Top 12 SAS Developer Skills to Put on Your Resume

In today’s data-driven world, SAS developers are in high demand, making it essential for aspiring professionals to highlight the right skills on their resumes. Mastering a blend of technical prowess and analytical acumen can set you apart in the competitive field of SAS development, paving the way for a successful career.

SAS Developer Skills

1. SAS Base
2. SAS Macro
3. SAS/STAT
4. SAS/GRAPH
5. SAS/SQL
6. SAS Enterprise Guide
7. SAS Visual Analytics
8. SAS Data Integration Studio
9. SAS Viya
10. Hadoop Integration
11. Python (for SASPy)
12. R (for integration)

1. SAS Base

SAS Base is a core component of the SAS software suite used for data access, manipulation, analysis, and reporting. It provides a programming language environment for SAS developers to work with data in various formats and perform statistical analysis.

Why It's Important

SAS Base is crucial for an SAS Developer as it provides the foundational programming language and tools necessary for data management, analysis, and reporting, enabling the creation of sophisticated statistical models and insights from large datasets.

How to Improve SAS Base Skills

Improving your SAS Base skills as an SAS Developer involves a combination of foundational knowledge enhancement, practical experience, and staying updated with the latest trends and features. Here’s a concise guide:

1. Master the Basics: Ensure you have a solid understanding of SAS fundamentals. Focus on data steps, proc steps, arrays, and macro programming. SAS Programming Basics is a great starting point.

2. Practice Regularly: Apply your knowledge through regular practice. Work on real-world problems or datasets. Websites like Kaggle provide datasets for practice.

3. Learn Advanced Techniques: Dive into advanced topics like optimization techniques, high-performance procedures, and advanced data manipulation. The SAS Advanced Programming course is beneficial.

4. Stay Updated: SAS is constantly evolving. Stay updated with the latest features and best practices by following the SAS Official Blog.

5. Join SAS Communities: Engage with other SAS professionals. Share knowledge and get answers to your questions. The SAS Community is a great platform.

6. Utilize SAS Documentation: The SAS Documentation portal is an invaluable resource for in-depth understanding and troubleshooting.

7. Certification: Consider obtaining a SAS Certification. It not only validates your skills but also keeps you motivated to learn.

8. Use SAS University Edition: For hands-on practice, use the SAS University Edition, which is free for learning purposes.

Improving your SAS Base skills is a continuous process. By combining theoretical knowledge with practical experience and engaging with the community, you can enhance your proficiency as an SAS Developer.

How to Display SAS Base Skills on Your Resume

2. SAS Macro

SAS Macro is a powerful SAS programming tool that allows developers to automate repetitive tasks and parameterize code by defining macro variables and creating macro programs, thereby enhancing code reusability, efficiency, and scalability in data processing and analysis tasks.

Why It's Important

For an SAS developer, SAS Macro is important because it allows for code reusability, simplifies complex code, enhances program flexibility, and enables parameterization, thereby streamlining workflow and improving efficiency in data analysis and reporting tasks.

How to Improve SAS Macro Skills

Improving your SAS Macro skills involves a combination of understanding best practices, optimizing code, and continuous learning. Here are concise tips with resources for an SAS developer:

1. Understand Macro Variables and Scopes: Grasp the difference between local and global macro variables to manage your data effectively. SAS Documentation on Macro Variables

2. Use Macro Functions Wisely: Utilize macro functions for text manipulation and conditional logic to make your code more dynamic. SAS Macro Functions

3. Optimize Macro Loops: Only use loops when necessary and optimize their performance by reducing the amount of code executed inside the loop. Efficient Loops in SAS

4. Debug Efficiently: Use %PUT and other debugging techniques to troubleshoot your macros. Understanding how to quickly find and fix issues saves time. Debugging Macros

5. Modularize Your Code: Break down complex macros into smaller, reusable components. This not only makes your code cleaner but also easier to debug and understand. Modular Programming in SAS

6. Adhere to Best Practices: Follow coding conventions and best practices for naming conventions, commenting, and formatting to make your macros maintainable and understandable. SAS Programming Guidelines

7. Keep Learning: SAS is always evolving, so stay updated with the latest features and techniques. Participate in forums, read SAS blogs, and explore SAS conferences and user groups. SAS Communities

Improving SAS macro skills is an ongoing process. Practice regularly, review your code for efficiency, and stay connected with the SAS community to learn from others’ experiences.

