Introduction

Big Data is neither a technology nor a tool. The term Big Data is composed of two words, ‘BIG’ which means a large quantity and ‘DATA’ which refers to a set of values i.e., BIG DATA is terminology that describes a large volume of data.

Characteristics

Big data characteristics can be described by the following 5 Vs:
Volume: It refers to the quantity or the size of data generated. The size of the data determines the value and potential insight- and whether it can actually be considered big data or not.
Variety: Variety, as the name shows, it means the type and nature of the data. This helps people who analyze it to effectively to use the resulting insight.
Velocity: In this context, it is the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development.
Variability: Inconsistency of the data set can hamper processes to handle and manage it.
Veracity: The quality of captured data can vary greatly, affecting accurate analysis.

Importance

“The value of your data is in what you do with it.”
We produce a lot of data daily from various channels like emails or social media like Facebook, Instagram, Twitter and so on. The importance of big data is not only limited to know how much data we have, but also what we can do with it. We can take data from any source that can be analyzed and used to find the answers that enable cost reduction, time reduction, new product development and optimized offerings, and smart decision making.

The Banking and Financial Services (BFS) industry has been one of the biggest adopters of Big Data technologies. It can be used for:

1. Security
   The security of the system can be enhanced by using effective analytics and Big Data technology to gain a general view of customers and distinguish fraudulent activity from normal activity.
2. Customer Segmentation
   All the customers can be grouped into different segments such as sales, promotion, marketing, etc. by collecting and analysing all the available and stored data.
3. Personalized Product Offering
   The available data can be analyzed properly by implementing software which supports flexible and integrated processes and can be used to understand customer buying habits, the key influencers, etc. This will help the company to target new product and service offerings to the right customers.
4. Risk Management
   Support new regulations and increasing demand for better internal management support by implementing a central, integrated finance, and risk management data platform that can quickly and flexibly address new requirements.