sas global forum

5月 092012
 

Stanley Fogleman says that SAS can be hard to learn on your own - not because it is a difficult language - but because of the various business requirements. In fact, even college students entering the workforce are often ill-prepared in some ways. That's why Fogleman believes that a SAS mentoring program can be so effective.

Fogleman says that when he first began learning SAS, he had only six months of mentoring - that was the length of a SAS consultant's contract that he was working with. During that time, he could ask any question that he wanted. After that, he was on his own to learn and figure out the courses to take.

Since that time, Fogleman has refined a mentoring program for junior programmers. He believes the plan should span one to two years, have executive buy-in and include SAS users group conferences.  

"Creating a structured learning environment should be the goal of a mentor," said Fogleman.

Here are some of his tips for success:

  • Map training using support.sas.com Learning Paths, training organized by job roles.
  • Provide training milestones and keep track of accomplishments.
  • Make yourself available as a resource.
  • My favorite resources: SAS-L, sasCommunity.org and SAS Samples and SAS Notes
  • Provide coding guidelines.
  • Advocate SAS users group conference attendance and participation.

"I wish more managers knew about the value of  that local, regional and national SAS users group conferences have," said Fogleman. "I can say very confidently that most of the SAS code that I've learned has been at conferences."

What not to do:

  • Micromanage
  • Be a substitute manager
  • Criticize
  • Monday morning quarterback

"It's about guidance. Structured learning is more efficient," said Fogleman. "There are many different ways to solve programming problems, but there are also many blind alleys. A SAS mentor can help programmers avoid the blind alleys."

Read Fogleman's paper for more advice on What is a SAS Mentor? If you are interested in becoming a mentor, I'd suggest you contact Fogleman. In his presentation, he included a slide showing how to structure the learning process and accomplishments.

tags: mentor, SAS Global Forum, sas programmer
5月 092012
 
The SAS Student Ambassadors are a select group of student researchers who have been recognized for using SAS technologies in innovative ways that benefit their respective industries and fields of study.  Recently, this extraordinary group of young researchers met and attended the SAS Global Forum Conference in Orlando and presented [...]
5月 072012
 

SAS already has some cool mobile Business Intelligence apps. Now, Scott McQuiggan tells Anna Brown, in this Inside SAS Global Forum interview, that you can view the really cool high-performance analytics reports that you've created on your desktop - right from your mobile device. Check this out!!

 

 

tags: high-performance analytics, Inside SAS Global Forum, mobile technologies, SAS Global Forum, SAS Visual Analytics
5月 052012
 

It is becoming more and more apparent that social media is a gold mine of unstructured data that is just waiting to be analysed so that the nuggets can be extracted. At SAS Global Forum, I was particularly impressed with the diversified use of sentiment analysis and the exploration that has been conducted into the field of social media. I attended a number of great presentations and an extremely interesting Super Demo on the analysis of consumers’ moods during Super Bowl commercials.

Analyzing passion

The Super Demo detailed how to use mood statements alongside sentiment analysis to measure in more detail the emotion displayed by people - more than would be possible with sentiment analysis alone. For example, the underlying purpose of advertising is to generate a reaction, hopefully positive, to a particular product or service. The key, therefore, is to understand this reaction through the use of social media to determine the best marketing strategies to implement.

Text analytics can be used here to derive the emotions people are displaying through the words and phrases they use on social networking sites such as Twitter and Facebook. From this data, sentiment and intensity (defined here as the “passion” component) can be derived to determine which commercials hit the mark with their targeted audience. Read this blog post by Richard Foley about analyzing sentiment for more information about the Superbowl research.

Predicting outcomes

Another thought-provoking presentation on a novel implementation of sentiment analysis and forecasting was given on the topic of predicting electoral outcomes. The purpose of this presentation and paper was to try to predict the outcomes of popular elections through social media when polling data is not necessarily available. It also demonstrated the ability to validate election outcomes and check for potential instances of fraudulent election administration.

What was interesting (maybe more than the demonstration on popular elections) was the demonstration of this same methodology on the popular television show American Idol!

The four-step methodology given to achieve this through the extraction, validation, analysis, and prediction of outcomes from the relevant social media data was:

  1. Extract a set of Tweets about the candidate of interest.
  2. Filter the Tweets to ensure that the keyword pulls are relevant.
  3. Analyse the Tweets for positive or negative sentiment around a candidate using sentiment analysis.
  4. Predict contest winners based on the aggregate sentiment scores for the candidate of interest over time using forecasting.