How to Display SAS Macro Skills on Your Resume

3. SAS/STAT

SAS/STAT is a suite of statistical analysis tools within the SAS software environment, designed for data analysis and modeling. It provides SAS developers with a wide range of statistical methods to perform advanced data analysis, predictive modeling, and inferential statistics.

Why It's Important

SAS/STAT is important for an SAS Developer because it provides comprehensive statistical methods and analytics capabilities, enabling the development of sophisticated statistical models and the extraction of insights from complex datasets, thereby supporting data-driven decision-making.

How to Improve SAS/STAT Skills

To improve your skills in SAS/STAT, consider the following steps:

1. Official SAS Documentation: Start by thoroughly reviewing SAS/STAT documentation. It covers all procedures and provides examples.

2. Online Courses: Enroll in SAS-specific courses on platforms like SAS Learning. They offer both free and paid courses tailored for developers at different skill levels.

3. Practice: Apply your knowledge on datasets. Websites like Kaggle provide a wide variety of real-world data to work with.

4. Join SAS Communities: Engage with other SAS users in forums such as SAS Communities. Sharing knowledge and solving problems together can significantly boost your understanding.

5. Stay Updated: SAS regularly updates its software. Keep an eye on the What’s New in SAS/STAT page to stay informed about new features and improvements.

6. Read Books: There are several comprehensive books on SAS/STAT. Start with “The Little SAS Book” and explore more advanced topics as you progress.

7. Use SAS Blogs: SAS Blogs, like The SAS Dummy and The DO Loop, provide valuable tips, tricks, and insights into using SAS more effectively.

8. Attend Workshops/Conferences: Whenever possible, attend SAS workshops and conferences. They are great opportunities to learn from experts and network with other professionals.

Continuous practice and engagement with the SAS community are key to improving your SAS/STAT skills effectively.

How to Display SAS/STAT Skills on Your Resume

4. SAS/GRAPH

SAS/GRAPH is a software product from SAS Institute that provides tools for creating sophisticated graphical representations of data, such as charts, plots, and maps, within the SAS programming environment. It enables SAS developers to visualize and present data analysis results in a more meaningful and accessible way.

Why It's Important

For an SAS Developer, SAS/GRAPH is important because it enables the creation of high-quality, customizable graphs and charts from statistical data, enhancing data visualization and interpretation for reporting and decision-making processes.

How to Improve SAS/GRAPH Skills

Improving your SAS/GRAPH skills involves understanding its features and applying best practices. Here are concise tips:

1. Master Basic SAS/GRAPH Syntax: Start with the basics of PROC GPLOT, PROC GCHART, PROC SGPLOT, and PROC SGRENDER to create various types of graphs. Documentation is key. SAS GRAPH Documentation.

2. Utilize Templates and Styles: Learn how to use and customize Graph Template Language (GTL) and style templates for consistent and visually appealing graphics. GTL Guide: SAS GTL Guide.

3. Incorporate Annotations: Use the ANNOTATE facility to add custom annotations to your graphs for more detailed and informative visualizations. Annotation Guide: SAS/GRAPH Annotate.

4. Optimize Data Preparation: Ensure your data is in the best format for graphing, including using summary procedures and data step processing for optimal graph source data. SAS Data Preparation.

5. Explore Advanced Features: Delve into advanced features like dynamic data-driven graphics, ODS Graphics Designer for custom graphs, and integration with other SAS procedures for enhanced analytics. ODS Graphics Designer: ODS Graphics Designer.

6. Practice and Examples: Practice creating a variety of graphs using sample datasets. Reviewing and replicating examples can solidify your understanding and inspire new ideas. SAS/GRAPH Samples.

