Big data in the modern era is the main focus in the IT plans of all financial institutions. As the financial sector becomes increasingly competitive, the value contained within their data sets can determine their success or failure. Their data is increasing rapidly, coming from multiple sources and the traditional tools to analyze and manage this data are largely incapable to cope with the current growth. Big Data is marketed as the solution to address various banking, regulatory, compliance and financial challenges but the true power of technology lies in the value addition it brings to an organization.

The following steps will ensure you have a system in place that leverages big data. We take a quick look at the 5th V of Big Data: Value.

 

The classic Vs of Big Data

Big Data characteristics are popularly defined by data scientists using the four V’s; volume, velocity, variety and veracity. Using the characteristics of these is the more important decision making process that lends businesses the ability to recognize and improve the value of its existing data.

Let us take a look at the four traditional Vs of Big Data and how Value plays an important role in harnessing the power of the other parameters.

The 5 V’s of Big Data
Variety Volume Velocity Veracity Value
Structured, Semi-structured or Unstructured data Quantity of information created Speed at which data is delivered and used Uncertain or vague data Making sense of available data
Challenge
Understanding and utilizing heterogeneous Big Data in different formats
Challenge
Analyzing large volume of data
Challenge
Real time intelligence and on time reporting
Challenge
Data Aggregation and Lineage
Challenge
Lack of a clear understanding of Big Data and no proper strategy to leverage it

 

Volume

Data storage-8

Image: www.arnnet.com.au

The first parameter used to define Big Data is the most obvious, for it is one of the prime reasons Big Data is named the way it is. Organizations today are working with and producing huge amounts of data, which the traditional legacy systems are incapable of handling. However, since the advent of Big Data, organizations have the ability to store as much data as possible in a cost-effective manner. They have the capability to perform a broader analysis across various data streams and gain deeper insights. This is largely being done using the help of distributed systems, where parts of data is stored in different locations, connected by networks and brought together by software. Hence, mass storage of data is not the only value addition Big Data brings; data security is an extremely important aspect too.

Variety

The second parameter that defines Big Data is variety or the various types of data sources from which data comes in. In today’s age, the ability to acquire and analyze varied data is extremely valuable. 80% of the world’s data today is unstructured and therefore cannot be utilized properly. Big Data technology can harness different data types and bring them together in a more structured form. Combining and making sense of the data from disparate sources is one of the key features of Big Data which is important especially for enterprises in the banking and financial sector, where data influx from disparate sources is high.

Velocity

du-stacks-to-moon

Source: http://www.emc.com/leadership/digital-universe/2014iview/executive-summary.htm

The third parameter defines the speed at which new data is generated and the rate at which it moves around. Every day, we create 2.5 quintillion bytes of data i.e. 90% of the data in the world today was created in the last two years alone. But velocity not only refers to the speed at which data is generated, it also takes into account the speed at which it is analyzed and worked on. For time sensitive processes such as fraud detection for example, the time required to identify potential fraud and report them is crucial. Big Data technology allows us to analyze the data while it is being generated without the need to put it into a database, saving crucial time for organizations.

Veracity

The fourth parameter, coined by IBM, defines the accuracy and inherent trustworthiness of data. Uncertainty about the consistency of data and other ambiguities can be a major obstacle for organizations. As a result, it is essential to add data quality, data cleansing, master data management and data governance as a critical aspect of Big Data. Big Data and Analytics technology provides various options to check for the correctness of the data and also to find anomalies quickly and effectively.

Value

Mirrorimage

© Laura Williams

 

The final parameter defines an organizations’ ability to turn data into value. Despite the huge volumes of fast-moving data of various variety and veracity, it is important to have a strategy in place that can utilize and properly leverage available data to deliver value to businesses.

Big Data is the new necessity for banks both large and small. Regulatory requirements such as Dodd-Frank are leaving banks and financial institutions in a lurch, putting them under stress to meet the growing compliance definitions and the changing regulatory scenario. The various analysis and data management tools go a long way in helping institutions cope up with added pressures.

However, in order to do so, having a focused strategy that is based on the requirements of the particular organization is important. The applications of big data are endless and every part of business will change as we now have much more data and a better understanding and ability to analyze it.

 

How Hexanika adds Value to your organization?

Hexanika is a RegTech big data software company which has developed a software platform SmartJoin and a software product SmartReg for financial institutions to address data sourcing and reporting challenges for regulatory compliance.

Value

Big Data is new and agile, but cannot be properly exploited without the right strategy. There is no ‘one size fits all’ solution available. The Big Data landscape is changing rapidly and it is critical to adopt the right strategy to suit your business needs.

Selection of the right Big Data strategy will enhance productivity, reduce costs and lower risk. This will also help businesses to extract insights and business intelligence which will help in exploiting large, varied, fast-moving data to improve business performance. In other words, Hexanika adds value to your organization by helping you choose the right Big Data strategy and deploy it to suit your requirement. Read more about our services at: https://hexanika.com/big-data-services/

Image Credits: Laura Williams

Reference Links:

http://www.wired.com/insights/2013/05/the-missing-vs-in-big-data-viability-and-value/

http://www.information-age.com/it-management/strategy-and-innovation/123460041/how-measure-value-big-data

http://www.ibmbigdatahub.com/blog/why-only-one-5-vs-big-data-really-matters

https://www-01.ibm.com/software/in/data/bigdata/

 

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