The number of models used by large operators in the financial sector is increasing by around 10 to 25 percent per year. Most of the new models are designed to meet business needs, such as pricing, the definition of strategic plans and the management of liquidity. Some, though, are for
Jim Harris shares examples of how and why AI applications are dependent on high-quality data.
Salads are the image most of us see in our heads when we think of healthy eating. And for good reason, they can be really healthy. However, it is possible (and very common) for salads to end up being not so healthy, or just not enough for a meal.
Hackathons are short-term programming events that use data and analytics to solve real-world challenges. They have been around for a while now, and there is general agreement that they are great opportunities for networking and experimenting. There is also, however, now a growing sense that organisations can use them to
In numerical linear algebra, there are often multiple ways to solve a problem, and each way is useful in various contexts. In fact, one of the challenges in matrix computations is choosing from among different algorithms, which often vary in their use of memory, data access, and speed. This article
Natural language understanding (NLU) is a subfield of natural language processing (NLP) that enables machine reading comprehension. While both understand human language, NLU goes beyond the structural understanding of language to interpret intent, resolve context and word ambiguity, and even generate human language on its own. NLU is designed for
The recently released results of a new joint survey from SAS and the Global Association of Risk Professionals (GARP) on the use of AI in risk management makes for very interesting reading. Here are the highlights from the study, which involved more than 2,000 participants from across the global financial
Chances are that sometime in your life you have been hurt by gossip. We probably all agree that gossip is wrong. It spreads negativity in our workplaces and social groups. It is designed to make someone else look bad and to isolate them from the group. It encourages people to
Let’s be blunt. Procurement fraud is a problem. Orders and purchase procedures are one of the most vulnerable areas of corruption. The scale of irregularities and abuse in the procurement area is large. In fact, procurement fraud is the second-biggest economic crime after theft. Estimates suggest that businesses can
Have you ever wondered if love at first sight really exists? And if it exists, what qualities are people drawn too? Watch any romantic comedy and you’ll see this phenomenon play out on the big screen. Which begs the question, “If it can happen to them why not me?” Let’s
Education can change the future trajectory of generations. That is a fact we know to be true. But what does it really look like on a micro level, through the lens of an individual life? SAS employees like Ada Lopez demonstrate the transformative power of education. Ada spent most of her professional
As word spreads that SAS integrates with open source technologies, people are beginning to explore how to connect, interact with, and use SAS in new ways. More and more users are examining the possibilities and with this comes questions like: How do I code A, integrate B, and accomplish C?
SAS Global Forum 2019 (SGF) is rapidly approaching - and which of the hundreds of presentations are you planning to attend? Well, no matter what types of analyses you perform with SAS software, you'll most likely want to present your findings in a really nice/informative graph! Therefore I highly recommend
Suppose you need to assign 100 patients equally among 3 treatment groups in a clinical study. Obviously, an equal allocation is impossible because the second number does not evenly divide the first, but you can get close by assigning 34 patients to one group and 33 to the others. Mathematically,
The catch phrase “everything happens somewhere” is increasingly common these days. That “somewhere” translates into a location on the Earth; a latitude and longitude. When one of these “somewhere’s” is combined with many other “somewhere’s”, you quickly have a robust spatial data set that becomes actionable with the right analytic
Recently, the North Carolina Human Trafficking Commission hosted a regional symposium to help strengthen North Carolina’s multidisciplinary response to human trafficking. One of the speakers shared an anecdote from a busy young woman with kids. She had returned home from work and was preparing for dinner; her young son wanted
Recently, you may have heard about the release of the new SAS Cloud. The platform allows fast access to data-science applications in the cloud! Running on the SAS Cloud and using the latest container technology, SAS Cloud eliminates the need to install, update, or maintain software or related infrastructure. SAS
You are a data scientist, in your office, doing data scientist-y things when, your manager's, manager's, manager makes an impossible request. She wants you take a raw data set from the stem cell research team, scrub the data, create and score models, and be ready to rescore when new data
Have you ever dreamed of working for a professional sports organization? Do you play fantasy sports leagues and fantasize about owning a real team? Do you follow the news about player drafts and trades, and wish you could influence who your team picks? Well, here’s your chance. The latest SAS
When working with files like SAS programs, images, documents, logs, etc., we are used to accessing them in operating system directories. In Viya, many of these files are not stored on the file-system. Let's look at where and how files are stored in Viya, and how to manage them.
The idea of running software in a self-contained package took off with the launch of Docker in 2013 and has become a hot topic in the application development and DevOps community. In a recent survey by Red Hat, 57 percent of companies questioned said they use containers for some workloads
Changing how we’ve viewed the beautiful game forever. How often have we looked at a game and wondered, “How did he miss that?!” Now, with expected goals (xG) metric, we can really see if our frustration is justified, and perhaps use that to predict future results. The use of analytics
According to the World Cancer Research Fund, Breast cancer is one of the most common cancers worldwide, with 12.3% of new cancer patients in 2018 suffering from breast cancer. Early detection can significantly improve treatment value, however, the interpretation of cancer images heavily depends on the experience of doctors and technicians. The
I recently saw an interesting graph that showed the number of motor vehicle crash deaths has been going down. The graph showed deaths per mile. That's a good statistic, but I wondered whether there were other ways to look at the data? An Interesting Graph Here's the graph, from an
Structuring a highly unstructured data source Human language is astoundingly complex and diverse. We express ourselves in infinite ways. It can be very difficult to model and extract meaning from both written and spoken language. Usually the most meaningful analysis uses a number of techniques. While supervised and unsupervised learning,
I've previously written about how to deal with nonconvergence when fitting generalized linear regression models. Most generalized linear and mixed models use an iterative optimization process, such as maximum likelihood estimation, to fit parameters. The optimization might not converge, either because the initial guess is poor or because the model
There's been a lot of hype regarding using machine learning (ML) for demand forecasting, and rightfully so, given the advancements in data collection, storage, and processing along with improvements in technology. There's no reason why machine learning can't be utilized as another forecasting method among the collection of forecasting methods
The day you have been planning for (and paying for) is fast arriving! Your college student is graduating and taking that next step toward full-fledged adulthood. What’s not to celebrate? And please do take the time to celebrate. 😊 After a week or two, however, it’s time to talk about
Data scientists spend a lot of their time using data. Data quality is essential for applying machine learning models to solve business questions and training AI models. However, analytics and data science do not just make demands on data quality. They can also contribute a lot to improving the quality
What is that makes some innovations "stick" and others disappear into the ether, never to be seen again? In a high-technology industry, it is tempting to say that the technology simply wasn’t right, or the timing was wrong. However, history suggests that this is probably not the case. Much of the
