There are two types of data available to most financial institutions (FIs) today: structured and unstructured.

Structured data is highly organized, readily searchable and generally generated by machine. It’s easily entered, stored and analyzed.

Unstructured data is essentially the opposite. Often generated through media, such as email messages, word-processing documents, audio files, voicemails, social media posts, photos and instant messages, unstructured data includes all data not contained in a database or other data structure.

Following the classic 80/20 principle, structured data generally represents 20 percent of the information available to an organization with 80 percent in unstructured form. Unlocking the potential of that valuable 80 percent is arguably the next big data challenge.

One solution may be big text. Also known as “text analytics” or “text mining,” big text is the science of giving structure to unstructured data. It works to extricate key pieces of information from conversations. By analyzing language and context, Big Text uncovers the who, where and when of a given conversation. It can also delve into vibe or tone of the conversation, revealing how people are feeling and why the conversation is happening.

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