SAS® popularity has grown over the years as it includes a variety of features to handle different types of data – structured and unstructured data – from different destinations. SAS® is used for various tasks such as predictive modeling; data mining; multivariate analysis and forecast analysis. Because of all these facilities, it has become one of the preferred custom integrated tools.
Understanding working with SAS®
To work with data with SAS®, the data must be in SAS format or tabulated Excel format. Data is put into tables in rows and columns. The rows are referred to as observation, while the columns are referred to as variables. This procedure allows users to retrieve information from the database; spreadsheet or other table format easily. In addition to ease of use, SAS® allows output to be saved in HTML, RTF and PDF formats. Because of all this, SAS® is used in banking, pharmaceuticals, education, government and other sectors.
DATA steps and PROC steps
SAS programs use DATA steps and PROC steps deal with data. To be specific, data can be changed or retrieved using DATA steps, and data can be analyzed using PROC steps. DATA steps consist of two stages; namely the compilation phase and the execution phase. In the compilation phase, the compiler identifies syntax errors and processes declarative statement. Submit this, every executable statement is processed.
Convenience with SAS®
Unlike other business intelligence software, where programming is a must for managing large volumes of data, SAS® offers the facilities to manage and analyze humane data with the click of a few buttons or programming. To elaborate, even non-technical users can work on it by clicking on the required features with an embedded facility called graphical point-and-click interface, while technical users can program for data analysis, data management, or for some other data-related tasks.
SAS® is compatible with both flat and unformatted files, so it is selected in relation to other software in various data analysis disciplines. Below are some of the sectors where SAS® is commonly used:
• Financial analysis
• Psychological testing
• Sales forecasts
• Examine consumer behavior
• Financial risk analysis
• Academic research
• Data analysis
• Business Intelligence
• Pharmaceutical analysis
SAS® Online Training – Base SAS® Training & Advanced SAS® Training
For aspirants who want to thoroughly understand and master SAS® features, Base SAS® training is the ideal choice. After Base SAS® training, individuals can choose Advanced SAS® training. Base SAS® training will focus on topics such as writing SAS® programs; understand data manipulation techniques; SAS® array processing; navigate the SAS® window environment and many more. Advanced SAS® training will provide knowledge on various aspects associated with SAS® programming, such as making use of conditional logic in Query Builder; macros; Advanced DATA step programming statements; Subqueries; combining large datasets, etc.