This process allows researchers to surface the general opinions of the social sphere at differing time points to determine a view of sentiment before and after a particular event, for example an eviction from the show.

Not only is sentiment analysis crucial for this exploration, but there are also forecasting applications to determine future events given the textual information that has been determined from the sentiment analysis. Check out Jenn Sykes’ full paper, Predicting Electoral Outcomes with SAS ® Sentiment Analysis and SAS ® Forecast Studio. Also take a minute to watch her in this short Inside SAS Global Forum interview.

With regards to the application of sentiment analysis in other sectors, I can see that there is certainly potential here in the financial sector, where there is a great need for information on sentiment from customers, not only for marketing-related activities, but also customer retention and acquisition.

This year’s conference was a fantastic display of what to look forward to in the world of analytics, and the next SAS Global Forum, San Francisco April 28th thru May 1st is already in the diary!

tags: Inside SAS Global Forum, papers & presentations, SAS Global Forum, SAS Sentiment Analysis, social media, text mining, unstructured data
5月 042012
 

Jenn Sykes (you probably remember her from this great sentiment analysis post last year about American Idol), presented Predicting Electoral Outcomes with SAS® Sentiment Analysis and SAS® Forecast Studio at SAS Global Forum 2012. In addition to predicting elections, Sykes tells Anna Brown from Inside SAS Global Forum, that there is a lot of unstructured data in social media that can help forecasters see anamolies that may point to fraud in elections - something difficult to see prior to the election.

She also says this combination of SAS Sentiment Analysis and SAS Forecast Studio could help predict which toys will sell out early at Christmas, who will win an election or which ATMs will run out of cash. Imagine the possibilities!

tags: fraud, Friday's Innovation Inspiration, Inside SAS Global Forum, jenn sykes, papers & presentations, SAS Forecast Studio, SAS Global Forum, SAS Sentiment Analysis, social media
5月 032012
 

According to Carlos André Reis Pinheiro, social networks in communications are easy to understand and detect, so Oi Telecommunications chose that route first when trying to detect fraud.

Community detection for fraud proved to be somewhat different. It is a progressive search, from looking at the entire network to looking at a group of customers and then within those groups to find unexpected behaviors - outliers.

Narrow the field

Pinheiro said that the first step is cleansing the data to remove phone numbers that are constants across the network. Those numbers might include the call center number and extensions from international calls.

Secondly, Oi Telecommunications needed to understand how to group people. “If you look at every small connection, every small call, you will have a huge community,” said Pinheiro. “We needed to understand how to divide people into relevant communities; we needed to define some boundaries.”

Tighten the linkage

According to Pinheiro, large networks, such telecommunications networks, follow a power law distribution, meaning they contain a small number of communities with a large number of nodes and the majority of the communities have only a few nodes. You can change the size of the communities by changing the value of resolutions.

Bigger communities mean more members, but weaker strength in the links that connect them. Conversely, smaller communities have fewer members but stronger links among the nodes. This metric, called modularity, is the average number of distinct connections.

“This may take trial and error to get the right modularity at first to solve your business problem – is it fraud, churn?” said Pinheiro. “My average number of distinct connections is 10, so I’ll try to end up with an average number of members in the communities like 10. With high-performance analytics, you can test many different types of communities.”  

Spotting oddballs

In this research, Pinheiro says that Oi Telecommunications collected three months of data. From the data, they could see those customers who seemed to be committing fraud, flag them and follow them through to the next step. “When you talk about social network, we all think about influence. People are influencing others to follow along in some type of event – like churn or a purchase,” said Pinheiro.

The data from the social network analysis show that in the churn field, the viral effect of communities is very real - 11 percent of churners can play as leaders and they can affect 8 percent of the people they are related to.

“When you talk about purchasing, 14 percent of our purchasers can play as leaders and they can influence 17 percent the entire network,” said Pinheiro.

For analysts, the bad news is that there is no viral effect in fraud. Fraudsters create a community with the express purpose of committing fraud. The good news is that there is no viral effect – fraudsters don’t spread their ideas like those who are thinking of changing providers or who’ve found bargain prices. So, according to Pinheiro, he and his team can just change tactics to search for fraud communities.

Pinheiro says that social network analysis now helped them see the differences in the calling patterns within a community. These differences were measured so that outliers became obvious and investigable.

