Uncovering The Big Data Iceberg

Out of the big data that gets assimilated in an organization, only the tip of the big data iceberg has been used.

Organizations gather a large volume of data to understand and analyze their customer’s needs and to improve their business. Data can be classified into three categories for any organization:

• Critical business data- data that are used for essential business operations,

• ROT (redundant obsolete and trivial) data- data which are not needed for any services, and

• Dark data- data that is below the surface.

Dark data can hold relevant information that can be moved to the critical dataset. However, according to the International Data Corporation, organizations currently analyze only 10% of the data they collect. 90% of the data, which is left neglected, is the dark data. Dark data includes spreadsheets, multiple old versions of documents, email attachments, .zip files, inactive databases, former employee files, log files, and so on.

Reasons Why Data Goes Dark

Organizations collect extensive data about their consumers to grow their business. There are numerous reasons why this data goes dark. Post-shopping, a customer is asked about her feedback on a particular brand. Sometimes there is a possibility that reviews provided by this customer are neglected. Structured data is stored in databases, whereas the remaining useless data is left without full utilization. Most of the time, organizations do not have access to unstructured datasets and these unstructured datasets may not have proper formats. All this lets the data turn dark and useless. Furthermore, specific sectors may lack data integration and analytics tools that can be used to analyze disorganized data, turning data dark.

There’s So Much More to the Big Data Iceberg

Approximately, ⅛ of an iceberg’s total mass is visible above water. ⅞ of its part stretches into the ocean and is hidden from our view. Similarly, data assimilated and generated in any organization is not entirely used. Companies use only the critical data for their business operations and functions and the rest is left useless. However, several reasons generated the need for organizations to look at what the big data iceberg all about; one of the primary reasons being the cost. Organizations spend a lot of revenue to collect data from different sources. However, only a part of big data is being used and exploited, resulting in increased cost with no outcome. The second issue is the storage space. Organizations waste a lot of their storage space to store data that is not being used. Furthermore, dark data can cause security issues as well. Data breaches such as the Sony Pictures hacking is driving the attention of organizations to use their dark data at the earliest. You may never know what kind of data is hidden in the dark data. It might contain data of no use or it might include sensitive data too. There is a risk that hackers might steal the sensitive data, leading to data breaches. Hence, these reasons generate the need for leveraging analytics to make full use of the collected data.

Dark data is an opportunity for industries with undiscovered potential, unknown insight, and unanalyzed value. Enhanced data-driven technologies must be used by sectors to manage dark data and gain actionable insights that will help them boost their business.