April Chapter Meeting: The Next Generation of Big Data - Building Real-Time Models of Reality

Real-Time Models of Reality

Big Data applications have traditionally focused on human-scale data sources, data created directly or indirectly by the intentional actions of people. Today, we are transitioning to the era of machine-scale data sources undefined the Internet of Things, sensor networks, mobile platforms, the Industrial Internet undefined which creates several unique challenges for data management and architecture. Machine-scale data is orders of magnitude higher volume and higher velocity; data sources include an unprecedented variety of data types; data models must fuse and act on diverse, unrelated data sources in real-time; and spatio-temporal relationships are central to data organization.

What You Will Learn

In this presentation, we will:

• explore the implications of machine-scale Big Data with respect to traditional data management,
• identify many of the unique pitfalls and best practices for these types of data models, and
• provide real-world example cases of data models that fused a wide range of traditional, social media, and sensor data sources.

Speaker Profile

R Andrew Roger is currently the CTO of SpaceCurve and a pioneer in the development of distributed database technologies for real-time geospatial systems and graph analysis. Prior to founding SpaceCurve, Andrew was vice president for geospatial systems at Neopolitan where he created a practice enabling the integration of sensor data with traditional map-like systems. Previously Andrew led large-scale analytic and geospatial systems development efforts for Google Earth, CBS News, and UK Met Office and was a systems architect for Netflix, Cisco, and France Telecom.