This work focuses on leveraging large data sets. It would be a useful resource for those studying or researching machine learning, artificial intelligence, algorithms, information systems, and statistics, as well as those within the disciplines of business and medicine. With the availability of inexpensive computer hardware, people can now use and store real-time data sets that were previously disposed of after a single use. Mayer-Schonberger (Oxford Univ., UK) and Cukier (data editor, The Economist) illustrate this through a series of case studies of repurposing data sets for new applications. The authors also outline the social shift in thought from the need to understand why something occurs to accepting that one will not know why it occurs, because the data sets used are too large and time-sensitive. Society is becoming dependent on decisions based on correlation and must accept that there will be outliers in the process. Many books on artificial intelligence focus on the algorithms that drive data sets. Big Data takes a somewhat unique approach in that it focuses on showing how existing and accessible data sets drive algorithm development. Finally, the book outlines the implications of big data for society and personal privacy. Summing Up: Recommended. Upper-division undergraduates through professionals; general readers.
Microsoft Access allowed many business users to create databases of information in a manner that mimics the use of spreadsheets. Unfortunately, the benefits of a well-designed database mostly evaded these users, and the burden of maintaining the data often became more costly than the benefits of having the data available within a database. As writer/instructor Oppel (Univ. of California) illustrates, a database is something that needs to be designed for ease of data management. When properly normalized, information is consistent and nonrepetitive, and the data can be maintained in one place. This book is a must read for anyone who wants to migrate from spreadsheets to databases. It covers all the important concepts necessary to create a well-designed set of database tables, applying principles of normalization. It covers queries, form-based access to data, transactions, and security. The volume is loaded with figures, diagrams, and screenshots that help to clarify the discussion, including examples from Access's Northwind sample database. Oppel addresses how databases are used for business analytics and describes the concepts of data warehouses/data marts to give readers a preview of more advanced data management strategies and the organizational principles that are applied in those domains. Summing Up: Highly recommended. Two-year technical program students, researchers/faculty, professionals, and general readers.