7. Stay Updated and Engage with the Community: SAS software updates regularly. Stay informed about new features and best practices by engaging with the SAS community and forums. SAS Communities.

By focusing on these areas, you can significantly improve your SAS/GRAPH capabilities, leading to more effective data visualization and analysis within your SAS development projects.

How to Display SAS/GRAPH Skills on Your Resume

5. SAS/SQL

SAS/SQL is a component of SAS (Statistical Analysis System) that allows SAS developers to use SQL (Structured Query Language) syntax within SAS programs to query, manipulate, and manage data stored in relational database management systems (RDBMS), enabling complex data retrieval and management tasks in a familiar SQL syntax alongside SAS functionalities.

Why It's Important

SAS/SQL is important for an SAS Developer because it enables efficient data manipulation, querying, and management within large databases, facilitating complex data analysis, reporting, and integration tasks crucial for data-driven decision making and insights.

How to Improve SAS/SQL Skills

Improving your skills in SAS/SQL as an SAS Developer involves a blend of understanding core concepts, practicing coding, and keeping updated with the latest features. Here’s a concise guide:

1. Understand Core SAS/SQL Concepts: Master the basics of SAS programming and SQL querying. Focus on data manipulation techniques, understanding JOINs, sub-queries, and set operations.

2. Practice Coding Regularly: Apply your knowledge by solving real-world problems. Use platforms like LeetCode and HackerRank for practice.

3. Learn Advanced Features: Stay updated with advanced SAS features and SQL functions. Explore SAS Documentation and use resources like SQLZoo for advanced SQL.

4. Optimize Code for Performance: Learn about indexing, query optimization, and efficient data storage. The Use The Index, Luke guide is a good start for understanding indexing and optimization in SQL.

5. Join Forums and Communities: Engage in communities like Stack Overflow for SAS and Database Administrators Stack Exchange for SQL to learn from real-world issues and solutions.

6. Follow Blogs and Tutorials: Websites like SASCrunch offer practical tutorials and exercises. For SQL, Mode Analytics SQL Tutorial provides interactive lessons.

7. Work on Projects: Apply your skills to projects that interest you. This could be anything from analyzing a dataset to automating a data cleaning process. GitHub is a great platform to find project ideas and collaborate.

8. Certification and Courses: Consider obtaining certifications like SAS Certified Specialist or taking courses on Udemy and Coursera that are specific to SAS and SQL.

Remember, consistency in practice and staying curious about new developments in SAS/SQL are key to continuous improvement.

How to Display SAS/SQL Skills on Your Resume

6. SAS Enterprise Guide

SAS Enterprise Guide is an integrated development environment (IDE) for SAS programming and analytics. It provides a user-friendly, point-and-click interface that enables SAS developers to access data, perform complex analyses, manage projects, and create reports without needing to write code, although it also supports custom code writing and editing for advanced users.

Why It's Important

SAS Enterprise Guide is important for an SAS Developer as it provides an intuitive, graphical user interface that simplifies data analysis, enables automation of complex processes, and enhances productivity by allowing for easy access to SAS analytics and reporting tools.

How to Improve SAS Enterprise Guide Skills

Improving your SAS Enterprise Guide experience involves enhancing efficiency, leveraging advanced features, and customizing the environment to suit your development style. Here are concise tips:

1. Master Shortcuts: Familiarize yourself with keyboard shortcuts to navigate and execute tasks faster.

2. Use Tasks and Wizards: Exploit built-in tasks and wizards for data manipulation and analysis, minimizing coding efforts.

3. Customize Environment: Tailor your work environment settings to streamline your workflow, including the layout and default behaviors.

4. Utilize Macros: Develop and employ SAS macros to automate repetitive tasks and improve code reusability.

5. Learn Advanced Features: Deepen your knowledge on advanced features by exploring SAS papers and SAS communities for expert tips and tricks.

6. Optimize Performance: Apply best practices for performance tuning, such as efficient data access and minimizing data processing steps.

7. Stay Updated: Regularly update your SAS Enterprise Guide to the latest version to benefit from new features and performance improvements. Check SAS support for updates.

