All quiet on the Barnett Front

The Barnett Shale in North Texas hit a historic mark on April 25: Its rig count fell to zero. Two hundred rigs once harvested the 40 trillion cubic feet of natural gas in this massive basin, stretching beneath 17 Texas counties. Today, nothing.183346796

This dramatic silence in North America’s second-largest shale field is echoing across the continent. Oil and gas rig counts have fallen by 540 over the past year. It is a stark reminder that credit risk management is growing in importance as the commodity price downtrend continues.

That echo is heard not just in the oilfield, but in the boardrooms of every oil and gas producer, services firm, pipeline and storage company – and all the other strands in the web of relationships that bring energy to market. The enthusiasm to invest as America became a net exporter of hydrocarbons amidst an unprecedented boom in shale oil and gas recovery has transformed into a single question: What’s our counterparty credit exposure?

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Analytics in the news: the NFL draft

Football field showing 30-yard-lineAs American football teams prepare to select new team members later today, fans and pundits can only guess how the draft will turn out. Will your favorite professional team make good picks? And will your favorite college players go to good teams?

With high stakes and billions of possible outcomes, professional sports team selection seems like an ideal problem for analytics. But is it? The "Moneyball" method has been famously documented in baseball, but football is a very different sport with more interactions between players and fewer individual statistics to track.

What are the experts saying about analytics and the NFL draft? I've put together a short reading list so you can learn all about it before today's draft. Read More »

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How to partner with IT to build a dashboard for community college administrators

It's a common problem in any industry: getting a large number of similar requests for information. But with limited resources and an already overburdened staff, how do you handle it?

At El Paso Coanalysts and IT shake handsmmunity College, analysts from the Institutional Research (IR) team enlisted the help of IT to create a data warehouse and a dashboard to make reports easily accessible for anyone who needed information while at the same time freeing up time for the analysts.

In particular, they needed a dashboard that would display key performing indicators (KPI) including demographics, student performance, college growth and more. In all, they wanted one central place where everyone could go to get accurate, timely information.

Presenters Christina C. Frescas (Research Associate), Angeles Vazquez (Statistical Research Associate), and Carlos Molina-Torres (Sr. Programmer Analyst) discussed the collaborative solution during their session at The Texas Association for Institutional Research (TAIR) conference. Read More »

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Why clinical insights, not budgets, hold the key to value-based healthcare

Right now, National Health Service (NHS) managers and clinicians in the UK are under phenomenal pressure to find big efficiency savings while improving the value of services to patients. Many in the NHS see integrated care as the answer. But the first step is finding innovative ways to increase the value we deliver in all clinical and commissioning decisions. The question is: How? NHS

Well, consider this: Every single thought, action, treatment plan, decision and interaction generates some form of data. The answers NHS leaders need are likely sitting in the masses of patient records, emails, discharge letters, scans and patient notes that litter every clinician’s in-tray and inbox.

The challenge is collating that data in a meaningful, structured manner that makes it readily accessible to decision-makers --  while protecting individual patient's privacy. But that’s just the beginning. Only when a clean data repository has been created, in which different types of information have been translated into digital formats, can decision makers extract the answers they need. Using sophisticated methods that allow them to easily model treatment outcomes for different patient groups, clinicians and managers can gain transformational answers. They can then evaluate investments versus the value of potential outcomes; investigate the efficacy of different management plans; predict demand, and answer many other questions.

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Campaigning to your customer: When elections and marketing collide

185556750It’s almost impossible to avoid election coverage right now, no matter how hard you try. If you’re like me, you’re fleeing to the safety of South Africa’s recently launched Netflix in to order avoid the coverage of the US primaries currently dominating international TV and print news, or South Africa’s local elections which are currently ramping up. But these same elections are eerily echoed by President Frank Underwood’s attempt to finagle his way to re-election in the latest series of Netflix’s House of Cards.

Campaign promises and issues-based pandering are very much part of the campaigning process, and politicians try every method at their disposal to try to influence those “swing voters” who are open to persuasion. But just how far are they willing to go to achieve this goal?

An election campaign is just a (very) expensive marketing campaign

As is becoming clear, in an established democracy like the USA, or even within a new and dynamic one like South Africa, an election is becoming more and more like a marketing campaign in which voters are presented with “offers” of promises made by the candidates. In doing so, they’re tapping into techniques used for years by consumer marketers.

Political candidates and their campaign teams are often forced into making assumptions about voter preferences based on demographic and psychographic information. However, consumer marketers realised years ago that restricting your understanding of customers to such basic information is nowhere near enough, especially given the reams of customer data that’s now available.

Marketers are now moving towards the “segment of one,” where predictive analytics are used to determine each individual customer’s personal brand, product and service preferences, and use this information to tailor unique messages to these customers.

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10 SAS Global Forum speakers to follow on Twitter

Like what you heard at SAS Global Forum? Want to stay in touch with the speakers you met or listened to there? Here's a list to get you started, but please add to it in the comments. Tell us which speakers you've found - and followed - on Twitter.

