Exclusive Interview with Shubh Nandi, a Data scientist & First Generation Entrepreneur

Exclusive Interview with Shubh Nandi, a Data scientist & First Generation Entrepreneur
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Shubradeep Nandi, an IIM graduate, has many feathers to his technology hat. The fact that even before graduating from the prestigious business school he tried his hand at entrepreneurship by setting up an online food-tech business, reveals his visionary zeal. Moving further, in 2011, he cofounds CBC, a social payment marketplace, and sells it successfully to Zius in 2014. An ardent data scientist, and ambitious entrepreneur, Shubh Nandi talks to Analytics Insight in an exclusive interview, as to what his vision for finance technology is.

Kindly share your point of view on the current scenario of Big Data Analytics and its future.

The current scenario suggests a bright future for analytics & big data in India in rural India. Since 2019, there has been a 45% growth in active internet users. According to a Neilson report, rural India has 352 million internet users — almost 20 percent higher than urban.  The report further adds that almost 60 percent of the rural population is still not actively using the internet, paving headroom for further growth.

How is IoT/Big Data/AI/Robotics evolving today in the industry as a whole? What are the most important trends that you see emerging across the globe?

1. There are five Key trends with the data explosion:-

2. Smarter AI due to more data

3. Scalable ML Algorithms with state of art systems

4. Data Fabric – A powerful architectural framework and set of services that standardize data management practices

5. Augmented Analytics that uses the combined potential of NLP, CV, and other state of art ML systems

6. Death of Predefined Dashboard with the advent of modern, automated, and dynamic BI tools

How is Machine Learning (ML) shaping the IT/Big Data/Robotics industry today? How is it changing the role of CIOs and Leaders?

The role of the Chief Information Officer has expanded over the years. The disruptive potential of Machine Learning means the role should become even more strategic. CIOs at large enterprises must be prepared to play a more central role in their organizational decisions. The key to successful leadership in the digital age is to accept and embrace the changes and improvements that AI & Machine Learning technology brings to the IT/Bigdata/ Robotics Industry. Leaders are no more immune to AI/ML technology. As these technologies are integrated into the workplace, their role will be key to transforming into an analytical organization. Thus they have to be prepared and ready for the new reality.

The industry is seeing a rising importance of business and technology enablers like virtualization, convergence, and cloud. How do you see these emerging technologies impact your business sector?

One of the biggest trends for 2022 in the financial services industry is the more than ever increase in the use of hybrid cloud services and cloud computation. Public clouds are cost-effective but do have security concerns. On the other hand, the private cloud is secure but highly expensive. Therefore the most suitable and emerging option is the hybrid cloud. It is a balance of both a public cloud and a private cloud where cost and security are balanced to offer more agility. Hybrid clouds are bringing change to IT infrastructures by providing a flexible yet centralized database, data security, scalability of data, and much more at an affordable cost.

What is the reason that organizations are using IoT/analytics/big data/AI/ML/Big Data Analytics?
  • Better understanding of the customer needs
  • Prevention of customer churn
  • Optimisation of resources and cost
  • Discover new products and customer segments
  • Beter sales and growth opportunities
What are the concerns that organizations have before using Analytics?

1. The key concerns organizations have included

2. Right people with appropriate skill sets to work on analytics

3. Does the company have the right data to do analytics?

4. Has the data been collected with customer consent

5. Infrastructure to perform analytics

6. Assurance of data privacy and protection

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