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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Category Archives: Data Mining

10/19
2011

Predictive Analytics on Big Data – What Does the Future Hold?

predictive analytics world Predictive Analytics on Big Data   What Does the Future Hold?The future of targeting and online marketing begins with predictive analytics on big data, according to today’s Predictive Analytics World Session presented by Dr. Usama Fayyad.

Known as the industry’s first chief data officer (his former position at Yahoo!), Fayyad is the current chairman & CTO of ChoozOn Corporation, a consumer deals search engine.

Fayyad really knows big data because he’s been developing technologies and research to harness, process and elicit insights from it for the past 20 years. More specifically, he has helped organizations including NASA, Audience Science, Microsoft and Yahoo! develop data mining technologies and data strategies.

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Filed under: Big Data, Data Mining

10/11
2011

2012: The Year of Big Data in American Politics

data analytics and 2012 politics 2012: The Year of Big Data in American PoliticsGuess who has the hottest job in the 2012 presidential campaign … is it the chief campaign manager for President Obama, Mitt Romney, or any other GOP candidate?

Well, believe it or not, it’s the data mining scientist—or data analyst. No, really. It’s the person who’s responsible for sorting through tons (read terabytes) of big data to track voter behavior and figure out how they’ll vote, if they’ll donate to a particular campaign and whether they’ll try to persuade their nearest and dearest to vote for one candidate over another.

Traditionally, people running presidential campaigns have relyed on telephone polling to determine the collective will of the voters but that could all change during this presidential campaign. According to the blog, 2012 will be the year of big data in American politics—at least for President Barack Obama’s re-election campaign.

It seems the Obama for America campaign is hot on the trail of paid staffers, including analysts and data geniuses, to use their skills to make a real difference in his campaign to be a second-term president.

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06/22
2011

Top Three Challenges for Data Miners

top three challengs for data miners Top Three Challenges for Data MinersAn article in the June issue of Data Analytics magazine discusses the results of the 2010 Rexer Analytics annual data mining survey. Different from surveys that target analytics executives, the Rexer survey goes direct to the data miners themselves. In the 2010 survey, data miners identified their top challenges and many discussed how they’ve tried to work around or overcome obstacles. In both cases, a clear theme emerges that has very little to do with statistics and a lot to do with engaging and communicating with business users.

1. Dirty Data
It’s no surprise to Rexer that dirty data tops the list, because it has been at the top of the list for the past several years.  It’s probably no big surprise to anyone who reads our blog either, because we’ve discussed in several posts how dirty data can derail data analytics and business intelligence projects. In the Rexer survey, many data miners provided input as to how they’ve tried to overcome the problem, and a clear theme emerges: involve business users. Data miners use descriptive statistics and visualization to assist business users in understanding their data and identifying problem areas.  Helping users understand their data “hands on” helps everyone gain a shared understanding of the quality of the data. This can help manage expectations about the potential results of a data modeling exercise given data quality and convince data owners to create action plans to improve quality.

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06/10
2011

“Data Geeks” in Demand as Salaries Climb in 2011

Data Mining Salary Up in 2011 300x300 Data Geeks in Demand as Salaries Climb in 2011OK, so your company has taken a big step toward operating more efficiently by implementing a business intelligence (BI) solution—or it’s planning to install one in the near future. But if that’s the case then you’re probably also going to have to enlist the help of a new type of worker—a “data geek”—to make sense of all that BI data.

At least that’s the opinion of Jorge Garcia, a research analyst at Technology Evaluation Centers Inc.  Organizations that use business analytics software can improve their decision-making processes if they have the right set of tools and the right people—those data geeks—in place, Garcia says.

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04/27
2011

New Degree Programs Help Meet the Demand for Analytic Talent

degree programs New Degree Programs Help Meet the Demand for Analytic TalentAccording to the U.S. Bureau of Labor Statistics, the demand for people with analytics skills and expertise is growing much faster than other occupations. BLS forecasts more than 20 percent growth in demand for mathematicians, operations research analysts and management analysts across all industries. To help provide the educational background needed for many of these roles, colleges and universities are introducing new degree and certificate programs focused on data mining, data analytics and business intelligence. Below are a few examples:

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03/23
2011

Data Mining and Predictive Analytics Contest Has a $3 Million Prize

Predictive Analytics Cash Contest 300x241 Data Mining and Predictive Analytics Contest Has a $3 Million PrizeIn a post earlier this year entitled, “Data Mining Improved Company’s Revenue By 187%,” we described how the knowledge that led to a 187% improvement in revenue was hiding inside data that Assurant Solutions collected, but did not use. A California managed care provider also believes there is hidden knowledge inside data that they have, but aren’t using. The Heritage Provider Network hopes to discover knowledge in patient healthcare data that can prevent hospital stays and reduce healthcare expenses. To find that knowledge, they’re turning to the public for help and offering a $3 Million prize to the team who can come up with the best and most accurate solution.

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02/22
2011

Data Mining Improved Company’s Revenue By 187%

Call Center 150x150 Data Mining Improved Companys Revenue By 187%Assurant Solutions sells insurance policies on credit card payments, for example if you lose your job or become disabled. Their customer service center takes calls from people who see the monthly add-on fee on their bill and call to cancel.  Metrics are simple. If a customer does not cancel, the customer is “saved.” If a customer is saved by downselling or upselling to a different plan, a percentage of revenue is saved.  Assurant’s objective was to increase the percentage of saved customers and to increase the percentage of saved revenue. To do this, they agreed to abandon their assumptions about how the customer service center should operate in favor of what data mining revealed. MIT Sloan Management Review published this article detailing their astounding results.

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02/15
2011

The ABCs of Desktop Data Mining

desktop computer 150x150 The ABCs of Desktop Data MiningWhat is it?

“Data mining” can be described as the process of finding patterns and relationships in data.  There are several different flavors of data mining, using different methods and pursuing different results.  For example, a data mining project might look for:

  • associations (interconnected events or information items)
  • sequential relationships (one event leading to another)
  • affinities (events that occur in clusters, information items that are frequently found together)

There are also two levels of approach to data mining.  “True” data mining is an IT-intensive process, using complex algorithms and very sophisticated procedures to discover deep and/or unexpected patterns in data.  At the business level, however, data mining is often viewed more generally, as a way of exploring data to answer questions and support analysis.

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