SAS DI Assessment Test

An SAS DI (Data Integration) Assessment Test evaluates candidates on their proficiency in using SAS Data Integration Studio for designing, developing, and managing data integration processes.

A SAS DI Assessment Test evaluates candidates for:

1. SAS DI Studio Overview:
   • Understanding of SAS Data Integration Studio, its purpose, and its role in designing and managing data integration jobs and workflows.
2. Data Sources and Targets:
   • Proficiency in connecting SAS DI Studio to various data sources (e.g., databases, flat files, XML files) and targets (e.g., data warehouses, data marts), configuring data source properties, and defining target schemas.
3. Job Design and Development:
   • Skills in designing data integration jobs in SAS DI Studio using drag-and-drop interface, arranging transformations (e.g., extract, transform, load - ETL processes), defining data flows, and scheduling job execution.
4. Transformations and Data Quality:
   • Experience in using SAS DI Studio transformations (e.g., query, join, filter, aggregate) to manipulate data, ensure data quality, perform data cleansing, validate data integrity, and handle data anomalies.
5. Metadata Management:
   • Techniques for managing metadata within SAS DI Studio, including creating metadata definitions, importing metadata from external sources, maintaining metadata repositories, and ensuring metadata consistency.
6. Error Handling and Logging:
   • Knowledge of implementing error handling mechanisms in SAS DI jobs, configuring error handling nodes, defining error handling strategies (e.g., retry logic, error notification), and logging job execution details for troubleshooting.
7. Scheduling and Automation:
   • Skills in scheduling SAS DI jobs for automated execution, configuring job schedules, dependencies, and job triggers, monitoring job status, and managing job execution queues.
8. Data Integration Performance:
   • Techniques for optimizing SAS DI job performance, improving data integration throughput, reducing job execution time, tuning data transformation processes, and managing resource utilization.
9. Deployment and Version Control:
   • Experience in deploying SAS DI jobs to production environments, promoting job versions across development, testing, and production environments, and using version control systems (e.g., Git) for managing job versions.
10. Integration with SAS and External Systems:
    • Knowledge of integrating SAS DI Studio with other SAS products (e.g., SAS Analytics, SAS Visual Analytics) and external systems (e.g., ERP systems, CRM systems) using SAS APIs, connectors, and data exchange protocols.
11. Security and Access Control:
    • Understanding of SAS DI Studio security features, configuring user roles, permissions, and access controls, implementing data encryption, ensuring data confidentiality, and protecting against unauthorized access.
12. Documentation and Best Practices:
    • Commitment to documenting SAS DI Studio configurations, job designs, transformation logic, data integration workflows, and best practices for maintaining data integrity and optimizing data integration processes.
13. Continuous Learning and Development:
    • Commitment to staying updated with SAS DI Studio updates and features, attending SAS webinars and training sessions, obtaining relevant certifications (e.g., SAS Certified Data Integration Developer), and contributing to SAS community forums.

Overall, an SAS DI Assessment Test assesses candidates' abilities to design, develop, and manage data integration processes using SAS Data Integration Studio, ensuring efficient data movement, transformation, and integration across enterprise environments.

This evaluation helps identify individuals who can contribute effectively to data integration projects and support data-driven decision-making using SAS technologies.