The Unrealized Opportunities with Real-Time Data

The amount of data generated from various processes and platforms has increased exponentially in the past decade, and the challenges of filtering useful data out of streams of raw data has become even greater. Meanwhile, the essence of making useful insights from that data has become even more important.

In this incisive report, Federico Castanedo examines the challenges companies face when acting on data at rest as well as the benefits you unlock when acting on data as it's generated. Data engineers, enterprise architects, CTOs, and CIOs will explore the tools, processes, and mindset your company needs to process streaming data in real time.

Learn how to make quick data-driven decisions to gain an edge on competitors. This report helps you:

• Explore gaps in today's real-time data architectures, including the limitations of real-time analytics to act on data immediately
• Examine use cases that can't be served efficiently with real-time analytics
• Understand how stream processing engines work with real-time data
• Learn how distributed data processing architectures, stream processing, streaming analytics, and event-based architectures relate to real-time data
• Understand how to transition from traditional batch processing environments to stream processing

Federico Castanedo is an academic director and adjunct professor at IE University in Spain. A data science and AI leader, he has extensive experience in academia, industry, and startups.