Per Wikipedia, Unstructured data (or unstructured information) refers to information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well.
This results in irregularities and ambiguities that make it difficult to understand using traditional programs as compared to data stored in fielded form in databases or annotated (semantically tagged) in documents.
As a result the traditional model of business analytics no longer works.
Recent discussions about Big Data are showing that about 80-90% of data currently being captured by businesses is unstructured. Just two year ago it was 50% and five years ago about 20%. The boom is unstructured data storage is fundamentally changing business analytics as we know it.
Businesses across all industries are gathering and storing more and more data on a daily basis. But when it comes to assessing the benefits and challenges of big data, sometimes it is easy to overlook one key point: Most of the business information in use today does not reside in a standard relational database.
So how do we overcome these challenges?
DMAI has the answer!