Thought Leaders in Big Data: Nenshad Bardoliwalla, VP of Products, Paxata (Part 6)

Sramana Mitra: You founded it in 2012. We are now in 2014. How much adoption have you had following your methodology and in what segment? Where are you finding the sweet spot of your adoption?

Nenshad Bardoliwalla: I’m not at liberty to share the exact customer numbers, but we’re above 20 customers at this point. We have a variety of customers. We basically target five industry segments that we think are right for the types of analysts that we target. The five segments are high tech manufacturing, consumer products, retail, financial services, and public sector. >>>

Thought Leaders in Healthcare IT: Girish Navani, CEO of eClinicalWorks (Part 3)

Sramana Mitra: That’s great. I’m actually working on a book on Unicorn Companies right now. I would love to include you in that. The definition of this Unicorn Company is billion-dollar exit. The truth is if you were to exit in the market today, you would be over a billion dollar in valuation easily.

Girish Navani: Easily. Maybe, multi-billion.

Sramana Mitra: It’s probably more like $3 billion plus valuation. You’ve probably seen my work in the last four years that we’ve launched One Million by One Million. Our philosophy is entrepreneurship equals customers, revenues, and profits. Financing and exit are optional. That’s a very simple and powerful change in the way entrepreneurship is viewed. >>>

Thought Leaders in Big Data: Nenshad Bardoliwalla, VP of Products, Paxata (Part 5)

Sramana Mitra: Let’s look at use cases now that we understand what you do. Let’s do a before and after. If you were not in the picture, what are they able to do? With you in the picture, what are they able to do?

Nenshad Bardoliwalla: I’ll give you a story of my own life because this is actually how we started designing the Paxata product. If you’re an analyst today, your number one weapon of choice is Excel. That has always been the case for as long as Excel was available. When it comes to data preparation, the analyst lifecycle looks like the following. I used to get a request from one of the management teams saying, “I need you to answer this analytical question. I need you to find out which of our accounts in Europe have this many escalations logged against them, find out who is assigned to those cases, and how long they have been in operation.” >>>

Thought Leaders in Big Data: Nenshad Bardoliwalla, VP of Products, Paxata (Part 4)

Nenshad Bardoliwalla: Typically what we find is that once we prepare the data, that data is then pulled by the consuming applications. However, it’s also important to note that we ourselves do persist with data. A very important part of our value proposition is the notion of data governance. We maintain and cache a copy of all the data that actually flows through our system, which means that we also keep every version of data that’s ever loaded into the system, every version of data that is transformed in our system, and every version of data that is exported. The moment a data element hits our system to the moment it goes out, >>>

Thought Leaders in Big Data: Nenshad Bardoliwalla, VP of Products, Paxata (Part 3)

Sramana Mitra: It stopped being relational a long time ago.

Nenshad Bardoliwalla: That’s right. So if you have S. Mitra in your relational database, Sramana M. in your tweets, and Sramana Mitraa with two A’s at the end in one of your documents, you need to be able to figure out in 2014, regardless of the schema or the structure of the data, that those are all referring to the same entity. Our machine learning techniques are able to introspect the content and come back and make a recommendation to the user so that they don’t have to figure out how to align these schemas together. That’s also an important point of our positioning.

 Sramana Mitra: If you look at the ecosystem map, where would you fit layer-wise? >>>

Thought Leaders in Big Data: Ulf Mattsson, CTO of Protegrity (Part 5)

Sramana Mitra: What is the status of that capability in the Big Data industry today to be able to achieve that balance between protection, privacy, and analytics?

Ulf Mattsson: Larger companies and companies providing Big Data distributions like Cloudera and Hortonworks are actually involving third-party security companies like Protegrity to fill the security gaps. For example, Protegrity has partnerships with Cloudera, Hortonworks, IBM, Infosphere, Teradata, and other companies to satisfy these new types of security requirements.

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Thought Leaders in Big Data: Ulf Mattsson, CTO of Protegrity (Part 4)

Ulf Mattsson: We’ve seen studies talking about how Big Data analytics can revolutionize the way the Internet  did many years ago. I’ve seen figures saying that 63% are using it to enhance customer relationships, 58% are using these capabilities to redefine the product and product development, and 56% are using it to change their operations. These create a lot of opportunities but, at the same time, open up privacy issues. According to recent reports and studies, 51% are saying that security is the most important issue. The monetization of data and data breaches are driving the need for security. >>>

Thought Leaders in Big Data: Ulf Mattsson, CTO of Protegrity (Part 3)

Ulf Mattsson: Let’s look at another interesting use case. It’s a travel product company. It’s an airline-owned company in the US that is providing ticket distribution and financial settlements for 135 airlines and 23,000 travel agents. They have more than $65 billion per year in settlement. Their primary issue was to protect sensitive customer data and payment data. It’s a challenge when you have these different varieties of data. They’re looking for a solution that can fit the requirement, be flexible, and not disrupt their business processes. They also choose this new type of protection called data tokenization. These are three interesting use cases of our technology. >>>