“Fraud is business,” said Pinheiro. “So there is always this behavior to find and investigate.”

Read Pinheiro’s paper, Community Detection to Identify Fraud Events in Telecommunications Networks. Also read Jodi Blomberg's paper,  Twitter and Facebook Analysis: It’s Not Just for Marketing Anymore, about catching criminals using social media. (You can also watch as Anna Brown interviews Blomberg about her paper in this Inside SAS Global Forum video interview.)

tags: churn, fraud, Oi Telecommunications, papers & presentations, SAS Global Forum, social network analysis
5月 032012
 

Congratulations to all of you who presented at SAS Global Forum. It takes a lot of hard work to put together the research, write a paper and presentation, and then stand on stage and present to a crowd of people you have never met. You are amazing.

From all of those papers, a select few are chosen as Best Contributed Papers.

Here's the list:

Applications Development - Best Contributed Paper

Use the Full Power of SAS in Your Function-Style Macros
Mike Rhoads

Applied Business Intelligence - Best Contributed Paper

Lost in Wonderland? Methodology for a Guided Drill-Through Analysis Out of the Rabbit Hole
Stephen Overton

Honorable Mention
Using SAS® Enterprise BI and SAS® Enterprise MinerTM to Reduce Student Attrition
Matt Bogard, Chris James, Tuesdi Helbig, Gina Huff

Coders' Corner - Best Contributed Paper

Proc Format, a Speedy Alternative to Sort / Sort / Merge
Jenine Milum

Data Management - Best Contributed Paper

Trend Analysis: An Automated Data Quality Approach for Large Health Administrative Databases
Mahmoud Azimaee

Data Mining and Text Analytics - Best Contributed Paper

Combining Datasets Using Exact Character Variables in SAS
Kulwant Rai

Operations Research - Best Contributed Paper

Using SAS® to Measure Airport Connectivity: An Application of Weighted Betweenness Centrality for the FAA National Plan of Integrated Airport Systems (NPIAS)
Hector Rodriquez-Deniz  

Pharma and Health Care Providers - Best Contributed Paper

A Standard SAS® Program for Corroborating Clinical Data Interchange Standards Consortium Error Messages
John R. Gerlach, Ganesh Sankaran Thangavel

Planning and Support - Best Contributed Paper

Successfully On-Boarding SAS Analysts
Aaron Augustine  

Posters - Best Contributed Paper

Put a Little Zip in Your SAS® Program
Louise S. Hadden, Christianna Williams

2nd Place
Wake Up Your Data with Graph'n'Go
Christopher Battiston

Programming: Beyond the Basics - Best Contributed Paper

Seamless Reporting Automation through the Integration of JMP®, SAS®, and VBA
Rachel Poulsen, Raghunathan Chakravarthy

Programming: Foundations and Fundamentals- Best Contributed Paper

Selecting All Observations When Any Observation Is of Interest
Christopher J. Bost

Reporting and Information Visualization - Best Contributed Paper

Quick and Dirty Microsoft Excel Workbooks without Dynamic Data Exchange or the SAS® Output Delivery System
Andrea Wainwright-Zimmerman

SAS® Enterprise Guide®: Implementation and Usage - Best Contributed Paper

Case Study: Implementing and Administering SAS® Enterprise Guide® across the Enterprise as a Solution for Data Access Security
Linda Sullivan, Ulf Borjesson, Evangeline Collado, Maureen Murray

Social Media & Networking - Best Contributed Paper

Analyzing Sentiments in Tweets about Wal-Mart's Gender Discrimination Lawsuit Verdict Using SAS® Text Miner
Hari Hara Sudhan Duraidhayalu, Satish Garla, Goutam Chakraborty

Statistics and Data Analysis - Best Contributed Papers

Including the Salesperson Effect in Purchasing Behavior Models Using PROC GLIMMIX
Philippe Baecke, Dirk Van den Poel

Dynamically Evolving Systems: Cluster Analysis Using Time
David J. Corliss

Systems Architecture - Best Contributed Paper

Using Dynamic Views as a Supplement to SAS® Security to Enhance Multiple Levels of Access Requirements to Row-Level Data Upon SAS Server Startup
Christopher Bresson, Marty Flis

tags: papers & presentations, SAS Global Forum
5月 022012
 

If you have ever searched social media - Twitter, the blogsphere, Facebook, LinkedIn, Pinterest - for your favorite topic (I'm guessing it's baby penguins or monster truck racing), then you know that it can be like searching for a needle in a haystack. Imagine how law enforcement officers feel: They are searching for crimes on social media.

