Interview with Sundeep Sanghavi, CEO of DataRPM
What is your startup
DataRPM is an award-winning, industry pioneer in smart machine analytics for big data.
What does it do?
Leveraging the power of cognitive computing, DataRPM delivers the unprecedented ability for business people to talk – literally – to their data in plain English and immediately receive visually intuitive answers. DataRPM uses this same advanced computational approach to automatically model multiple disparate data sources, delivering huge reductions in labor and cost associated with IT support of Big Data initiatives.
DataRPM’s smart machine analytics solution provides an end-to-end smart pipeline for effective Big Data Discovery and Analytics. DataRPM enables Automatic Data Modeling from disparate data sources using cognitive algorithms, eliminating the need to manually build complex data warehouses. The data is modeled into a Computational Search Graph stored in a smart data lake, empowering business users to do ad-hoc, cross-source data analysis in real-time. Finally, our Natural Language Question-and-Answering interface provides an easy, Google-like user experience, enabling anyone in the enterprise to talk directly to their data in a human-friendly, natural language and instantly receive automatically visualized answers.
Who is your startup aimed at?
I co-founded DataRPM with the goal of providing a cognitive data discovery solution that delivers hyper-fast results to organizations challenged by the volume, velocity and variety of their big data.
We are aimed at businesses that are looking for a faster and more accurate way to analyze and draw powerful insights from their big data. Utilizing the power of cognitive computing, DataRPM solves the issues brought on by manual approaches by automating tasks and facilitating information for businesses to allow data scientists and analysts to focus on more productive analysis of big data, rather than mundane, “data janitor” work.
How does your startup stand out against its competitors?
DataRPM competes primarily against IBM Watson Analytics (which is very different from the original IBM Watson). IBM Watson Analytics takes the natural language parsing layer of the original Watson smart machine and rehashes the existing enterprise SPSS data modeler, Catalyst and some parts of Cognos as well to create a data discovery / BI solution. This is where they are in similar turf as us.
The difference with DataRPM is that we are an end-to-end full stack solution designed ground up (without any rehashing) to enable smart machine analytics right from our smart data modeling from disparate data sources to smart search-based computation on commodity hardware using our just-in-time memory to smart visualization – all of which are designed to scale for big data on any infrastructure (cloud or on-premises) and works out-of-box with minimal pre-training or complex configurations and gives the fastest go-live from raw data to insights. We provide one click Smart Insights for data interpretation and Smart Prediction where the system enables anyone to use data intelligently without really requiring knowledge of the science behind it.
DataRPM was named “Best New Big Data Solution” by the American Business Awards and “Cool Vendor” in Content and Social Analytics by Gartner in 2014.
It was recognized as one of the DC’s hottest startups by the Tech Cocktail Showcase in 2013 and was ranked as 10 Startups destined to break out in 2014 by Tech.co. It is also ranked as one of the Top 10 Big Data Analytics Company by Enterprise Apps Today.
Where did the idea for the startup come from?
Our inspiration for DataRPM came when we began building and using several analytics solutions ourselves. We realized how difficult and expensive it is for a company to build a custom solution and how complicated it can be to use the ones currently the market.
We set out to solve two of the biggest business intelligence problems that exist today. Those being the long, expensive and painful manual data warehousing from disparate data sources, and the significant learning curve of BI software leading to poor user experience and adoption.
DataRPM’s patent-pending Computational Graph Search technology enables automatic and dynamic modeling of data from disparate sources using semantic algorithms, eliminating the need of manually building complex data warehouses for BI. DataRPM provides a natural language question answering interface to analyze and visualize data that learns from user behavior, eliminating the software learning curve seen in other BI platforms.
How did you initially raise funding for your company?
DataRPM is privately held and venture backed.
How long has your startup been in the making, and who is the team behind the business?
DataRPM was founded in 2012 by Gautam Shyamantak, Ruban Phukan, and I. Gautam Shyamantak is the former technical architect at Trigo, which was acquired by IBM, and Ruban Phukan was a data scientist at Yahoo and the co-founder of Bixee, which was acquired by Ibibo.