Data is the most valuable asset in today’s disruptive age. It can help organizations understand their customer needs, recruit the right talent, and define a strategy for the 21st century if leverage effectively. A company which offers comprehensive datasets on businesses, people, products, and properties to power enterprise applications and analytics is Datafiniti. Analytics Insight caught up with Andy Lovell, Chief Growth Officer at Datafiniti and spoke to him about how the right data can be turned to drive action, results, creating new products and solutions, and ultimately drive revenue.
Kindly brief us about Datafiniti, its specialization and the services that your company offers.
Datafiniti is a data aggregation company which sells data as a service. In addition to aggregating data, we also transform and clean, merge and create a consistent structure for the data.
Kindly brief us about your role at Datafiniti and your journey in this highly promising sector.
I am the Chief Growth Officer at Datafiniti, responsible for the sales, marketing and strategic development of the business side of Datafiniti. I came from the e-commerce sector where I highly leveraged as much data as I could as the Chief Growth Officer at Tennis-Point where we were approaching $100m euro in annual revenue.
What is your biggest USP that diﬀerentiates the company from competitors?
Our biggest USP is how accurately we merge and clean data, in order to give end-users, the data they want with rapid deployment. Our customers find long-term satisfaction with our extremely comprehensive & rich data database, which is quicker and easier to integrate than similar offerings.
Please brief us about the products and services you provide to your customers and how do they get value out of it.
Our product is data and that is split amongst 4 offerings including Products, Businesses, Real Estate, and People. Our use cases are widely varied and can range from lead generation, reputation management on products or brands, risk analysis on consumer insurance, fraud prevention, and countless other examples.
Tell us how your company is contributing in the AI/Big Data Analytics industry of the nation and how the company is benefiting the clients.
Our company contributes to the big data analytics, ML and AI fields by providing the data that empowers better business decisions, training for ML libraries, and the pipeline to further AI developments all while decreasing the costs, increasing the simplicity and improving the speed upon which companies start or expand on projects in these areas.
Kindly share your point of view on the current scenario of the big data analytics and its future.
Big data analytics has been a growing field for a while now, and with every new technology that comes out there, seems to be more potential for tracking and analytics.
At one point, not too long ago, it seemed like the market was in a rush to implement solutions to catch up with industry leaders that they were benchmarking against. Now that companies have had a chance to take a step backward, they’ve been able to improve their data analytic systems beyond what is just informative and have implemented systems that are actionable.
One big change that will continue to impact some companies is consumer privacy. We have already seen some changes happen with GDPR in Europe, while other countries will debate how to regulate which information can be captured and how it is stored.
What is the reason that organizations are using AI/ ML and big data analytics?
Organizations typically are using these technologies to capture ROI and/or to validate decisions. It’s important to note, however, that some of these systems can have inherent limitations. There can be problems with the quality of the data as well as the analysis. No business wants to interpret correlation as causation or to misunderstand what can scale. Businesses need to understand the data and systems they are using while also implementing sanity checks, where possible, to minimize any chance of poor outcomes.
How C-suite executives can leverage data to deliver business value to their organizations?
C-suite has a variety of ways they can leverage data to deliver value to their organizations. But if I were to recommend just one thing, particularly to an executive with too little extra bandwidth, it is for them to get the data into a project owner’s hands who is/has: the right skillset, ruthlessly critical, honest, always curious, and who has a good sense of business.
With how much value can be gained with great execution, it is best to entrust the system to a knowledge worker who can prevent automated results from being sub-optimal.
How can businesses efficiently extract the value from data, without increasing cost and complexity?
One major way businesses can efficiently extract the value from data, without increasing cost and complexity, is to have data that is usable from the beginning. Usable data with low overhead cost is the key. If you have that, you can better implement the data into your systems, applications, processes and decisions that much easier.
The time-to-market and percentage accuracy are key metrics you should be optimizing for if you want to be successful on any new, low-cost/low-complexity data project(s).