Four Principles for Engineering Scalable, Big Data Systems
In this podcast, Ian Gorton describes four general principles that hold for any scalable, big data system. These principles can help architects continually validate major design decisions across development iterations, and hence provide a guide through the complex collection of design trade-offs all big data systems require.
About the Speaker
Suzanne Miller is a principal researcher at the Software Engineering Institute of Carnegie Mellon University in the Continuous Deployment of Capability Directorate. Miller actively supports multiple large DoD cyber-physical programs in their Agile/Lean adoption efforts, in addition to designing and teaching Agile courses and workshops tuned to government settings. Miller …Read more