By focusing on these areas, you can significantly enhance your productivity and effectiveness as a SAS developer using SAS Enterprise Guide.

How to Display SAS Enterprise Guide Skills on Your Resume

7. SAS Visual Analytics

SAS Visual Analytics is a data visualization and business intelligence tool within the SAS software suite, enabling developers to analyze data, create interactive reports and dashboards, and share insights across an organization. It offers advanced analytics capabilities like forecasting and decision trees, integrating seamlessly with SAS programming for more complex analysis.

Why It's Important

For an SAS Developer, SAS Visual Analytics is crucial because it enables the rapid creation and sharing of interactive, visually appealing reports and dashboards from complex datasets, enhancing data-driven decision making and communication.

How to Improve SAS Visual Analytics Skills

To improve SAS Visual Analytics, follow these concise steps:

1. Leverage Best Practices: Familiarize yourself with best practices for data visualization and dashboard design. SAS provides guidance on effective visual analytics strategies here.

2. Optimize Data Preparation: Ensure your data is clean, formatted correctly, and optimized for analysis. SAS offers tips on data preparation here.

3. Utilize Advanced Analytics: Incorporate advanced analytics and machine learning models into your visualizations for deeper insights. Learn more about SAS Visual Data Mining and Machine Learning here.

4. Customize Reports: Tailor your reports and dashboards to the needs of your audience. SAS Visual Analytics allows for extensive customization, which is detailed in their documentation.

5. Enhance Interactivity: Make your reports interactive with filters, prompts, and dynamic elements to enable users to explore data in real time. SAS provides examples and tips here.

6. Stay Updated: Always use the latest version of SAS Visual Analytics to take advantage of new features and improvements. Check the latest updates and features here.

7. Training and Certification: Continuously improve your skills by taking advantage of SAS training and certification programs. Explore training options here.

By following these steps and utilizing the provided resources, you can significantly enhance your proficiency and effectiveness in using SAS Visual Analytics.

How to Display SAS Visual Analytics Skills on Your Resume

8. SAS Data Integration Studio

SAS Data Integration Studio is a visual design tool that allows SAS developers to build, implement, and manage data integration processes across multiple sources and targets, facilitating data warehousing, data migration, and data transformation.

Why It's Important

SAS Data Integration Studio is important for an SAS Developer because it provides a powerful, visual toolset for building, implementing, and managing complex data integration processes without the need for extensive coding, thereby enhancing productivity and ensuring data accuracy and consistency across diverse sources.

How to Improve SAS Data Integration Studio Skills

Improving your skills in SAS Data Integration Studio involves a combination of understanding its features, practicing regularly, and staying updated with the latest enhancements. Here's a concise guide:

1. Understand Core Concepts: Start with a solid foundation in SAS Data Integration Studio's core concepts, including its architecture, data management capabilities, and ETL (Extract, Transform, Load) processes. The official SAS documentation offers comprehensive insights.

2. Hands-on Practice: Apply your knowledge through projects. Practice integrating, transforming, and managing data from various sources. This hands-on experience is crucial for mastering the tool.

3. Use SAS Communities and Forums: Engage with the SAS Community to learn from experienced professionals, share your knowledge, and stay informed about new features and best practices.

4. Official SAS Training and Documentation: Leverage SAS training courses and certifications specifically designed for data integration. SAS provides both free and paid resources that are structured and comprehensive.

5. Explore Advanced Features: Dive into advanced features like error handling, custom transformations, and performance tuning to enhance your data integration processes. The SAS support documentation is a great resource for detailed information.

6. Stay Updated: Technology evolves rapidly, and so does SAS Data Integration Studio. Follow SAS blogs and subscribe to newsletters to keep up with the latest updates and features.

7. Network with Other Developers: Networking with peers can provide insights into new and effective ways of using SAS Data Integration Studio. Attend SAS conferences, webinars, and user groups to connect with other professionals.

By focusing on these areas, you'll enhance your proficiency in SAS Data Integration Studio, making you a more effective and efficient SAS Developer.

