SAS Analytics provides an integrated environment for predictive and descriptive modeling, data mining, text analytics, forecasting, optimization, simulation, experimental design and more. From dynamic visualization to predictive modeling, model deployment and process optimization, SAS provides a range of techniques and processes for the collection, classification, analysis, and interpretation of data to reveal patterns, anomalies, key variables and relationships, leading ultimately to new insights and better answers faster. This instructor-led course provides students with the knowledge and skills to leverage SAS tool to analyze data about customers, suppliers, operations, performance and more.
Generating detail reports by working with a single table, joining tables, or using set operators in the SQL procedure.
Generating summary reports by working with a single table, joining tables, or using set operators in the SQL procedure.
Construct sub-queries and in-line views within an SQL procedure step.
Comparing solving a problem using the SQL procedure versus using traditional SAS programming techniques.
Accessing dictionary tables using the SQL procedure.
Creating and using user-defined and automatic macro variables within the SAS Macro Language.
Automating programs by defining and calling macros using the SAS Macro Language.
Understanding the use of macro functions.
Using various system options that are available for macro debugging and displaying values of user-defined and automatic macro variables in the SAS log.
Creating data-driven programs using SAS Macro Language.
Demonstrating the use of advanced data look-up techniques such as array processing, hash objects, formats, and combining/merging data.
Reducing computing resource requirements by controlling the space required to store SAS data sets using compression techniques, length statements, or eliminating variables and observations.
Developing SAS programs which incorporate data step views and use the FCMP procedure.
Performing effective benchmarking by using the appropriate SAS System options and interpreting the resulting resource utilization statistics.
Identifying appropriate applications for using indexes and create them using the DATA step, the DATASETS procedure, or the SQL procedure.
Comparing techniques to eliminate duplicate data using the DATA step, the SORT procedure, and the SQL procedure.
Certificate of participation in ‘Statistical Analysis Software Advanced Programmer course.