This document discusses big data and provides an agenda for a presentation. It defines big data, outlines its key characteristics of volume, velocity and variety. A brief history of big data is given starting from individual data generation on social networks and sensors to Google's distributed file systems. Common use cases are listed across various industries. Traditional systems are noted as unable to handle unstructured data at big data scales, while new architectures using distributed processing and NoSQL databases are needed. Research projections include a shortage of data analytics skills and rapidly growing data volumes. Action plans propose distributed file systems, parallel processing and machine learning to extract value from large, diverse datasets.