It is the era where almost every aspect of our daily lives is digitised. There are numerous sources to gather, collect and analyse data. It has become such a gargantuan term that academicians, influencers and other prominent stakeholders vouch for Big Data as it has completely revolutionised the way organisations and businesses work.

Before we move ahead, let us understand what Big Data is?

Big Data is large and complex unprocessed data. Such data are time-consuming and difficult to process using traditional processing methods. It can be characterised using the following categories:

    • Volume
    • Variety
    • Velocity
    • Variability
    • Veracity
  • Complexity

There are a lot of sectors that are being benefited through Big Data applications.

Following are the major fields where big data application is being used:


Unlike the banking sector, Big Data has always proved to be very useful in the government sector. It had played an essential role in not just the re-election campaign of Barack Obama but also the BJP and its allies to win Indian General Election 2014. Various techniques were used by the Indian Government to find out how the Indian electorate is responding to the actions taken and ideas for policy growth introduced by the government.

Fraud Detection

One of the most compelling examples of Big Data application is in Fraud Detection, especially in the businesses which involve any claims or transaction processing. In most of the cases, fraud is discovered long after it’s done, which means the damage is already done. Analysing requests and transactions in real time, detecting anomalous behaviour or identifying large-scale patterns across transactions through Big Data applications can definitely prove to be a game changer in Fraud Detection.


Sensor data to optimise crop efficiency is used by a biotechnological firm. This is used to measure how plants react to changes in various conditions by planting test crops and running simulations. Its data environment continually collects and records the changes in attributes like temperature, soil composition, water level, growth, gene sequencing and output of each plant on the test bed. Such data helps in discovering the optimal environmental condition for the specific gene types.


Very recently, I stumbled upon a study conducted in the Harvard Business Review. This study on the basis of various factor published the kinds of advertisements that compels viewers to continue watching ads and the ones that dampens their interest levels. To perform the research, one of the tools used was “a system to analyse facial expressions revealing viewers’ feelings”. Similarly, other markets are also using facial recognition software to know how well their advertising have succeeded or failed at generating interest in their product/service.


Usually, the health industry had lagged when it came to the use of Big Data. One of the most critical reasons behind it is the resistance to change providers being accustomed to making treatment decision autonomously, using their clinical judgement, instead of depending on protocols based on Big Data.

Other reasons being the unequal distribution of relevant information is that the organisations like single hospital (not a multi speciality hospital) or pharmaceutical companies lack a procedure for incorporating data and communicating findings. These organisations are now turning to Big Data application to analyse the data to obtain insights and extract more action-oriented results. The recent technological advances have helped them in improving their ability to work with such data.

The Caution Point

While Big Data analytics have been a boon for organization, the threats surrounding Big Data applications cannot be overlooked. Privacy has become a big concern when it comes to the use of customer data, especially in BFSI industry. Big Data analytics have the potential to reveal sensitive personal information by uncovering hidden connections between pieces of data that seems unrelated. As per the research, approximately 62% of the bankers avoid using Big Data applications because of privacy issues.

Outsourcing of data analysis only increases the security risks as information like customers’ earnings, mortgages, savings and insurance policies are required to be shared for the purpose. There is always a concern about these data ending up in the wrong hands, and that is what discourages customers from sharing their personal information in return for customised offers.

The Bottom Line

To summarise it all, if optimize in the right direction, Big Data is indeed a powerful tool that makes things easier in various fields. Apart from the above mentioned sectors, Big Data application is also making a positive contribution in chemistry, data mining, cloud computing, finance and more. Its application is so huge that the article could only be considered as an overview about the Big Data applications and its advantages.