We’re sure you’ve heard about Big Data. Everyone’s calling it the next big thing, but what’s all the hype about it?
Big Data is generally understood as a large volume of information that makes decision making more efficient and accurate. Have you ever wondered how websites like Amazon and eBay can magically predict what you want to buy? No, it’s not magic. It’s Big Data.
In today’s economy, businesses face increasing pressure to stay competitive and to meet increasing consumer demands. Case in point—the iPhone series. Each iPhone model that Apple has launched has offered better specs than its predecessor. Similarly, each product that Samsung has launched has been designed to outperform its former version. The thing about Big Data is it immense potential to help businesses increase their competitive advantage.
These are some ways in which businesses use Big Data:
Sales & Marketing
Wouldn’t it be great if a product could sell itself? Big Data has the ability to gather information about what potential customers like. That information is then used to create a product that appeals to the customer—this is what is known as Customer Analytics
In customer analytics, companies use Big Data to track customer behaviour. Subsequently, that data is crunched to create personalised products and services according to consumer preferences. For example, Citibank makes use of machine learning algorithms and applies it to Big Data to acquire and retain clients.
1) Supply Chain Optimisation
One issue that many companies face in their supply chain operations is excess inventory. Typically, companies have to discard a product when its shelf life expires—a loss which companies have to incur. Hence, the more excess inventory you have, the greater the losses. With Big Data, these companies can better forecast demand and stock inventory in appropriate amounts, thereby reducing the chances of excess stock and ultimately cutting their losses.
2) Human Resource Optimisation
In human resource business processes, quantitative data such as cognitive and personality tests, can improve the quality of the hires.
Security and fraud is one of the most pressing issues that financial institutions face. Banks such as Citibank have implemented Big Data analytics in their security protocols to identify and predict potential frauds. The bank has invested in Feedzai, a machine learning company that focuses on real-time fraud prevention in eCommerce and banking. Feedzai’s machine-learning platform has the ability to scan large amounts of data and detect threats at a level and speed far beyond human capabilities, providing customers with real-time alerts to better guard against fraud.
Future of Big Data
International Data Corporation (IDC) predicts that worldwide market revenue will grow from US$130.1 billion in 2016 to US$203 billion 1 in 2020, at a compound annual growth rate of 11.7%. This presents great opportunities for the Big Data industry.