How to Display SAS Data Integration Studio Skills on Your Resume

9. SAS Viya

SAS Viya is a cloud-enabled, in-memory analytics engine designed to deliver rapid, scalable, and robust analytics solutions. It allows SAS developers to build, deploy, and manage complex analytics and machine learning models using the latest programming languages and open-source tools within an integrated, collaborative environment.

Why It's Important

SAS Viya is important for an SAS Developer because it offers a cloud-enabled, in-memory analytics engine that enables scalable, high-performance, and robust data processing and machine learning capabilities, facilitating integration with other languages (e.g., Python, R), and supports collaborative efforts across various environments, significantly enhancing analytical workflows and application development efficiency.

How to Improve SAS Viya Skills

Improving your skills in SAS Viya as an SAS Developer involves a combination of understanding the platform's capabilities, hands-on practice, leveraging available resources, and staying updated on the latest features. Here are concise steps to enhance your proficiency:

1. Familiarize with SAS Viya Documentation: Start by thoroughly reading the official SAS Viya documentation to understand its architecture, features, and how it differs from SAS 9.

2. Utilize SAS Communities: Engage with the SAS Communities, specifically the Viya section, to learn from experienced developers and share knowledge.

3. SAS Programming on Viya Courses: Take advantage of SAS Viya programming courses to build and enhance your technical skills through structured learning.

4. Practice with SAS Viya for Learners: Get hands-on experience by using SAS Viya for Learners, which offers a free version of SAS Viya for academic and learning purposes.

5. Explore SAS Viya REST APIs: Learn to interact with SAS Viya programmatically using its REST APIs for more flexibility and integration capabilities. The REST APIs documentation is an excellent starting point.

6. Stay Updated: SAS frequently updates Viya with new features and improvements. Keep abreast of these changes by regularly checking the SAS Viya What’s New page.

7. Join SAS Webinars and Workshops: Participate in SAS webinars and workshops focused on SAS Viya to learn about best practices, new features, and advanced techniques.

8. Experiment and Build Projects: Apply your knowledge by working on real-world projects or challenges. Experiment with different features and tools within SAS Viya to understand their practical applications.

By combining these resources and approaches, you can significantly improve your SAS Viya skills and enhance your capabilities as an SAS Developer.

How to Display SAS Viya Skills on Your Resume

10. Hadoop Integration

Hadoop Integration for an SAS Developer involves utilizing SAS software tools to process, analyze, and derive insights from large datasets stored in a Hadoop environment. This integration enables the combination of SAS's advanced analytics capabilities with Hadoop's scalable data storage and processing framework, allowing for efficient big data analysis.

Why It's Important

Hadoop integration is essential for an SAS Developer because it allows for the processing and analysis of vast amounts of unstructured data within the SAS environment, leveraging Hadoop's distributed computing power and scalability, thereby enhancing data-driven decision-making capabilities.

How to Improve Hadoop Integration Skills

Improving Hadoop integration, especially from an SAS Developer's perspective, involves enhancing data processing and analytics capabilities by leveraging the power of Hadoop's distributed computing. Here are concise steps to achieve better integration:

1. Leverage SAS/ACCESS Interface to Hadoop: Utilize SAS/ACCESS Interface to Hadoop to streamline data access, management, and analysis between SAS and Hadoop. It simplifies the process of running SAS analytics on Hadoop data.

2. Utilize SAS Data Loader for Hadoop: Employ SAS Data Loader for Hadoop to enhance data preparation, quality, and governance without writing Hadoop code, making integration more efficient.

3. Incorporate SAS Visual Analytics: Integrate SAS Visual Analytics to visualize Hadoop data and gain insights through interactive reports and dashboards.

4. Adopt SAS In-Database Technologies: Use SAS In-Database Technologies for Hadoop to perform analytics directly on Hadoop data, reducing data movement and accelerating insights.

5. Embrace Hadoop Best Practices: Follow Hadoop's best practices for data management and processing to ensure efficient integration. This includes optimizing Hadoop's storage and compute resources. The Apache Hadoop documentation provides guidelines and best practices.