For extra fun, I've included a tweet by or about each person on the list. You'll find some bonus people to follow if you look closely at those tweets.

1. @michaelraithel conducted a pre-conference workshop on how to be a top programmer, and presented a paper about PROC DATASETS.


2. @annmariastat taught attendees about factor analysis and led a second presentation for biostatisticians.

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Sleep: Your legal performance enhancer

Arianna Huffington

Arianna Huffington speaks at the SAS Global Forum Executive Conference

Our society lives under a collective delusion that burning out is a requirement to success.

We’ve been conditioned to believe that sacrificing family, relationships and what’s personally important opens the door to achievement. But how can you be an effective leader, run a successful company or properly manage employees when you aren’t functioning at your optimal potential?

Arianna Huffington came to that conclusion the hard way, when she found herself with a broken cheek bone after collapsing from complete exhaustion. With a bloodied face, Huffington had to ask herself one tough but honest question: “Is this what success really has to look like?”

If you look at science, the answer is no. Modern science proves that if individuals take care of themselves they are more effective, yet we rarely act with that proven research in mind.

“Everyone knows the exact battery life remaining on their cellphones,” said Huffington, “But how many of us are self-aware enough to know when our own battery life is getting low?”

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Don’t let anything come between you and your customers – except IoT sensors

42-26102259When something comes between you and your customers – like not having product in-stock or providing offers that aren't relevant to the customer – it causes delays and makes it harder to complete transactions in a satisfying way. But, an inexpensive sensor, beacon or Radio Frequency Identification (RFID) tag placed between you and your customers can help you get closer.

Those simple little devices are part of the trendy Internet of Things (IoT) conversation happening now -- and they can help you sense who your customer is and what she wants. They’ll also help you better understand behavior and preferences and allow you to act on those insights to create a more engaging customer experience.

When retailing was a simpler business, store owners knew their customers. As society advanced, the stores got bigger, and entire chains of retail stores emerged around the country and the world. As the businesses grew, merchants became separated from customers and relied more on spreadsheets and reports to run the business than a handshake and a smile. With the advent of the Internet, the modern merchant was able to track and understand their customers better, but only while they were online shopping. This was impersonal and, in many cases, the retailer was not able to tie the online customer to the in-store customer, creating customer dissatisfaction and operational failures. This is where embracing the IoT can be a genius move for retailers.

By bringing sensor technology into a bricks and mortar store, the website and store can be on equal footing to recognize customers and meet their expectations. There are three main ways the IoT can help the retailer: Read More »

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How to embed advanced analytics in your biggest ideas

As we look at the last 40 years of innovation using analytics, it can be both humbling and inspiring.

I mean, who would have anticipated 40 years ago that SAS® would be used to analyze genomic data and help develop specialized medications as a result? Who would have guessed that a car manufacturer could analyze streaming data from sensors and onboard devices to improve safety? Who would have imagined in 1976 that someday a global retailer would develop a customer loyalty app that runs SAS Analytics in the background to provide real-time mobile phone offers?

Of course, nobody knows what the next 40 years will bring, but we do anticipate that SAS will be used more and more in the cloud, with big data, with streaming data, with automated applications, and with cognitive computing tools. To name a few.

SAS Viya No Limits adOverall, we know that our customers want to run SAS anywhere, anytime and by virtually anyone. It sounds like a big set of requirements, but we’re making it possible with SAS® Viya, which opens SAS to run inside almost any environment you can imagine. Built for the cloud and deployable anywhere from a common code base, SAS Viya can be in-memory, in-database and in-Hadoop. With the ability to flow seamlessly from the device, to “the fog” and right back to the cloud, we’re helping to put advanced analytics inside your biggest ideas.

Maybe we can’t imagine exactly how you’ll use SAS in the next 10 to 40 years, but we can imagine that you’ll need to be working in one of these environments, and we want to make sure you can take analytics, predictive capabilities and machine learning along with you.
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Deep learning methods and applications

287407709If I were to show you a picture of a house, you would know it’s a house without even stopping to think about it. Because you have seen hundreds of different types of houses, your brain has come to recognize the features – a roof, a door, windows, a front stoop – that make up a house. So, even if the picture only shows part of the house, you still know instantly what you’re looking at. You have learned to recognize houses.

Deep learning is a specialization of artificial intelligence that can train a computer to perform human-like tasks, like recognizing, classifying, and describing images of houses. But how are deep learning methods and applications used in business, and what benefits does deep learning promise for the future of analytics? We turned to Oliver Schabenberger, SAS VP of Analytic Server R&D, to learn more about deep learning and how it works.

How do you define deep learning?

Oliver Schabenberger: Deep learning methods are part of machine learning, which is considered a form of weak artificial intelligence (AI). We say weak AI, because we do not claim to create thinking machines that operate like a human brain. But we do claim that these learning methods can perform specific, human-like tasks in an intelligent way. And we are finding out that these systems of intelligence augmentation can often perform these tasks with greater accuracy, reliability or repeatability than a human. Read More »

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