Big data is a buzzword, or catch-phrase, used to describe a massive volume of both structured and unstructured data that is so large that it's difficult to process using traditional database and software techniques. In most enterprise scenarios the data is too big or it moves too fast or it exceeds current processing capacity.
In other words, when we have data of high volume, at high velocity, and with high variety, we have the potential for big problems.
Because big data is a buzzword, we have chosen to represent it in descriptive terms in the notes for 005.7 Data in computer systems: "Class here high-volume data sets." (We have also mapped the LCSH Big data there.) The import of this note is that big data approximates the whole of 005.7. Since class-here notes have hierarchical force, big data can also be found throughout the subdivisions of 005.7. Thus, Large scale and big data: processing and management, a comprehensive work on big data, is classed in 005.7, while Data warehousing in the age of big data is classed in 005.745 Data warehousing.
This doesn't mean that all works on big data are classed in 005.7 and its subdivisions. (Things are rarely that simple, are they?) At the centered entry for 004–006, we find the following preference note: "Unless other instructions are given, class a subject with aspects in two or more subdivisions of 004–006 in the number coming last." This means that a work treating two or more aspects of computer science, for example, big data (at 005.7) and data mining (at 006.312 Data mining), is classed in the later number, in this case, in 006.312. Such is the number assigned to Data mining and knowledge discovery for big data: methodologies, challenge and opportunities.
If big data were to come with the potential just for big problems, we would find ways to decrease the volume, velocity, or variety of the data we work with. But big data also has the potential for big value: "Big data is high volume, high velocity, and/or high variety information assets that . . . enable enhanced decision making, insight discovery and process optimization." We see this, for example, in Actionable intelligence: a guide to delivering business results with big data fast!, to which the Library of Congress subject headings, Decision making, Strategic planning, and Big data have been assigned. By the rule of application, such a work is classed in management and not in computer science. Specifically, this work has been classed in 658.4038028557 (built with 658.4038 Information management ["Class here gathering of information by management for use in managerial decision making; information resources, knowledge management"], plus notation T1—0285 Computer applications, plus notation 57 from 005.7 Data in computer systems).