Course Outline
Overview
Comprehensive Review of SAS
- Structure of SAS data sets
- Definition and management of SAS variables
- Organization within SAS libraries
- Standardized structure of SAS code
Establishment of the Development Environment
- Installation and configuration of SAS Studio
- Installation and configuration of WPS
Data Management Practices in SAS
- Ingestion of external data sources
- Export of processed data
- Development of variables and computational logic
- Selection and filtering of observations
- Implementation of conditional logic and iterative processes
- Integration of multiple data sets
- Application of core SAS statements
- Data cleansing procedures
Advanced Arrays and Functional Methods
- Generation of new variables through iterative loops
- Construction of derived variables
- Utilization of standard SAS functions
- Consolidation of raw data files for government reporting
Data Visualization Techniques
- Development of bar charts
- Development of scatter plots
- Development of pie charts
- Layering of graphical overlays
Statistical Analysis
- Compilation of statistical reports
- Application of simple linear regression models
- Application of multiple regression analyses
- Interpretation of analytical results
- Forecasting and predictive capabilities
Structured Query Language (SQL) in SAS
- Fundamentals of SAS SQL syntax
- Implementation of clauses and statements
- Manipulation of columns and rows
- Management of relational tables
Indexing Strategies in SAS
- Validation with test data sets
- Execution of PROC procedures for indexing
- Creation, modification, and application of indexes to improve access for government systems
Macro Programming in SAS
- Utilization of macro variables for dynamic content
- Utilization of macro functions
- Development of custom macros
- Debugging techniques and storage management of macros
Predictive Modeling Frameworks
- Application of linear regression techniques
- Application of multiple regression techniques
- Evaluation of underlying data patterns
- Selection and preparation of input variables
- Execution of PROC MI for missing data imputation
Summary and Conclusions
Requirements
- Proficiency in managing hierarchical directory frameworks
Target Audience
- Data Analysts
Testimonials (3)
Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!
Deepthi - Invest Northern Ireland
Course - IBM Cognos Analytics
he was well prepared - and he is very sympathetic
Oliver - Post CH AG
Course - Splunk Fundamentals
lots of pratical exercises