6. Continuous Learning and Training: Stay updated with the latest advancements in Hadoop and SAS integration technologies through continuous learning. SAS offers training and certification to help developers enhance their skills.

By focusing on these aspects, an SAS Developer can significantly improve Hadoop integration, leading to more efficient data processing and analytics capabilities.

How to Display Hadoop Integration Skills on Your Resume

11. Python (for SASPy)

Python for SASPy is a Python module that enables a Python developer to connect to and run SAS code, access SAS datasets, and convert data between SAS and pandas data frames, effectively bridging the capabilities of Python and SAS programming environments.

Why It's Important

Python, through SASPy, enables SAS developers to leverage Python's extensive libraries and flexibility for data manipulation, analysis, and visualization, directly within SAS environments, enhancing productivity and expanding analytical capabilities.

How to Improve Python (for SASPy) Skills

To improve your Python skills for SASPy—a Python interface to SAS—focus on the following concise steps, tailored for an SAS developer:

1. Understand Python Basics: Ensure you're comfortable with Python syntax and basic programming concepts. Python's official documentation is an excellent start.

2. Learn Pandas: SASPy converts SAS data sets to Pandas data frames, so understanding Pandas is crucial for data manipulation.

3. Familiarize with SASPy: Explore the SASPy documentation to understand its capabilities, installation, and configuration.

4. Practice Data Manipulation: Apply your knowledge by performing common data manipulation tasks in Python that you would do in SAS. This Data Manipulation in Python: A Pandas Crash Course can help.

5. Integrate SAS and Python: Start small by running simple SAS procedures from Python using SASPy and gradually increase complexity. The SASPy examples on GitHub can provide inspiration.

6. Join Communities: Engage with communities on platforms like Stack Overflow or the SAS and Python Users Group for support and knowledge exchange.

By following these steps and utilizing the provided resources, you'll be well on your way to effectively using Python and SASPy for your SAS-related tasks.

How to Display Python (for SASPy) Skills on Your Resume

12. R (for integration)

In the context of integration for an SAS Developer, "R" refers to a programming language and environment used for statistical computing and graphics. It provides extensive libraries for data manipulation, calculation, and graphical display, allowing for intricate statistical analysis and data integration tasks. R can be integrated with SAS to enhance statistical modeling, data analysis, and visualization capabilities.

Why It's Important

R is important for an SAS Developer because it offers advanced statistical and graphical capabilities, enabling more sophisticated data analysis and visualization, thus complementing SAS's functionalities for more comprehensive data science projects.

How to Improve R (for integration) Skills

Improving your R skills for integration, especially coming from an SAS background, involves understanding how to leverage R's capabilities in data manipulation, statistical analysis, and integration with other tools. Here’s a concise guide:

1. Learn the Basics: If you're new to R, start with the fundamentals. DataCamp’s Introduction to R is a great starting point for SAS developers.

2. Understand Data Manipulation: Familiarize yourself with the dplyr and data.table packages for efficient data manipulation. The R for Data Science book by Hadley Wickham is an excellent resource.

3. Master R Integration Techniques: Learn how to integrate R within SAS processes. The SAS Documentation on calling R from SAS using the PROC IML procedure is directly relevant.

4. Use RMarkdown for Reporting: Get comfortable with RMarkdown for creating dynamic reports. This integrates well with SAS datasets and can be shared easily. The RMarkdown Guide is a key resource.

5. Learn Shiny for Web Applications: To make your analyses interactive, learn Shiny. This can be particularly useful for sharing insights with non-technical stakeholders. Start with the Official Shiny Tutorial.

6. Join R and SAS Communities: Engage with both R and SAS communities. Stack Overflow for R and SAS Communities are excellent places to exchange knowledge and get help.

7. Practice with Real-World Datasets: Apply what you learn on platforms like Kaggle, using their datasets for practice and joining competitions to challenge yourself.

By progressing through these steps and leveraging the provided resources, you'll significantly improve your R skills for integration purposes as an SAS developer.

How to Display R (for integration) Skills on Your Resume