MapR Experts Author New Book on AI and Analytics

According to a recent announcement, MapR Technologies, a data platform for AI and Analytics, has released a new book, “AI and Analytics in Production,” written for a C-level execs (CIO, CTO, CDO), business team leaders, architects, system administrators, data engineers and data scientists.

Authored by Ted Dunning, PhD, board member of the Apache Software Foundation and chief application architect at MapR, and Ellen Friedman, PhD, principal technologist at MapR and Apache committer, and published by O’Reilly Media, the book examines best practices for maximizing the value of data-driven applications in production.

Dunning and Friedman assert that value from big data becomes real when the data-intensive applications built to extract value from data go into production. But for that to be successful, businesses must have a way to take action based on the insights from those applications, action that is tied to practical business goals. Running a large-scale data project in production can be challenging, but there are ways to make it easier and more likely to succeed.

The book provides a guide to best practices for production based on the authors’ combined experiences and observations of real-world production use cases across a wide range of industries so that readers can gain from what has made others successful.

Readers will learn:

• The goals, challenges and potential pitfalls of deploying analytics and AI/ machine learning to production across multi-cloud systems, on-premises or at the IoT edge
• How to best plan, design and execute large data systems tied to practical business considerations
• The role of multitenancy, a comprehensive data fabric and the powerful combination of Kubernetes-orchestrated containerization coupled with a data platform able to persist data from containerized applications
• How to develop a production-ready culture across your organization
• The special issues related to AI/ machine learning in production
• A collection of fundamental design patterns that can be customized and combined for your own use cases