Good news for application developers and data scientists: Analytics leader SAS has extended the reach of its flagship SAS Viya platform to support open source users. Whether the software user needs to develop an API-first strategy, fuel a data preparation routine with machine learning or improve interoperability, SAS Viya is a game changer for open source integration and utility.
Data scientists report they spend 50% to 80% of their time enmeshed in the tedium of collecting and preparing structured and unstructured data so it can become useful. Once a model is built to analyze that data, deploying it can be nightmarish. SAS Viya is built to help relieve that stress.
SAS Executive Vice President and CTO Bryan Harris said simplifying and automating data collection and model deployment are critical regardless of the technologies you choose. “When you figure this out for your ecosystem, the payoff is huge,” he said. “SAS Viya can help get you there.”
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“Open source is flexible and cost effective,” said Ritu Jyoti, Group Vice President, Worldwide AI and Automation Research Practice at IDC. “And to extract the most value from open source models, users need a platform that simplifies and secures data and model management so users can trust the decisions they make. SAS Viya helps users confidently bridge that gap.”
Canadian hackathon team uses SAS and open source to optimize traffic sensors in emergencies
Members of Hackanadians, a 2021 HackinSAS hackathon team, used techniques that combined SAS and the open source Jupyter Hub to create an audio-based intersection management app for emergency vehicle prioritization. The artificial intelligence (AI) application uses optimization, IoT sensors, machine learning and deep learning to detect sirens and commandeer traffic signals to allow emergency vehicles to pass more safely through traffic.
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“The application of AI, the Internet of Things, and discrete, even simulation allowed us to offer an end-to-end solution to traffic intersection management for the benefit of the public good,” said Heather Friesen, Hackanadians team leader.
SAS Viya improves confident decisions by automating model development, deployment and governance
Open source is a proven, viable software development methodology. And using open source to resolve challenges and create business value demands a structured, unified framework for orchestration support. Many organizations rely on a robust data science and machine learning platform like SAS Viya to smooth those issues and allow developers to personalize their experience, such as using their preferred language with their favorite software, tools and libraries. The top reasons organizations cite for pulling in Viya include:
- Harnessing its cloud-native, high-performance architecture.
- Building models faster using massively parallel processing for endless scalability.
- Automated feature engineering with machine-learning-powered data preparation.
- Establishing model governance and management processes for SAS and open source.
- Using Python or R directly with SAS or integrating SAS into applications using REST APIs.
- Deploying models developed in SAS or open source to different environments such as cloud, containers, streaming or on-site edge devices.
- Writing and running native Python code directly in the SAS development interface to operationalize work.
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