Converting raw information to insight is a huge challenge in a world where data comes at organizations in massive, unwieldy quantities. Datameer offers a solution wherein the data being analyzed is not warehoused but instead goes into Hadoop in its raw form. We caught up with Karen Hsu, Sr. Director of Product Marketing at Datameer, to get the details.
Karen Hsu: Our CEO, Stefan Groschupf, was one of the original contributors to Nutch, the open source project that spun out Hadoop. Stefan and our core engineering team spent years architecting and implementing distributed big data analytic systems for companies like Apple, EMI, Hoffman La Roche, AT&T, the European Union, and others. Realizing they were architecting essentially the same solution over and over, they decided to create a company to productize that solution. On one Friday in late 2009 Stefan fired all of his engineers, and that following Monday he hired them all to the new company, and that was how Datameer was born.
While we may only be just over four years old, we actually have 10+ years of experience both helping to form and innovating in the Hadoop market. As you might guess, we’re very involved in the Hadoop community still. We continue to present and participate in meet ups and conferences to share and learn. We partner with and support all of the Hadoop distribution vendors. In fact, Stefan and team even contributed the yellow elephant logo we all know and love today.
insideBIGDATA: Please tell me what’s new at Datameer. What are the latest offerings and products?
Karen Hsu: Datameer is all about providing a self-service, end-to-end experience for big data analytics on Hadoop. From data integration to analytics to visualization, we are wizard-led, point-and-click. Most recently we announced our Smart Analytics module, which allows business users to use data mining algorithms through a drag and drop UI. These new capabilities complement what data scientists are doing and enable business analysts to take advantage of advanced algorithms without involving IT.
insideBIGDATA: Which market segments best suit these products?
Karen Hsu: Datameer is a horizontal solution. We have customers in just about every vertical, including financial services, manufacturing, high-tech, pharma, healthcare, telcos, retail, logistics, gaming, and eCommerce. Anyone who has disparate data sources they need correlate has a use case for Datameer. That being said, we see four common use cases, and those are customer analytics, operational analytics, fraud and compliance, and enterprise data warehouse optimization.
insideBIGDATA: Datameer positions itself as a pioneer. What sets the company apart from what the competition?
Karen Hsu: Our biggest differentiator is the the fact that we significantly shorten the time it takes to get to insight. We do this in several different ways. First, we are built natively on Hadoop, which enables a no-schema approach. That means no more extracting, transforming, or loading (ETL) data into a data warehouse. We get your data into Hadoop in its raw format right away. This alone saves months both on the front end and any time a user wants to add another data source. Second, we’re a self-service solution built for business users. Business users are the subject matter experts, and should be the ones working with the data directly. They shouldn’t have to go to IT every time they want to ask a new question. Third, we’re an all-in-one tool for data integration, analytics and visualization. In traditional business intelligence, there are typically three different tools and three different teams involved. With these features combined, there is no other tool on the market that allows you to get from raw data to insight in such a short period of time.
insideBIGDATA: As more and more of the enterprise segment sees the value in Big Data, how is Datameer positioning itself to get a piece of that pie?
Karen Hsu: Datameer was early to market. We now have hundreds of customers and a lot of experience getting these customers into production. Not only do we have the unique differentiators mentioned above, but we have the experience and the talent to help these customers get the most out of big data. Finally, we have built in all the requests they have made for an enterprise-ready, scalable, performant product that is monitored and optimized for production.
insideBIGDATA: Is there a recent success story involving a client that you’d like to tell us about?
Karen Hsu: Sure! One of our favorite new customers is Trustev an ecommerce identity verification solution that Forbes calls one of Europe’s hottest tech startups. In fact, they just won SXSW’s Startup Accelerator competition, and we couldn’t be more thrilled for them. We put together a cool video with them which you can watch here, but basically, they’re using Datameer in two capacities. First, they use Datameer to integrate and analyze 8 types of data (including location, email verification, social fingerprinting, website behavior) to increase the overall accuracy of Trustev’s fraud detection system. Second, they’re using Datameer to help deliver those insights to Trustev end-users via an interactive dashboard. We’re also doing a webinar with Trustev on March 19th, which anyone can join by registering here.