SAS Data Set is a collection of observations (rows) made on some variables (columns). A single observation or row usually consists of one or more pieces of numerical variables; each piece is called a variable. The values contained by an observation are called the observations (or rows ) of the dataset. A spreadsheet is a very simple, easy-to-use way of organizing data. On the other hand, SAS Data Set is a more powerful and complex tool for this. Typically the values in an observation are measurements made on a certain type of animal or experimental unit under consideration, or they could be observational data. Thereafter, the observations are usually saved so that they can be used later by SAS programs for statistical analyses or in some other way.
Why SAS Data Set?
- Data organization:
Improve performance and efficiency by performing data analysis using SAS Data Sets. SAS is a leader in statistical analysis, business intelligence, data mining, text mining, and advanced analytics. As a result, thousands of large enterprises around the world use SAS.
- Collaboration:
SAS Data Sets allow researchers and data scientists to work together more easily. Hence, it allows them to quickly and easily share large data sets with one another.
- Creativity:
Reduce the time to market by using SAS Data Sets in new and innovative ways. By filing data sets, you can add value to your organization and keep up with competitors by streamlining your processes.
- Scalability:
Build better products, improve services, and develop new methodologies by viewing the same data from different perspectives with SAS Data Sets.
- Agility:
Take advantage of multiple opportunities in a single, flexible environment by gaining faster access to accurate information with SAS Data Sets.
- Accuracy:
SAS Data Sets help to reduce the margin of error by allowing you to understand your data more thoroughly. For example, with SAS, examples can identify and remove data errors before they impact your organization.