Course Outline
Overview
Detailed Examination of SAS Capabilities
- Structure and composition of SAS data sets
- Definition and attributes of SAS variables
- Organization and storage within SAS libraries
- Syntax and architecture of SAS code
Configuration of the Development Environment
- Deployment and setup of SAS Studio
- Installation and configuration of WPS
Data Administration in SAS
- Data ingestion processes
- Data exportation methods
- Derivation of variables and computational logic
- Selection and filtration of observations
- Implementation of conditional logic and iterative processes
- Integration of multiple data sets
- Utilization of specific SAS statements
- Data hygiene and quality assurance
Application of Arrays and Functions
- Generation of new variables using iterative loops
- Construction of derived variables
- Utilization of native SAS functions
- Consolidation of raw data files
Data Visualization Techniques
- Generation of bar charts
- Creation of scatter plots
- Development of pie graphs
- Superimposition of graphical elements
Statistical Analysis
- Reporting and summarization of data
- Application of linear regression models
- Execution of multiple regression analyses
- Interpretation of statistical findings
- Development of predictive forecasts
SAS SQL Implementation
- Syntax standards for SAS SQL
- Application of SQL clauses and commands
- Manipulation of columns and row structures
- Management of tabular data structures
SAS Indexing Strategies
- Performance testing with data sets
- Utilization of PROC procedures
- Creation, maintenance, and application of indexes
SAS Macro Programming
- Utilization of macro variables
- Application of macro functions
- Development of macro routines
- Troubleshooting and persistence of macro code
Predictive Modeling Frameworks
- Implementation of linear regression models
- Application of multiple regression models
- Analysis of data patterns and trends
- Integration of input variables
- Utilization of PROC MI for missing data handling
Summary and Concluding Remarks
Requirements
- Familiarity with navigating file and folder hierarchies
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