Big Data

DEFINITION of 'Big Data'

The growth in the volume of structured and unstructured data, the speed at which it is created and collected, and the scope of how many data points are covered. Big data often comes from multiple sources, and arrives in multiple formats.

BREAKING DOWN 'Big Data'

The increase in the amount of data available presents both opportunities and problems. In general, having more data on one’s customers (and potential customers) should allow companies to better tailor their products and marketing efforts in order to create the highest level of satisfaction and repeat business. Companies that are able to collect large amount of data are provided with the opportunity to conduct deeper and richer analysis.

While better analysis is a positive, big data can also create overload and noise. Companies have to be able to handle larger volumes of data; all the while determining which data represents signals compared to noise. Determining what makes the data relevant becomes a key factor. Structured data, consisting of numeric values, can be easily stored and sorted. Unstructured data, such as emails, videos, and text documents, may require more sophisticated techniques to be applied before it becomes useful.

Big data is most often stored in computer databases, and is analyzed using software specifically designed to handle large, complex data sets. Many Software-as-a-Service (SaaS) companies specialize in managing this type of complex data. Data analysts look at the relationship between different types of data, such as demographic data and purchase history, to determine whether correlation exists.

Nearly every department in a company can utilize findings from data analysis: from human resources and technology, to marketing and sales. The goal of big data is thus to increase the speed at which products get to market, reduce the amount of time and resources required to gain market adoption, and to ensure that customers remain satisfied.