New data sources, ranging from diverse business transactions to social media, high-resolution sensors, and the Internet of Things, are creating a digital tidal wave of big data that must be captured, processed, integrated, analyzed, and archived. Big data systems storing and analyzing petabytes of data are becoming increasingly common in many application areas. These systems represent major, long-term investments requiring considerable financial commitments and massive scale software and system deployments. With analysts estimating data storage growth at 30 to 60 percent per year, organizations must develop a long-term strategy to address the challenge of managing projects that analyze exponentially growing data sets with predictable, linear costs. This blog post describes a lightweight risk reduction approach called Lightweight Evaluation and Architecture Prototyping (for Big Data) we developed with fellow researchers at the SEI. The approach is based on principles drawn from proven architecture and technology analysis and evaluation techniques to help the Department of Defense (DoD) and other enterprises develop and evolve systems to manage big data.