Customer Experience Day (aka #CXDay2019) is one of our favorite days of the year—when we can reflect on customer interactions, questions and feedback from the past year—and look to the year ahead for ways to enhance our customers’ experience, like expanding our support options and helping drive improvements to our website and self-service offerings.
This article continues a series that began with Machine learning with SASPy: Exploring and preparing your data (part 1). Part 1 showed you how to explore data using SASPy with Python. Here, in part 2, you will learn how to begin to prepare your data to use it within a
In part 1 of this post, we looked at setting up Spark jobs from Cloud Analytics Services (CAS) to load and save data to and from Hadoop. Now we are moving on to the next step in the analytic cycle, scoring data in Hadoop and executing SAS code as a
Importing about 4,400 messages worth of data into SAS Visual Text Analytics to exploring it and create an information extraction model.
The SAS Global Forum 2020 call for content is open until Sept. 30, 2019. Are you thinking of submitting a paper? If so, we have a few tips adapted from The Global English Style Guide that will help your paper shine. By following Global English guidelines, your writing will be
One of the features of SAS Grid Manager (and SAS Grid Manager for Platform) introduced in SAS 9.4 M6 is the capability for the grid provider software to handle open-source workloads in addition to traditional SAS jobs. In this post, we’ll take a look at the steps required to get your SAS Grid Manager environment set up to utilize this functionality, and we’ll demonstrate the process of submitting Python code for execution in the SAS Grid.
Just when you think you’ve seen it all, life can surprise you in a big way, making you wonder what else you've missed. That is what happened when I recently had a chance to work with the SAS® Scalable Performance Data Server, a product that's been around a while, but
Time-series decomposition is an important technique for time series analysis, especially for seasonal adjustment and trend strength measurement. Decomposition deconstructs a time series into several components, with each representing a certain pattern or characteristic. This post shows you how to use SAS® Visual Analytics to visually show the decomposition of
I recently had the incredible opportunity to attend SAS Global Forum in Dallas as a presenter and New SAS Professional Award recipient. At the conference, I was able to learn more about SAS features and applications, share my knowledge of SAS applications in the clinical trials space, and make new
SASPy is a powerful Python library that interfaces with SAS and can help with your machine-learning solutions. SASPy was created for Python programmers to leverage the power of SAS within their Python scripts. If you are not familiar with SASPy, see the following resources: Introducing SASPy: Use Python code to
