Synopses & Reviews
Today's databases can handle velocity, variety, and volume well beyond the traditional data warehouse, but the problems and architectures to handle them are not yet well-established. Drawing on years of experience in a wide variety of industries, Douglas Moore and Jeffrey Breen identify common big data patterns and guide users through solving tough problems that are well defined in the more traditional data warehouse space. This book is an essential resource as you plan for the entire data lifecycle, from data ingest, processing and enhancement, to publication, avoiding pitfalls and dead-ends and future-proofing your data storage and analysis.With an eye on the big picture of data analysis and the end goal of access and actionable intelligence, Moore and Breen cover all types of data—across the spectrum from batch to realtime, and the varieties of structured and unstructured data sources—in both general terms and the problems and potential pitfalls specific to each type.
About the Author
Douglas Moore has been at the forefront of big data for more than twenty years, engineering and architecting systems for energy, finance, and other data-intensive applications. Principal Consultant at Think Big, he delivers tech assessments, roadmaps, and applications utilizing a wide range of data tools.
Jeffrey Breen leads the Think Big Academy which provides training and education services for our clients, partners, and internal teams. Jeffrey has over 20 years of hands-on and leadership experience in IT, having served as the Chief Technology Officer of Yankee Group and the start-up Navient Corporation. Jeffrey is well known in the R community for his presentations and tutorials, and his method for mining Twitter for consumer sentiment is featured in Practical Text Mining and Statistical Analysis for Non?structured Text Data Applications from Elsevier. He holds an M.A. in Astronomy from the University of Virginia and a B.A. in Physics and Astronomy & Astrophysics from the University of Pennsylvania.