Big Data


   We are living in very exciting times. The outcome of people’s increasing reliance on digital business models is generating great money throughout the world. Artificial Intelligence (AI), Internet of Things (IoT), drones, and big data provide a glimpse of what the future may look like.

The use of big data has accelerated by the corona virus pandemic. It has led people to turn to the internet for many of their daily needs. Big data is the extremely large collection of data that is analysed to understand patterns, trends and association especially relating to human behavior. This data is so large that conventional methods of storing and processing data do not work.

Big data is characterized by the following 3 V’s:

Volume: Advancement in technology has resulted in an increase in the sources of information available. The scale at which information can now be generated has also multiplied manifold. For best use of the data, proper analytical tools and technologies are required.

Variety: This refers to the numerous sources types of data i.e structured, unstructured and semi-structured data. The challenge is to bring all the sources and types of data together to reveal valuable insights.

Velocity: This is the rate at which the data is produced. For eg: More than 1740 million messages are sent via whatsapp each second.

Use and application of big data is not restricted to any sector rather is used in all i.e. agriculture, manufacturing and service. Primary sector uses big data in the following ways: Big data provides farmers precise data on climate, water, farm equipment, fertilizer requirements, weeds, nutrients, soil acidity, sustainability and more.

Manufacturing sector makes use of big data to gain competitive edge in the dynamic environment. This involves gathering data to for capturing new markets, predicting demand, improving quality, customer retention, value engineering. Data is captured from customer loyalty cards, store inventory, data from shopping patterns.

Big data is also widely used in communications, media and entertainment industry. It enables service providers to collect, analyze and utilize consumer insights, mobile and social media content, understanding patterns in real-time, media content usage, create content for different target audience, recommend content on demand, measure content performance.

One very great example would be of Meru cabs and Ola. Meru was well funded and had a head start of 4 years. Ola started in 2010 but was able to capture market way quicker than Meru. The process of booking a cab in Meru was quite complicated, Ola made use of big data and adopted advanced technology and didn’t involve much manpower. Ola understood the need to connect customer directly to the driver and capitalized on this. The current position is such that 56% people prefer Ola and only a 2% prefer Meru( the other 41% prefer Uber) which is a vast diference.

This was an example of a company that made the best possible use of big data however there have been big corporate failures which seemed like they could be the next big disruptive tech but turned out otherwise. Therefore, it must be kept in mind that the information must be of value to the organisation and that it must be put to use properly.

Some major drawbacks of big data are:

Veracity: This is also one of the main features of big data. It refers to the accuracy of data. Inaccurate data leads to misleading decision which can have a very bad impact.

Cost: The hardware, software systems costs are difficult to establish. Also though these are decreasing over time, data is increasing hence the need for more storage.

Regulation- Some countries such as the UK have very strict laws regarding Data Protection. Customers wouldn’t like if there data was sold to third parties or misused.

Making cost vs benefit analysis before adopting any such ideas will be of great help.

Author: Shagufta Khithani

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