How to monitor and analyze your entire cloud infrastructure

The existing “Do-It-Yourself AI” solutions involve enterprises to procure, integrate, test and continuously perform maintenance of hardware and (open source) software - all by themselves. In the process, they lose valuable months to jumpstart their AI initiatives and underutilized their resources during this crucial phase. In this session, you will get the best-practices for the design and deployment of AI infrastructure, and learn how to build an AI platform that will deliver faster-time-to-insights and enable your data scientists to be more productive.

Learn how Arrow enables customers to address big business challenges and start the journey to a digital transformation of their business with advanced tools and services. Arrow’s Distribution capabilities now extend to supporting customers with complete Technology Platforms and Solutions. By aggregating electronics and enterprise computing solutions, Arrow is enabling customers from idea creation through the development of the complete technology stack, creating optimized designs capable of scaling for mass production and full deployment. Complex designs are supported by Arrow in-house engineering services and system integration, with the design competence to help customers address big business challenges and create easy to use and easy to deploy solutions.

Join this webinar to learn how to build an IoT data management solution at the endpoint, using commercial tools for IoT databases, data distribution systems on Linux. We’ll also discuss how to manage and analyze sensor data locally within the Industrial IoT paradigm for faster responses and to reduce reliance on the cloud infrastructure.

Want to make your digital transformation a success? Data governance and access control are key to that effort. Even if digital transformation doesn’t motivate you, compliance with GDPR, CCPA – and other regulatory frameworks for data protection – should. But implementing access controls manually, one data source at a time, won’t cut it anymore. Instead, you need a policy- and workflow-based approach that works across different repositories and platforms, in databases and data lakes, both on-premises and across multiple clouds.