Finding Value in Big Data

Big Data comes in various forms and is sometimes referred to as nonrelational data, semi-structured, or unstructured data, but more frequently it can also include large structured data warehouses. Big Data, as the name suggests, is a source of large volumes of data, such as Web logs, streaming media posts, stock market trades, and machine sensor data. Data can have a variety of content types and is often captured and processed at high speed.

Such data potentially holds value for organizations because it could be used to discover important trends and provide insights to solve business problems. For example, data clustering can find natural segments (such as customers with similar buying behavior) and predictive models can forecast trends (for example, in equipment failure) using seemingly unrelated information.

Depending on the organization, benefits might come from the following business scenarios:

Understanding consumer attitudes is found in data of consumer sentiment from examining social media posts. Consumer comments about an organization’s products could provide insights for an organization to use in making decisions about product marketing and pricing.