Data context is the network of connections among data points. Those connections may be created as metadata or simply identified and correlated. Contextual metadata adds value, essentially making it possible to receive information from data.
A single data point on its own is useless. Take the number 42. It may suggest possible contexts -- it could be a cool weather temperature in the Fahrenheit scale, for example, or it could be Bill Clinton, the forty-second president of the United States. If the context is pop culture, it's likely to refer to the meaning of life: In Douglas Adams' The Hitchhiker's Guide to the Galaxy, 42 is the number from which all meaning ("the meaning of life, the universe, and everything") could be derived.
Without context, the number 42 cannot yield information and will not help any individual or organization achieve their goals and objectives. The addition of context is particularly crucial for realizing value from big data, which by nature of its volume must be automatically processed.
In business analytics (BA), gathering context from external sources can provide useful information about events that have significance for the organization. Context for an unexplained surge in sales, for example, could be provided by pulling in data from news and social media as well as less obvious sources, such as weather over that period. Explored in context, it may be able to identify external causes for the increase, and that information might be used to guide future business decisions.