Differences between Big Data and Small Data

Excerpt Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information,by Jules J Berman (see yesterday's blog).Big Data is very different from small data.  Here are some of the  important features that distinguish one from the other.1. Goalssmall data-Usually designed to answer a specific question or serve a particular goal. Big Data-Usually designed with a goal in mind, but the goal is flexible and the questions posed are protean. 2. Locationsmall data-Typically, small data is contained within one institution, often on one computer, sometimes in one file. Big Data-Typically spread throughout electronic space, typically parceled onto multiple Internet servers, located anywhere on earth. 3. Data structure and contentsmall data-Ordinarily contains highly structured data. The data domain is restricted to a single discipline or subdiscipline. The data often comes in the form of uniform records in an ordered spreadsheet. Big Data-Must be capable of absorbing unstructured data (e.g., such as free-text documents, images, motion pictures, sound recordings, physical objects). The subject matter of the resource may cross multiple disciplines, and the individual data objects in the resource may link to data contained in other, seemingly unrelated, Big Data resources. 4. Data preparationsmall data-In many cases, the data user prepares her own data, for her own purposes. Big Data-The data comes from many diverse sources, an...
Source: Specified Life - Category: Pathologists Source Type: blogs