Big Data Is The Backbone For The Analytics Market

1. How is the Big Data evolving in 2018, the maturity of the market and the potential?

With the advent of internet, we have been producing enormous data daily. The data was termed ‘big data’ because it was so vast that traditional softwares were unable to efficiently process it. However, with time and technology improvement, data is now within the reach of not just the big corporates but also to the small and medium scale organisations. People have realised the potential of data and hence huge money is being invested on building teams and solutions that can analyse the data and provide insights to drive sales and business growth. All facets of business be it marketing, sales, customer experience, etc are being driven by data these days. With the growth of data and AI driven solutions, big data offers enormous opportunities in all industries.

2. Standing in 2018, has big data overcome the allegations of privacy and unregulated data mining?

With an increasing penetration of internet into every nook and corner of the world, we are generating enormous digital footprints. Availability of extensive data coupled with advancement in the field of parallel computing, storage and data analytics solutions has paved way for a plethora of opportunities in the field of e-commerce, social media, consumer analytics etc.

However, big data solutions and analytics come with its own set of risks and problems. It comes with a huge concern of data privacy and security. Moreover, with the advent of cloud platforms and technologies, data transcends the boundaries of physical networks of the companies and is advertently/inadvertently shared with multiple parties involved in the overall transaction. Owing to the lack of transparency, traceability and stringent regulations and controls around data privacy and sharing, consumers are exposed to the perils of unauthorized access to data which are utilized in various ways to drive business. Until the issues related to data security is dealt with preventive measures, it will in general continue to restrict utilization of big data to its full potential. Hence there is a need of widespread awareness as well as regulations which drive policies that protects the privacy and interests of the consumers.

3. How can one secure its Big Data off or on-premise?

There is a general belief that data is more secure on premise than on cloud. Larger companies are still wary of data transcending the boundaries of their physical networks and being hosted on the cloud. Machines on the cloud are seen as shared resources and hence vulnerable to attacks and unauthorized use. However, the need of the hour is to make the data platforms more democratic in nature and to embrace cloud technologies and solutions. Managed services like AWS and Azure leverages identity and access management(IAM) to provide fine grained access controls to servers and resources. Moreover, it greatly cuts down on operational and infrastructure costs and makes server maintenance trivial and easier. Hence, it is important that we embrace cloud technologies and deploy security measures like VPC, security groups, access control rules, UFW, etc to make the security more robust.

4. How majorly has Big Data Market impacted the Analytics Market?

Big Data is the backbone for the analytics market. In recet times, there has been surge of players providing analytics solutions based on structured and unstructured big data and processing them to provide meaningful analytics. Use case of analytics ranges from fraud and risk analytics, user behaviour, operational efficiency, and marketing strategies.

5. Which sectors in India are early adopters and which markets and geographies is the market set to mature evidently?

Big data has been adopted by different industries in different propositions. The e-commerce and advertising industry especially the digital ad networks have been the main adopters of big data where they have deployed AI based solutions to customize the listings for each customer. This has helped them see exemplary growth and results. Big investment firms have always deployed data analysis for industry research and trend analysis. However, now traditional setups like banking and insurance industries are also catching up on the importance of big data. This is where fintech startups like us play a major role by deploying technology solutions that helps these traditional setups to leverage big data technologies.

6. How critical is the recent data leak by Cambridge Analytica and how the novice repo of Big Data will not be hampered by this recent turmoil?

The recent data leak has indeed shaken the trust of the people. In developing countries like India, there is a general lack of sense of security in dealing with any sensitive piece of information online and events of data leaks like these will only further lead to lack of trust. In an interview Sheryl Sandberg, the second in line in Facebook after Mark Zuckerberg, said, that if you want to do away data driven advertising, then you have to pay for the product. This highlights a deeper problem since data can’t be done away with especially as a lot of companies survive on advertisement revenue which is impacted by data. This emphasis the need of regulations and policies which need to be in place to promote ethical usage of data.

7. What impact will SMAC (social, mobile, analytics and cloud) put to Big Data?

SMAC is the building block of big data. The interactions we do on social media through our mobile devices are the greatest source of digital data that are being generated daily. This data can then be processed using distributed cloud technologies like Spark, HDFS, Kinesis etc to ensure data availability and readiness for analysis. The processed data is then analysed to provide meaningful insights to the business.

8. Lastly, how your company is determining or say inking the future of Big Data in terms of technology, market adaption and revenue.

Rubique leverages big data and AI solutions to build Rubique Magic Score. Rubique magic score is a confidence score assigned to each customer which gauges the credit worthiness of the customer. It enables access to data for new to banking and new to credit customers through host of alternate data like call logs, social interactions, SMS data, mobile device data, GPS data, bank data and salary data. Rubique also deploys big data to evaluate the risk and fraud cases and take proactive actions. Rubique uses host of cloud solutions and analytics solutions to analyse the customer data and derive meaningful insights.