Jodi Blomberg tells Anna Brown, in an interview with Inside SAS Global Forum, that law enforcement have it tough when searching for their topics. It's not as easy as working for a marketing agency for Macy's or SAS where you look for terms like #Macy's, #sasgf12. Criminals don't advertise their work with terms like #moneylaundering or #carder. (Twitter users use # to identify what they are talking about at the end of a 140-charactor Tweet.)

In this interview, Blomberg tells how law enforcement uses social media analytics to locate crimes and criminals.

 

Watch live streaming video from sasglobalforum2012 at livestream.com

 

Imagine how effective social media analytics would be at finding baby penguins. Blomberg's paper, Twitter and Facebook Analysis: It’s Not Just for Marketing Anymore, goes into more detail about how you can use this in your organization. Let me know if you have questions. There are many more resources available for you.

tags: Inside SAS Global Forum, papers & presentations, SAS Global Forum, social media, social media analytics
5月 022012
 

Google's Chief Economist Hal Varian says the sexiest job of this decade will be statistician. Anna Brown interviewed George Hurley, a Senior Research Manager, to find out what the big deal is. Take a look at his answer and then tell me why you think being a statistician is the hot job of the decade.

 

Watch live streaming video from sasglobalforum2012 at livestream.com

 

tags: Inside SAS Global Forum, SAS Global Forum, Statistician
5月 012012
 

When David Gumpert-Hersh took over as Vice President of Credit Risk at Wescom Credit Union in 2008, the organization – like so many other financial institutions at that time – was in a bit of a bind.

“There was no data,” he said. “There was literally no data. Zero. So we started from scratch.”

In his presentation at the SAS® Global Forum Executive Conference, Gaining Competitive Edge with Analytics for Credit Risk, Gumpert-Hersh went through a granular account of the “lifecycle of the analytic process.”

At the time he started, there wasn’t an analytic or credit risk department at the organization, so it was up to him to find data, figure out a way to pull it into a system and segment it. To start, Gumpert-Hersh made a few changes.

“I stopped all the pre-approval programs,” he said, referencing the direct mail campaigns that guaranteed a credit card without a credit check or income verification - only needing a signature. “With that you have a lot of inherent risk that you’re taking on that’s not transparent to your risk models.”

It gave Wescom a chance to catch its breath and start collecting data the right way.

Mitigation, then management

In 2011, the pre-approval program began again. This time, Wescom was pricing more accurately for its customers and its risk. As a result, the acceptance rate was triple what Gumpert-Hersh anticipated, which fostered a favorable bump to portfolio loans and an increased engagement with the customer. 

"It turned out to be a huge profitability point that we’d been ignoring for 76 years - since the credit union started,” he said. “It turned intuition on its head, and we started moving further into the detailed analytics.” 

Using analytics also allowed Gumpert-Hersh and his team to use econometrics to evaluate how many of their services were trending, thereby giving signals to the state of the economy. In a graph that laid out econometrics for Q4 2011, he was able to pinpoint the time when things began looking up.

“You could say in the end of 2011 is the first point when you started to see everything together – not just delinquencies, not just rates, not just income – actually turn toward recovery,” he said. “It was kind of a celebratory time.”

The celebration didn’t last too long because the same econometrics allowed his team to see the effects of the European economic downturn. However, projections for next year look promising. “It’s not so good right now, but it’ll get better,” he said.

Mitigation as a relationship builder 

Gumpert-Hersh also touched on Wescom’s credit suspension initiative, which functioned on the premise of temporarily freezing portions of lines of credit rather than closing them. In fact, throughout the economic downturn, Wescom has never closed a line of credit.

It was an opportunity for Wescom to mitigate risk, while also giving credit union members a chance to get back on their feet financially rather than falling deeper into debt. And if their parameters changed, they would get back what they “lost” in suspension, he said.

As a result, exposure at default was reduced by 30 percent, meaning balances in default status were 30 percent less than they would have been – saving Wescom’s bottom line and preventing customers from getting deeper into debt.


Here are two great papers from SAS Global Forum that might interest those of you in the financial services industry and those working in credit risk management:

tags: credit risk, papers & presentations, SAS Global Forum