by devoting resources to these repairs.

The new data analysis system is known as “Windy Grid,” and it’s still fairly simple. Mostly, it handles simple “cause-and-effect” tests on the results of Chicago’s data collection efforts.

However, the city is working to upgrade the system in order to make it a much more useful tool, one that could potentially help Chicago solve bigger problems.

“Developing a full-blown predictive analysis capability is much more ambitious. As envisioned, the system will flag for city leaders…indicators of coming problems including those that, unlike the out-of-commission street lights, they hadn’t considered.

The goal is to apply historical analysis to predict and prevent future problems. ‘We have the bones of this,’ Goldstein says, referring to Windy Grid. The next step is ‘taking it and saying if we’re seeing this in a given neighborhood, what’s likely to happen next?’

Goldstein’s team talks of ways to prevent graffiti, rodents, and garbage cart thefts. But what about Chicago’s more serious scourges, like its alarming homicide rate…or struggling schools?

Graffiti and rodents are mere starting points, says Brenna Berman, an ex-IBMer who’s now first deputy CIO. ‘This is the approach for how this department will be part of the answer for tackling the murder rate or addressing complex emergencies like snowstorms or improving the water infrastructure,’ she says. The harder-to-solve problems will take more data and analysis of more variables, but ‘it’s the exact same story for how you figure out which water mains are going to explode this year, so that we use our limited budget to improve the water infrastructure the right way over the next 10 years.’

Every organization faces challenges, even if few organizations find themselves tackling city-sized problems. The first step in making sense of data collection efforts is to receive the appropriate training. That’s why TMA offers data analytics training courses and a free webinar to help organizations make the most of these powerful capabilities.

In a World Where Data Analysis Predicts Blockbusters

ClapperThe New York Times recently ran an article on the ways data mining is being used in Hollywood to predict sales at the box office. It turns out that there are some tangible factors that pop up in movies that do well vs. those that receive two-thumbs-down from moviegoers.

The industry leader in this enterprise is former statistics professor Vinny Bruzzese.

“Demons in horror movies can target people or be summoned,” Mr. Bruzzese said in a gravelly voice, by way of example. “If it’s a targeting demon, you are likely to have higher opening-weekend sales than if it’s summoned, so get rid of that Ouija Board scene.”

“Bowling scenes tend to pop up in films that fizzle…Therefore it’s statistically unwise to include one in your script. A cursed superhero never sells as well as a guardian superhero, one like Superman who acts as a protector.”

The average Hollywood film costs over $60 million to produce. It stands to reason that execs would want to have some guidance about what works and what doesn’t before investing any money into a film.

Bruzzese’s example only helps to demonstrate how data mining can help isolate what customers really like and want. That means that they have a better experience because companies can then deliver without messy guesswork.

Of course, there are some people who fear that this means that we’ll all be stuck in a world of bland products (and movies). But these fears are unfounded. Data mining is only a tool.

There are a lot of different ways to write movies with targeting demons and guardian superheroes, after all.

The Modeling Agency offers companies the training they need to make the most of advances in data mining no matter what their industry is. Start with TMA’s free webinar, and then move on to other data analysis training courses here.

The Argument for a Data Science Degree

Data science degreeWith the rise in popularity of “data science” as a term and a concept, journalists are increasingly pointing out the lack of a formal data science degree from any university in the country.

This is important because a well-rounded data science degree could produce graduates who are capable of handling all facets of data analytics and data management, rather than the current custom of companies hiring people who may only be skilled in one area of analytics, and training them for the rest.

Recently, Government Technology took the call for a data science degree a step further and outlined 3 key ingredients that such a degree would have to possess to be effective. Writer Tanya Roscorla suggests:

  1. Multi-discipline – the ideal data science education would include mathematics, statistics, computer science and content discipline. This presents a unique challenge for universities, as in order to achieve this mix in the current popular university structure you might have to cross over between several colleges to achieve the well-rounded curriculum.
  2. Graduate-level – undergrads with a focus on one of the four aforementioned disciplines could pursue a graduate data science degree where they’d learn the other three. According to Roscorla’s interview with Jennifer Lewis Priestley, associate professor of statistics and director of the Center for Statistics and Analytical Services at Kennesaw State University, “Young students can’t study all four things at once at an undergraduate level because they don’t have the absorptive capacity to understand all the concepts.”
  3. Research orientation – big data presents big problems, when it comes to analyzing enormous amounts of data and culling the wisdom within it. A data science degree that teaches research would lead to data scientists who can actively seek solutions for performing analytics on rapidly, massively growing data.

For the full article visit Government Technology.

Are you for or against a formal data science degree?

Ready to take your own data analytics education to the next level? Register for a free data mining webinar with The Modeling Agency, or enroll in a comprehensive data mining and predictive analytics training session.

Predictive Analytics Helps Businesses Get Better at Guessing

Predictive AnalyticsPredictive analytics – the use of data mining, machine learning and other techniques to look for patterns in data and make informed predictions – helps companies get better at guessing customer wants, needs and behaviors. In a recent Computing.co.uk article Jim Manzi of Applied Predictive Technologies explained predictive analytics helps companies get “about three percent better at guessing”. That may not seem like a large figure, and the effectiveness of predictive analytics depends on the size of the data and the scope of the project, but even 3% can certainly translate to a lot of cash in the right situation.

Predictive modeling allows companies in any industry to fine tune their sales efforts based on educated guesses what their customers will respond to best. “What we’re trying to do with predictive analytics is to get a little better at what you’re already doing,” said Manzi. “And so really our technologies could  in theory be used to build experiments and from that build models to say that a customer ID is more likely to respond to the following offer than another customer ID.”

Retail operations, banks, insurance agencies and the entertainment industry are just a few types of businesses that use data mining and predictive analytics to increase sales. For some practical examples of data mining, see this post on The Modeling Agency’s blog.

If you’re ready to learn more about how data mining and predictive analytics can work for your company, register for The Modeling Agency’s next free data mining webinar. Or for a more in-depth, hands-on examination, attend an upcoming data mining and predictive analytics training course.