3. Velocity: the speed at which the data is generated 4. Veracity: the trustworthiness of the data 5. Volume: the size of the data

Studying data helps us to answer science-related questions, better understand diseases and treat them, and learn more about a vast variety of things in the world. The study of big data also allows companies to better understand and serve their customers, reduce risks, better maintain their equipment and machinery, and improve the efficiency of workers and production processes—and make a lot of money in the process. The management consulting firm Bain & Company reports that “early adopters of big data analytics have gained a significant lead over the rest of the corporate world . . . those with the most advanced analytics capabilities are outperforming competitors by wide margins.” Big data is used by businesses, nonprofit organizations, and government agencies. The market research firm IDC reports that the banking, manufacturing, professional services, and federal government are currently making the largest investments in big data and business analytics solutions. Big data has many subfields, but the two main areas in this discipline are data analytics and data science. People disagree about the definitions of these terms, but for the purposes of this book, data analytics is the collection, organization, and study of data to solve problems, make strategic decisions, and meet other goals. Data science is the design and creation of new types of data analytics processes by using algorithms, predictive models (the use of statistics to predict the outcome of a process or event), and other methods.



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