If you’re a SAS user, you know that SAS Global Forum is where you want to be! It’s our premier, can’t-miss event for SAS professionals—that includes thousands of users, executives, partners and academics. It’s also our largest users’ event, organized by users, for users, and this year’s event marks our […]
Experience SAS Global Forum: A First-Timer’s View & Tip Sheet was published on SAS Users.
One of the first and most important steps in analyzing data, whether for descriptive or inferential statistical tasks, is to check for possible errors in your data. In my book, Cody’s Data Cleaning Techniques Using SAS, Third Edition, I describe a macro called %Auto_Outliers. This macro allows you to search […]
Finding Possible Data Errors Using the %Auto_Outliers Macro was published on SAS Users.
SAS Leonid Batkhan presents SAS coding techniques to shift a dates by given numbers of workdays accounting for weekends and holidays.
Shifting a date by a given number of workdays was published on SAS Users.
When I attend a conference, one of the first things I do is look at the agenda. This gives me a good overview of how my time will be spent. The next thing I do is find the detailed breakdown of sessions, so I can start building out my own […]
Make the most of SAS Global Forum with the session catalog was published on SAS Users.
One great thing about being a SAS programmer is that you never run out of new things to learn. SAS often gives us a variety of methods to produce the same result. One good example of this is the DATA step and PROC SQL, both of which manipulate data. The […]
Expand Your SAS Knowledge by Learning PROC SQL was published on SAS Users.
This blog is part of a series on SAS Visual Data Mining and Machine Learning (VDMML). If you’re new to SAS VDMML and you want a brief overview of the features available, check out my last blog post! This blog will discuss types of missing data and how to use imputation […]
Missing data? Quickly impute values using SAS Viya was published on SAS Users.
Some business models will segment the worth of their customers into categories that will often give different levels of service to the more “higher worth” customers. The metric most often used for that is called Customer Lifetime Value (CLV). CLV is simply a balance sheet look at the total cost spent versus the total revenue earned over a customer’s projected tenure or “life.”
How to utilize Customer Lifetime Value with SAS Visual Analytics was published on SAS Users.
Are you ready to get a jump start on the new year? If you’ve been wanting to brush up your SAS skills or learn something new, there’s no time like a new decade to start! SAS Press is releasing several new books in the upcoming months to help you stay […]
Foresight is 2020! New books to take your skills to the next level was published on SAS Users.