Ashish focuses on Big Data in Life Sciences.
Sramana Mitra: Let’s start by introducing our audience to yourself as well as to Axtria.
Ashish Sharma: Thanks for the opportunity. Axtria is a global Big Data analytics company. Our main focus is around the life sciences and financial services industries. In those two focus areas, we empower them to optimize their business strategies or their investments by optimizing their investment around both Big Data and advanced analytics.
The biggest problem in that space is how to create efficiency and flexibility by maintaining certain levels of compliance and privacy around the data. Those two elements are very critical to these two industries. While doing that, how do you combine technology and domain knowledge in a way that you are differentiating yourself either from a traditional technology company or a traditional domain expertise provider.
I come from a background of building small to mid-sized companies in Silicon Valley around Data-as-a-Service or Big Data-as-a-Platform.
Sramana Mitra: Do you have any background in the life sciences industry? Is that something that you have prior experience with or is this a new domain?
Ashish Sharma: My wife is a physician if that counts as experience. The two companies that I collaboratively built with a bunch of other partners in the past sold to life sciences but not in the way that Axtria does. Axtria has deeply penetrated focus on both life sciences and financial industries. What I was selling was more of a productized solution that was taking care of one aspect of their data needs or platform needs.
Sramana Mitra: Let’s double-click down into some of the types of customer problems that you’re solving with Big Data. Take some use cases in your customers that you can talk about. You don’t necessarily have to name customers. You can if you’d like to. Talk about scenarios and problem domains, and how you’re solving them.
Ashish Sharma: Axtria started as a data science company, and it is heavily invested in a lot of accelerators of frameworks that could expedite the journey from a data point of view. Most of the analyst communities in life sciences and financial industry struggle with two things.
One is, how can I get access to data in a form that I can analyze quickly and I can spend more time analyzing data as opposed to struggling with how to get the data in a format that I can use. Most of our frameworks are around combining very process-aware and domain-aware frameworks for these two very specific industries that expedite that whole data journey from raw data to the dashboard.
We are creating per STE efficiency for these organizations. If they have 200 to 300 analysts, by leveraging these different process-aware and domain-aware accelerators, they’re able to expedite the whole journey and reduce that whole data preparation time. It reduces the dependency on IT or data engineering organization by expediting that journey.