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The webinar provided invaluable insights into the process of translating SAS language to PySpark, showcasing Corios Group's expertise in facilitating smooth transitions for organisations embracing open-source frameworks. Attendees gained a deeper understanding of the challenges and opportunities associated with modernising SAS workloads, along with practical strategies for successful migration.

What is PySpark?

PySpark code is typically written in Python and follows the syntax of the Python programming language.

PySpark provides a Python API for Apache Spark, a fast and general-purpose distributed computing system.

Watch The Highlights

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Website Speakers


Key Points Covered

The webinar titled "Translate SAS Language to PySpark," Vasilij Nevlev from Analytium Group led an enlightening session by Robin Way, CEO, and founder of Corios Group. Robin, with over 40 years of SAS experience, delved into the intricacies of modernising SAS workloads into open-source frameworks, particularly focusing on PySpark.

Introduction to Corios Rosetta
Robin introduced Corios Rosetta, a solution comprising software accelerators, methodology, and a training academy to aid clients in modernising SAS workloads. The session explored techniques for translating SAS code into open-source frameworks, with a spotlight on PySpark.
Why Modernise SAS Workloads?

The discussion kicked off by addressing the necessity of modernising SAS workloads, considering factors such as cost, skill availability, and market trends. Robin emphasised the declining preference for SAS among data analytics developers and the growing demand for open-source frameworks.

Real-world Testimonials
Robin presented a case study involving CVS Health's journey to modernise their SAS-based risk scoring platform. By transitioning to Amazon Glue and PySpark, CVS Health achieved a 98% reduction in data processing time and significant cost savings, demonstrating the tangible benefits of modernisation.
Corios Rosetta Methodology
Robin outlined Corios' comprehensive approach to modernisation, starting with assessing existing SAS assets, identifying migration candidates, and executing code and data conversions using the Corios Rosetta suite. He emphasised the importance of job validation to ensure consistency between old and new environments.


Not sure if this is relevant to you? Here are the answers to a few common questions.

Who attended this webinar?

Professionals and practitioners in the fields of data analytics, data science, and related domains. Individuals who are currently using SAS for data processing and analysis and are interested in transitioning to PySpark for its capabilities in handling big data and distributed computing.

What knowledge or tools will I gain from requesting a demo?
Why should I consider transitioning from SAS to PySpark?

You might have questions about the advantages of moving from SAS to PySpark. The webinar can address this by explaining the benefits of PySpark, such as its scalability, ability to handle big data, and integration with the Python ecosystem. Clear insights into the practical advantages for data analysis and processing can help you understand the rationale behind the transition.

Other Resources

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Vasilij Nevlev
Post by Vasilij Nevlev
Mar, '24
Vasilij is the founder of Analytium. His career is characterised by a data driven mindset, which he now uses to achieve great results for others.