Zscore Technologies is a data management company with the core focus on data quality. Though their primary focus is on the Insurance sector, they plan to expand to other sectors as well. Its customers include Vidaal Health India and Vidaal Health Middle East. An organization has 30-40% of bad data which in turn decreases the revenue of a firm by 10-12%. ZScore solution helps an organization to make right decisions and implement right solutions.
Rohit Kalro is the Chief Revenue Officer at Zscore Technologies Pvt. Ltd. Rohit’s journey over the last couple of decades has led him to go through various roles and experiences in design, development, managing and building teams, setting up products and businesses and being an entrepreneur.
In an interaction with IncubateIND, Rohit Kalro talks about the future of data management in India. Read On!
Tell us something about yourself and what does Zscore Technologies do?
Zscore looks at tackling the problem of low data quality within an organization. We have experienced that almost 30-40% of data contained in an organization is flawed. This has a direct impact on the bottom-line of companies and in some cases can result in a loss of 10-12% of potential revenue. We seek to tackle this problem using modern technologies like ML which allow us to do this at scale. Having accurate data means better insights and predictions thus enabling management to make better decisions. We are currently part of the 3rd Cohort of the NetApp Excellerator due to graduate in January 2019. NetApp’s knowledge and experience in the data storage and management market globally has been invaluable to us over the last few months in shaping how we approach our technological and go – to – market challenges.
What does the future hold for data management in India?
India is one of the biggest markets in the world given the sheer size of the population and consumer buying potential. With the progress in digitization of all aspects of our lives, this means that the level of data generated by people consuming products and services has gone up drastically. Future businesses that thrive will be ones that can leverage data to provide more value to their customers. Companies will need more sophisticated data management practices to manage their data, secure an advantage over their competition and ensure a higher degree of customer satisfaction.
How will Artificial Intelligence transform data management?
With the volume of data and sources expected to grow exponential over the coming years (50X growth in data from 2010 to 2020, 1ZB to 50ZB). Given that newer channels of acquisition of data like mobile and IoT are generating data in real time, managing such large volumes of data is humanly not possible. That’s where technologies like AI and ML come in to lend a helping hand to businesses.
Why data governance is vital for AI & ML?
Current statistics reveal that almost 85% of AI and ML projects fail to make it into production. One of the contributing factors for this is the incomplete understanding and low quality of data in current organizations. To truly succeed in this new world of automation, organizations will need to ensure that the business has data of good quality and supported by a sustainable practice. Once an organization has a strong foundation in data, only then can it achieve a higher success rate and accuracy in its AI and ML initiatives.
How the growth of IoT is changing data management?
One of the eye openers for us in interacting with clients was that data generated by IoT devices are not 100% accurate. IoT devices can have much variance in their reading for reasons like human error, atmospheric conditions & vandalism to name a few. IoT devices generate vast volumes of data in real time at a very high frequency. This speed is something which businesses will need to support for future growth and competitive advantage. Data management solutions and processes will need to take into account that companies will be deploying IoT devices for various use cases.
Can businesses use blockchain to solve the problem of data management?
The applicability of blockchain as a technology toward data management is still on open question. Blockchain serves the purpose of validating trust in the absence of a third party. Also, blockchain operates at much slower transaction speeds than required to deal with massive data volumes. We might see blockchain applied in conjunction with data management in use cases where we need to validate the authenticity and trust of data sources when being shared within an open ecosystem. There is no saying how blockchain might evolve in the future to support use cases in data management. As of now, the jury is still out on that front.