IDC MarketScape deems SAS a leader for machine learning operations (MLOps) platforms
SAS has been named a leader in the inaugural IDC MarketScape: Worldwide Machine Learning Operations Platforms 2022 Vendor Assessment (doc #US48325822, December 2022). The report noted that as organizations are moving more models from experimentation to production, they need scalable ways to collaborate, operate and operationalize machine learning models. Machine learning operations (MLOps) help enterprise organizations manage the unique challenges of machine learning and enable collaboration and communication between data scientists, data architects, business analysts and operations professionals.
According to Kathy Lange, Research Director of AI Software research at IDC, “Top challenges that customers face with implementing machine learning initiatives in production include lack of expertise, cost and lack of automation. MLOps software and processes enable customers to overcome these challenges by improving collaboration between data scientists, application developers, and operational engineers; automating end-to-end model life-cycle management; and increasing model velocity.”
The report evaluated SAS® Model Manager – the MLOps solution included in the SAS® Viya® analytics and machine learning platform. “SAS Model Manager provides a wide range of related services and products that can assist with production of machine learning models in the enterprise,” it says, noting SAS’ strengths in flexible language and model support, as well as strong governance and production capabilities.
“A recent study of data scientists revealed that more than 40 percent of the time, analytics results are not being used by business decision makers,” said Marinela Profi, AI Product Strategy Lead for Analytics and MLOps, SAS. “There is clearly a gap between finding insights and using insights, and the integration of a ModelOps – or MLOps – tool is key to overcoming this gap.”
Recently, AI and analytics powerhouse SAS brought its cutting-edge analytics solutions to more people than ever with SAS Viya on the Microsoft Azure marketplace, which includes SAS Model Manager for the execution of fast model deployment and strong model governance. SAS Viya on Microsoft Azure combines robust data management, powerful machine learning and streamlined model deployment, all available with a click of a button in a pay-as-you-go format.
“The secret for a successful MLOps practice is to not adopt different sets of tools that perform individual tasks but rather implement a comprehensive solution that does everything for you and speaks to both data scientists and IT, reducing complexity and increasing usability,” said Profi. “And this is what SAS Model Manager is.”
The IDC MarketScape report is the latest recognition from top industry analyst firms for SAS AI, machine learning and advanced analytics capabilities.
About IDC MarketScape
IDC MarketScape vendor assessment model is designed to provide an overview of the competitive fitness of ICT (information and communications technology) suppliers in a given market. The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each vendor’s position within a given market. IDC MarketScape provides a clear framework in which the product and service offerings, capabilities and strategies, and current and future market success factors of IT and telecommunications vendors can be meaningfully compared. The framework also provides technology buyers with a 360-degree assessment of the strengths and weaknesses of current and prospective vendors.
SAS is a global leader in AI and analytics software, including industry-specific solutions. SAS helps organizations transform data into trusted decisions faster by providing knowledge in the moments that matter. SAS gives you THE POWER TO KNOW®.
Machine learning operations (MLOps) help enterprise organizations manage the unique challenges of machine learning and enable collaboration and communication between data scientists, data architects, business analysts and operations professionals.