Big Data Means Big Biz Opportunities For SMEs Too
Big Data has made its mark in the enterprise, but SMEs are still sceptical about its adoption. Satish Gidugu, CTO, RedBus.in, explains how Big Data is not restricted to the large enterprises alone.
There is no doubt that Big Data has made its mark in the enterprise community. But is it worth the time and money for SMEs or e-commerce businesses to look into Big Data from the business perspective? Satish Gidugu, CTO, RedBus.in, in conversation with Biztech2.com, shares some key insights about Big Data and how SMEs or e-commerce businesses can extract the most out of it.
What challenges do e-commerce businesses face?
Back in 2006 when the company started, it was primarily meant for those traditional brick-and-mortar agents but eventually the website evolved into an e-commerce venture. There are some challenges which are common for any e-commerce venture, for example, payment gateway errors, tracking transactions that are Cash on Delivery (COD), logistics issue in the market, etc.
One of the unique challenges that we face would be managing the entire database of buses and operators. With data growing enormously every passing day, storing all of it and retrieving it at an appropriate time is very difficult. Another challenge we face is maintaining portal with almost zero downtime within budgetary constrains.
Contrary to popular belief that e-commerce businesses do not require that much capital, an e-commerce venture depends solely on technology infrastructure which is seldom cost effective.
Talking about the enormous burst of data, do you think that SMEs, including a large chunk of e-commerce businesses, should also be drawn towards the Big Data buzz?
I think most of the small and medium businesses have reached a stage where the cost of storage and maintenance can only be recovered if they know how to handle Big Data. It is important for SMEs, especially e-commerce businesses, to understand that Big Data is not restricted to large enterprises only.
SMEs also tend to believe that Big Data is only for verticals such as telecom or BFSI but the key is to understand how you can make use of Big Data within your small environment. The right way to approach Big Data for all is with analytics. The moment you choose to analyse the data you have and get information out of it, you will realise that Big Data presents an opportunity for every organisation.
Still many believe that Big Data is all about Volume and Velocity so it’s not for my organisation. What’s your take on this?
In India, Big Data and its awareness is still at a very nascent stage. In fact, many technologically mature organisations also feel that the decision-making can still be done by traditional data warehousing methods - which in some cases that might prove to be more cost effective and viable. But looking into the future era of smartphones, tablets, etc., Big Data is definitely going to play a major role irrespective of the organisation size.
Today almost every organisation has a social presence. Now, many people use social media to comment about products they use or in our case about their journey experience. It is part of the new go-to-market strategy to measure this Big Data in real-time to get insights into audience sentiments.
So, Big Data is not only about Volume or Velocity, it is also about how you are able to understand and use the information you have.
What are the key considerations one should have before going for Big Data solutions?
I believe the best way to look into Big Data is answering the right questions. Do I really need social media data to learn about customer emotion? Will Big Data help me align my business goals with IT? The best way is not to go just for the sake of the hype created around Big Data. For instance, there might be some software for Big Data, which is a great technology and is getting a lot of attention, but it is not necessary that it will be a realistic solution for SMEs and midsize companies. At the end, I think the most important thing is to determine what to do with your organisational data.