I was reading a statistics book when I encountered a histogram that caught my eye. The histogram looked similar to the one at the left. It contained a normal density estimate overlaid on a histogram, but the height of the density curve seemed too short when compared to the heights
There is a job category unfamiliar to most people that plays a crucial role in the creation of analytics software. Most can surmise that SAS hires software developers with backgrounds in statistics, econometrics, forecasting or operations research to create our analytical software; however, most do not realize there is another
SAS Cares. That’s how we want you to feel once you become a SAS customer. How do we do that? By bringing all of the support resources together with one goal in mind – helping you become a better SAS user. The SAS Cares experience involves everything from searching on
In my previous post, I discussed the similarities, differences and overlap between event stream processing (ESP) and real-time processing (RTP). In this post, I want to highlight three things that need to get real. In other words, three things that should be enhanced with real-time capabilities, whether it’s ESP, RTP or
Have you ever heard the expression, “Guess I gotta pay the piper.”? It is often used about a situation where a price is paid that is considered too high or unfair, but failing to pay the price often results in dire consequences. This expression is based on the story of
I guess most of us have a morbid curiosity about how we're going to die ... which is probably why Francis Boscoe's Causes of Death map went viral (no pun intended, of course!). This blog post shows how to create such a map... But first, to lighten up the mood a bit
I’ve had the good fortune to support the Pharmaceutical Industry SAS Users Group as their SAS liaison for the majority of their conferences since 1996. That’s meant a lot to me personally and professionally over the years. I’ve developed some genuine friendships with the dedicated volunteer leaders who organize the
I recently taught a SAS training course where the students were very engaged. They had so many questions, I could have spent the next month writing helpful blog posts that came from that one class. However, I picked this one question that the class begged for me to share. The
A SAS programmer asked for a list of SAS/IML functions that operate on the columns of an n x p matrix and return a 1 x p row vector of results. The functions that behave this way tend to compute univariate descriptive statistics such as the mean, median, standard deviation, and quantiles. The following
This month we take a fresh analytical view of our hypothetical VirtualOil portfolio by comparing the forward price of WTI (the green line) to the prompt month price (red line). The resulting graphic (chart 1) demonstrates the relative stability of the 48-month forward price in contrast to a very active spot
SAS offers a rich collection of features for working with Hadoop quickly and efficiently. This post will provide a brief run-through of the various technologies used by SAS to get to data in Hadoop and what’s needed to get the job done. Working with text files Base SAS software has the
A recent news report shows an unexpected spike in traffic fatalities here in the US in 2015. This got me wondering what the data shows ... for the past 100 years or so... Driving was a lot more dangerous in the early days. If you were in a wreck, you
I was at a family gathering recently. An elderly relative asked my teenage nephew, "So, what do you want to be when you grow up?" My nephew looked over at me hoping I'd rescue him from the situation. I didn't. But I also recognized the pressure a teen can feel
SAS software is used around the world in some of the most sophisticated ways, like ATM fraud detection and cancer research. But recently, I used it for a practical, and much needed, task -- replacing our break room coffee machine. Now, this is no ordinary coffee machine. It also makes
I previously wrote about the best way to suppress output from SAS procedures. Suppressing output is necessary in simulation and bootstrap analyses, and it is useful in other contexts as well. In my previous article, I wrote, "many programmers use ODS _ALL_ CLOSE as a way to suppress output, but
The final figures are in! This year there was a fierce battle for the top spot of the SAS Global Forum 2015 books bestseller list. In a nail biting finish, newcomer, Exchanging Data between SAS and Microsoft Excel: Tips and Techniques to Transfer and Manage Data More Efficiently, beat off
“Phew! That tip alone was a life saver,” said a student in one of my SAS SQL classes. “Before, I would have to read about ten Google search results before I could find that content of the sort you shared in class.” That student was referring to the tip I
In my last post, we examined the growing importance of event stream processing to predictive and prescriptive analytics. In the example we discussed, we looked at how all the event streams from point-of-sale systems from multiple retail locations are absorbed at a centralized point for analysis. Yet the beneficiaries of those
French fries, pommes frites, chips…or just fries…are indisputably one of the most popular foods in America with the average American consuming nearly 29 pounds of fries a year.
I saw an interesting graph on dadaviz.com that claimed Italians had gone from drinking twice as much as Americans in 1970, to less than Americans in recent years. The data analyst in me just had to "independently verify" this factoid ... But before I get into the technical part of this
A proof of concept (POC) is smartest way for customers to evaluate if a product meets the required objectives, and the best way for vendors to demonstrate why they feel they are best placed to resolve the current outstanding problems. However, not all POCs are successful. Let’s explore why. What is
What prompted me to find a co-author and write a new edition of my original book on PROC TABULATE? It’s those inventive developers at SAS. They keep adding new features to make the product even better. There are too many new features and techniques in the book to name, but these are
SAS procedures can produce a lot of output, but you don't always want to see it all. In simulation and bootstrap studies, you might analyze 10,000 samples or resamples. Usually you are not interested in seeing the results of each analysis displayed on your computer screen. Instead, you want to
PharmaSUG 2015 in Orlando was held at the Renaissance had a record breaking attendance of over 650. Weather was great, except for a huge downpour on the evening of the last day. All the popular presenters were in attendance including Art Carpenter, Kirk Lafler, Arthur Li and many others. Presentations
Recently I had the privilege of hearing Nathan Falkenborg, Head of Consulting & Analytics, North Asia at Visa speak at the SAS Executive Forum in Singapore. Nathan has also spoken at SAS Premier Business Leadership Series where he talked about how the analytics guy won over the marketers at Visa.
As we enter the era of “everything connected,” we cannot forget that gathering data is not enough. We need to process that data to gain new knowledge and build our competitive advantage. The Internet of Things is not just a consumer thing – it also makes our businesses more intelligent. Whenever
The cottage industry was based on workers buying raw materials, bringing them home and producing hand-crafted items to sell. The system worked, but was slow, tedious and expensive, producing goods that were affordable only by the rich. The Industrial Revolution changed all that. The factory system brought machines and workers
After acquiring personal IoT data in part 1 and cleaning it up in part 2 of this series, we are now ready to explore the data with SAS Visual Analytics. Let's see which answers we can find with the help of data visualization and analytics! I followed the general exploratory workflow
We have spent a good deal of time at the Analytic Hospitality Executive advocating for the value of big data for hospitality. Just a few months ago, for example, I wrote a two part series on how Big Data was a “big opportunity” for hotels and casinos. Our goal at
.@philsimon says that you shouldn't bring a knife to a gun fight.
