6 tips to prepare data for analytics
Proper data prep means faster, better analytics. Guest blogger Jenine Milum shares tips.
Uncategorized
How to win the SAS Championship
What can data tell us about the easiest hole at your favorite golf course? Or which hole contributes the most to mastering the course? A golf instructor once told me golf is not my sport, and that my swing is hopeless, but that didn’t stop me from analyzing golf data!
Teaching children AI skills for future jobs
Estimations suggests that 65% of children entering primary school now will be doing jobs that do not yet exist.
What statistic should you use to display error bars for a mean?
In a previous article, I mentioned that the VLINE statement in PROC SGPLOT is an easy way to graph the mean response at a set of discrete time points. I mentioned that you can choose three options for the length of the "error bars": the standard deviation of the data,
Computer vision: Past, present and future
Thanks to recent advances in Artificial Intelligence (AI) and deep learning, image recognition has become a reality.
Hackathon challenge: Fighting fire with data
In Greece we conduct a SAS Hackathon. This will focus on wildfires - come and join!
Graph the mean response versus time in SAS
It is always great to read an old paper or blog post and think, "This task is so much easier in SAS 9.4!" I had that thought recently when I stumbled on a 2007 paper by Wei Cheng titled "Graphical Representation of Mean Measurement over Time." A substantial portion of
Guest blogger: Len Tashman previews fall 2019 issue of Foresight
Foresight Editor-in-Chief Len Tashman's Preview of the Fall 2019 Issue This 55th issue of Foresight opens with an article from Phillip Yelland, Zeynep Erkin Baz, and David Serafini of the Data Science/AI team at Target: Forecasting at Scale: The Architecture of a Modern Retail Forecasting System. The challenge of scale
Pictures, words and the coming AI storytelling opportunity
At the #AISummit early this summer, I was interested to see that one of the most popular demos on the SAS stand was of object detection. A camera was detecting the nature of an object waved in front of it and tracking it moving through the livestream. This was a
Common ground for future fraud detection techniques
Fraud detection is a wide field. Every organisation experiences the implementation differently.
When did household air conditioning become ubiquitous in the US?
We've had record high 90+ degree temperatures here in the southeast US this past week (September / October), and it has made me appreciate having an air conditioner. Indeed, air conditioners were pretty much invented here in North Carolina (see Eric Cramer). They are used in pretty much every building
Why Talk of the Geeks is popular with data science customers
Nowadays, geeks are increasingly cool, and we’re all proud to let our inner geek out in public. This wasn't always so ...
Meetup - PyData Südwest@SAS
Die PyData-Südwest-Gruppe hatte zum 3. Meetup mit über 100 Gästen bei SAS in Heidelberg eingeladen.
Mystery solved: The case for operationalizing analytics
The final phase in analytical model deployment is the perfect unsolved mystery. Why are 50% of analytics models never deployed? And why does it take three months or more to complete 90% of deployed models? What happened or didn’t happen to allow analytical insights to reach their potential? It’s a
Compute the geometric mean, geometric standard deviation, and geometric CV in SAS
I frequently see questions on SAS discussion forums about how to compute the geometric mean and related quantities in SAS. Unfortunately, the answers to these questions are sometimes confusing or even wrong. In addition, some published papers and web sites that claim to show how to calculate the geometric mean
Why data management protocols are key to implementing legislative actions
Surprise! The data team does more than you think to implement certain legislative actions.
Customer experience matters
Did you know the first SAS® Users Group event took place before SAS was incorporated as a company? In 1976, hundreds of early SAS users gathered in sunny Kissimmee, FL to share tips and offer feedback before SAS was even officially a company. Our users have continued to influence the
10 ways to sharpen your approach to payment fraud analytics
New payment methods will deliver huge improvements in speed of transaction, but also provide challenges.
5 steps to unlock business value from industrial IoT
Industrial leaders need an #IoT #analytics platform and a strategy that generates intelligence in lockstep with business needs.
What is a geometric mean?
There are several different kinds of means. They all try to find an average value from among a set of numbers. Although the most popular mean is the arithmetic mean, the geometric mean can be useful for problems in statistics, finance, and biology. A common application of the geometric mean
Uma geração de clientes | SANTANDER TOTTA
A relação do SAS com o Banco Totta & Açores – que entretanto se fundiu com o Banco Santander, dando origem ao Banco Santander Totta, uma das maiores instituições financeiras a atuar em Portugal – data de 1998, com sete users PC e a implementação do SAS Warehouse Administrator. Nos
How do you achieve innovation at scale in a traditional company?
Interview with Line Lyst about how to ensure innovation at Ramboll while taking care of business as usual.
Graphing the record unemployment in California and New York
Lately we've been hearing a lot about "record low unemployment" in the news. Being a data guy, I wanted to see it for myself. Follow along as I create some custom unemployment graphs from the official data for California and New York (two of our most populous states). Or, if
Solve many optimization problems
One of the strengths of the SAS/IML language is its flexibility. Recently, a SAS programmer asked how to generalize a program in a previous article. The original program solved one optimization problem. The reader said that she wants to solve this type of problem 300 times, each time using a
Videos: Building computer vision models with Python and SAS Deep Learning
This series of videos spotlights a very powerful API that lets you use Python while also having access to the power of SAS Deep Learning.
What's In Your Well-Being Chart?
"Take care of yourself!" Sound like something you hear often? This instruction may conjure up fixed ideals of what "taking care" means: getting to the gym, making smoothies, meditating, or getting more sleep. But gym memberships aren’t for everyone, not everyone has a blender, and we may not be able
Why intelligent dashboards do not always lead to intelligent decisions
"Senior managers adore their dashboards. Are they really capable of understanding what they indicate? I have my doubts!"
We consider artifical intelligence as a catalyst for new jobs
"Artificial intelligence? Creates jobs? I admit it is far more usual to hear apocalyptic predictions that AI will destroy jobs. Is that true?"
Finding themes in the "Trafficking in Persons" reports
In this blog, I use data from the U. S. Department of State Trafficking in Persons (TIP) reports for the years 2013-2017 to accomplish these objectives: 1) To determine what are the main themes in TIP reports, and 2) to show how to work with ASTORE code to deploy models using SAS Viya 3.4 Visual Text Analytics 8.4.
The identity challenge: How can banks know who’s who?
"Once an attack is discovered, the average #cybercrime victim in the UK spends 14.8 hours dealing with the aftermath. These are worrying facts."