Big data refers to the collection, curation, storage, sharing, transfer, and visualization of large amounts of data for purposes of future analysis from traditional and digital sources. A mainstream definition of big data also contains the three V’s of big data volume, velocity, and variety and some industry experts include variability and complexity. From a high level, the data types can be classified as structured, unstructured, or multi-structured.
- Structured data is clear-cut and objective, such as transaction history.
- Unstructured data comes from information that is not easily interpreted or organized. Usually, this type of data is text-heavy. Social media posts are a great example of unstructured data.
- Multi-structured data can be taken from interactions between different people or interactions between people and machines. Web log data is an example of multi-structured data; it can include multiple forms of data, such as text, images, transaction information, and time data.
Big data constantly grows and will continue to have greater impact on business. Things such as cost reductions, determining causes of failures, detecting fraudulent behavior, calculating risk, reducing timelines, and all sorts of real-time customer-focused services will occur. Big data will continue to make businesses, markets, and governments much more efficient.