Predictive Analytics for the Modern Enterprise

The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics in the cloud. Author Nooruddin Abbas Ali, principal solutions architect at MongoDB, brings you up to speed through industry use cases and end-to-end hands-on examples. This book helps business technology leaders: Implement and operationalize predictive analytics in your organization Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow

Nooruddin Abbas Ali is a Principal Solutions Architect at MongoDB. This select global team works with innovative customers and partners looking to disrupt their respective industries. It is the team's belief that data is the key to unlocking business potential and bringing about the sustainable disruption that moves the human race forward. He has been in the tech and service management industry for over 18 years, where he has held several positions in development, professional services, management, pre-sales, and thought leadership. He has worked for 0-1 startups, large public cloud providers (Alibaba Cloud), hypergrowth data platform companies (MongoDB), and end-to-end large system integrators. He has been working with distributed data systems and cloud technologies for over a decade. Nooruddin has experience and credentials in multiple cloud technologies, architecture best practices, and Big Data and Application Data platforms. This unique combination of data and cloud skills, coupled with his experience at various levels of the enterprise spectrum, has allowed him to amass the knowledge and field experience required to build this book that is multi-faceted yet in-depth on core foundations of predictive analytics.