Informatica recently introduced a serverless, Spark-based data integration engine that features improved performance using NVIDIA RAPIDS Accelerator for Apache Spark. The first time, Informatica gives an explanation where it says, “users have access to end-to-end machine learning operations (MLOps) capabilities by operationalizing machine learning models, and to the power of data management with the scalability and speed delivered by RAPIDS data science software and NVIDIA infrastructure.” The release comes on the heels of Informatica’s January Launch of SaaS MDM.
The company has its big data management platform that allows organizations to access, integrate, clean, master, and govern. The tools’ features include connectivity to hundreds of data sources, real-time streaming, and mass ingestion. Informatica has a visual development interface that ensures that the best open-source platforms can be adopted without compromising usability. One can now find public cloud support for extensive data management on AWS and Microsoft Azure.
The Informatica NVIDIA data integration engine is equipped with increased data processing speed up to five times, letting customers work on their data management workloads and implement machine learning.
“Data science is the backbone of AI, as it is key to transforming oceans of enterprise data into business opportunities,” said Manuvir Das, Head of Enterprise Computing, NVIDIA. “Informatica’s integration of RAPIDS Accelerator for Apache Spark with NVIDIA accelerated computing brings the world’s most advanced infrastructure to the many industries that rely on Informatica’s enterprise cloud data management solutions, enabling customers to speed their data science and AI pipelines across their cloud and on-prem data centers.”
Talking about the product, Informatica Chief Product Officer Jitesh Ghai said, “You can’t leverage the power of data and gain valuable insights if you are restricted in your data access. Our collaboration with NVIDIA is valuable to bringing enterprise-scale data democratization and narrowing the gap between the data-haves and the data-have-nots within the enterprise. This important milestone with NVIDIA shows our continued commitment to unlock the value of data embedded in organizations across all levels and more importantly empower all key users to gain faster business-critical insights and operationalize data analytics and data science projects at scale.”
