SAS Users
Providing technical tips and support information, written for and by SAS users.![SAS Studio Webwork library demystified](https://blogs.sas.com/content/sgf/files/2016/12/SAS-Studio-Webwork-library01.jpg)
In a previous blog about SAS Studio I’ve briefly introduced the concept of using the Webwork library instead of the default Work. I also suggested, in SAS Global Forum 2016 paper, Deep Dive with SAS Studio into SAS Grid Manager 9.4, to save intermediate results in the Webwork library, because
![Enhancing SAS Asset Performance Analytics’ Root Cause Analysis with Calculated Columns](https://blogs.sas.com/content/sgf/files/2016/12/SAS-Asset-Performance-Analytics’-Root-Cause-Analysis03.png)
During a recent customer visit, I was asked how to include a calculated variable within SAS Asset Performance Analytics’ (APA) Root Cause Analysis workflow. This is a simple request. Is there a simple approach to do this? To remind you, in the APA workflow, an ETL Administrator makes a Data
![SAS integration with Hadoop - one success story](https://blogs.sas.com/content/sgf/files/2016/12/SAS-Integration-with-Hadoop01.png)
Nearly every organization has to deal with big data, and that often means dealing with big data problems. For some organizations, especially government agencies, addressing these problems provides more than a competitive advantage, it helps them ensure public confidence in their work or meet standards mandated by law. In this
![Securing sensitive data using SAS Federation Server at the data source level](https://blogs.sas.com/content/sgf/files/2016/11/Securing-sensitive-data-using-SAS-Federation-Server01.png)
Data virtualization is an agile way to provide virtual views of data from multiple sources without moving the data. Think of data virtualization as an another arrow in your quiver in terms of how you approach combining data from different sources to augment your existing Extract, Transform and Load ETL batch
![SAS Global Forum 2017 is closer to home, or should I say…](https://blogs.sas.com/content/sgf/files/2016/11/SAS_Global_Forum_2017.jpg)
est plus près de la maison, está más cerca de casa, está mais perto de casa, dichter bij huis, is closer to home, eh! In analytics and statistics, we often talk about sample sizes. The size of the data sets that you analyze are a measure of the amount of
![Modifying variable attributes in all datasets of a SAS library SAS toolbox: macro functions](https://blogs.sas.com/content/sgf/files/2020/05/pixabay-handyman-600x336.png)
Using the DATASETS procedure, we can easily modify SAS variable attributes such as name, format, informat and label: proc datasets library=libref; modify table_name; format var_name date9.; informat var_name mmddyy10.; label var_name = 'New label'; rename var_name = var_new_name; quit; We cannot, however, modify fixed variable attributes such as variable type