In a conversation Mr. Shion Deysarkar, Founder & CEO, Datafiniti divulged Fusion Analytics World how Datafiniti is planning to change the online web data game by introducing more machine learning approaches and automating data extraction process. To add diversity to his team, he is currently hiring Growth Marketer and Data Visualization professionals for Texas HQ.

Introduction: Yourself. What is Datafiniti and how did it all start.

• Our competitors can be broken down into two categories: Web Scrapers and Competing Data Feeds.
• Web Scrapers: We see web scrapers as a means to an end.  No one actually looks forward to using a web scraper.  They’re only interested in the data.  Datafiniti offers data directly to its users.  It’s like comparing a pizza oven to getting an actual pizza.  The oven will eventually make a pizza for you, but why would you use it when you can just get a pizza?
• Competing Data Feeds: There are a small number of companies that offer direct competition to some of our data offerings.  What we’ve found is that our data is simply higher-quality.  We seem to do a lot more work in terms of merging data across sources, normalizing the data so it’s more searchable, and so on.  Our data is just easier to use.

What is your view of the intelligent web data landscape?

It’s very fractured right now. There’s no single solution that people turn to as the market leader.  No one has really approached the problem of providing data from a well-designed product perspective.  We are a young, small company, but we’re hoping to change that, and I think we’re on the right track.

Which are the key success factors for intelligent web data providers?

With data, it’s traditionally been all about volume, velocity, and veracity. I would add a fourth factor: usability.  You need to have the data customers want, and it has to be up-to-date, and accurate.  But it also needs to be accessible – is it easy for them to find it and use it.

How do you see the demand for web data companies shifting over next few years? (With exponential increase in internet data and clients looking at new ways of looking at data through use of Big Data, self-service BI tools and advanced visualizations)

It will continue to grow. We see all sorts of companies ask for our data, each with different use cases.  The potential is practically unbounded.  The question is – how much bigger is the market once companies realize this data is easily accessible.

Which are the sectors observing demand for intelligent web data are how it is adding value to their current processes?

We see a lot of demand from retailers and brands that need competitive intelligence in the e-commerce space. With Datafiniti, they’re able to get insights that were previously unreachable.  eg., it’s super-simple to access every price for every competing product within minutes.  That can radically change the business flow within the marketing department.

Are there any particular sectors picking up on the demand faster than others? Why?

I think we’ll see faster growth from startups once companies are more aware of our offering. By enabling developers to access our data quickly, easily, and affordably, we let them build out proof-of-concepts that can be turned into new businesses.

What is your take on potential jobs losses with web data companies adopting newer technologies? Any new skills that you see in demand 5 yrs. down the line?

Machine learning will supplant manual web scraping soon. Also, data wrangling will become obsolete as cleaner data becomes more available.

So what are some of the main challenges of the intelligent web data setup? Is there any Privacy and Security Issues?

I don’t think there are any privacy issues so long as you stick to accessing public data. We’re only gathering information that anyone can already access.  We just do it at scale.  Our challenges center around scaling our web scraping operations.  We’re trying to move to a more automated process.

Can you talk about mix of few client case studies that were challenging? How did the team finally overcome the obstacles and lessons learnt?

As a young company, there are still things we’re figuring out. Our hope is that so long as we communicate clearly to our customers, they can work with us if we ever encounter any challenges.  We always learn from each customer and apply that learning to our product and technology.

What is next for you and Datafiniti? What are the tools and technologies that you currently use and which ones you plan to use in future?

We’re constantly improving our technology. Our focus this year will be moving toward more machine-learning based approaches to improving our data quality and automating our data extraction.

It’s been a pleasure to chat with you Shion. Thank you for your time.

Great talking to you Kalyan!

Kalyan Banga

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