The Big Deal About Big Data

Make no mistake; Big Data is the business/technology/marketing buzzword of recent years. Ironic, because there’s so much debate about what that term means and even more discussion about what you can do with it.

Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis. (Forbes) 

It really doesn’t sound too complicated, does it? Put simply, Big Data is information your bank can use to inform strategy. The complexity arises in knowing how to identify useful data, knowing how to use and control the volume of information, and understanding risks and benefits. 

The explosive increase in data collection (50 times year over year) has created a new enterprise asset that, if used and managed in an effective and efficient manner, can lead to better decision-making. According to the Harvard Business Review, companies that invest in analytical searching (AKA, Big Data scanning) outperform the S&P 500 by more than 60%, on average. And yet, most companies only use 12% of the data they collect. 

The answer to why companies aren’t making full use of the data may lie in a prevailing sense of confusion about where the data is sourced, what forms it can take, and how to apply internal controls. 

Fundamentally, Big Data falls into two types – Unstructured Data and Structured Data. 

Unstructured Data may pose the greatest challenge for banks, as it refers to information that either does not have a predefined 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 computer programs as compared to data stored in fielded form in databases or annotated in documents. 

Structured Data, as its name implies, refers to information with a high degree of organization, such that inclusion in a relational database is seamless and readily searchable by simple, straightforward search engine algorithms or other search operations.

Obviously, structured data is the most useful in data analytics and decision-making by enabling companies to discover fraudulent activity, understand customer behaviors and identify unprofitable accounts. The problem is that at least 80 percent of data in today’s organizations is unstructured. 

To unlock Big Data's potential, banks must understand that how it sources and uses data is key to identifying holes in your information flow, and for creating strategies for improving customer engagement going forward. 

Are you asking the right questions to gather the information you need? Have you developed a strategy for how to utilize unstructured data? This is perhaps one of the greatest opportunities for banks striving to understand and better engage their customer base. Make sure you’re using all of your resources to the fullest potential.  

In our next post on the topic, we’ll look deeper into how to put Big Data to use. Subscribe now so you don’t miss out.