SAS programming has become an essential tool in the field of data science and statistical analysis. Its flexibility and power make it indispensable for professionals looking to handle large data sets efficiently.
In this article, we will discuss what exactly SAS programming is, its evolution over time, the fundamentals behind it, and its most common uses.
For professionals who want to master SAS programming and give their career a boost, training is key. Different options are available to them, such as the master in Big Data Analytics offered by Universidad Europea. If you are still not sure whether you should specialise in this discipline or not, read on.
SAS, which stands for Statistical Analysis System, is software that allows users to perform statistical analysis, data mining, data management and application development. SAS programming is the process of writing and executing code in the SAS environment to perform various analytical tasks.
This system is characterised by its ability to efficiently handle large volumes of data and its versatility in statistical analysis. It uses its own language, the SAS language, which combines elements of conventional programming languages with specific commands for data analysis.
The development of SAS programming dates back to the 1960s, when it was conceived as a project of North Carolina State University. Initially, the focus was on providing tools for agricultural analysis, but its application expanded to various industries over time.
SAS Institute, the company behind the software, has been constantly updating and improving the system. Today, SAS has become as standard in business and academia as other Java-like programming languages. Its particularity is that it is more focused on data analysis and report generation, a key skill that you will develop should you decide to study a programme such as the degree in Business Analytics at Universidad Europea.
The SAS language serves as the fundamental basis for SAS programming. It includes specific commands that allow various operations to be performed, from loading and manipulating data to creating detailed reports. The programming structure of the SAS language is relatively simple, making it easy to learn and efficient to use.
Some fundamental concepts are defining variables, manipulating data sets and using statistical procedures. SAS programs are often structured in code blocks that perform specific steps, making the code easier to understand and debug.
SAS programming has applications in a variety of areas, most notably data analysis, statistics and report generation. Some of its most common uses include:
Advanced statistical analysis.
SAS programming is often used to perform advanced statistical analysis, such as regression, analysis of variance, and time series analysis. Its statistical procedures provide very effective tools for understanding variability and relationships within data.
Data mining
In the field of data mining, SAS programming is used to uncover hidden patterns, trends and relationships in large data sets. This is crucial for informed decision making and identifying strategic opportunities.
Data management
SAS programming's ability to efficiently manipulate large volumes of data makes it an invaluable tool for data management and data cleansing. This ensures the quality of data used in subsequent analysis.
Report development
The SAS reporting system facilitates the creation of detailed reports and data visualisations. This is essential for effectively communicating analysis results to stakeholders, management and other interested parties.
SAS programming has established itself as an indispensable tool in the field of data analysis and statistics. Its evolution over time, its solid foundations and its versatility make it the preferred choice for professionals seeking to handle data efficiently and perform advanced statistical analysis.