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Thought Leaders in Big Data: Interview with Stew Langille, CEO of Visual.ly (Part 1)

Posted on Monday, Jan 14th 2013

Stew Langille is the chief executive officer and co-founder of Visual.ly. Previously Stew was director of marketing at Mint.com, where he built that company’s data business. He is a pioneer in the use of data as a marketing vehicle for both publishers and brands. In this interview Stew talks about how Visual.ly applies big data to visualize content in a cost-effective and practical way and gives insight into how to become a player in the big data visualization space.

Sramana Mitra: Stew, let’s start with a bit of context about Visual.ly. Could you introduce the company to our readers and explain what you do and how you do it?

Stew Langille: We are the largest platform and community for data visualization on the web. We are composed of a group of 50,000 community members, who are information designers (that is, designers who are interested in information and data visualization), journalists, developers, and data scientists. >>>

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Thought Leaders in Big Data: Derek Rodner, Vice President of Product Strategy, Agilence (Part 1)

Posted on Thursday, Jan 10th 2013

Derek Rodner is the vice president of product strategy at Agilence, an industry-leading company in retail big data. In this interview Derek talks about the implications of more widespread use of big data on retail video surveillance and security systems, and about future trends in the industry.

Sramana Mitra: Hi, Derek. Could you please start by putting some context around Agilence so that our readers are able to follow the rest of the story accordingly?

Derek Rodner: I’d be happy to. Agilence is a big data and cloud provider focused on the retail space. Our goal is to provide store-level insight across the entire chain at a corporate level. Our customer range is anywhere from small retailers all the way up to Rite Aid, which has 4,700 locations around the country. >>>

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Thought Leaders in Big Data: Interview with Dale Skeen, CTO of Vitria (Part 1)

Posted on Monday, Jan 7th 2013

Dale Skeen is CTO and co-founder of Vitria Technology Inc. He has a PhD from the University of California, Berkeley, and was chief scientist for TIBCO Software prior to founding Vitria. Today, Dale is considered by many of his colleagues in the industry as the pioneer in real-time business process analysis. In this interview he talks about the application of big data as an infrastructure as compared to a service, and he points out the various opportunities for entrepreneurs in the market of big data analysis.

Sramana Mitra: Dale, let’s start with context about you and about Vitria. I have known of Vitria for a very long time, having been in the industry for a while, but I suppose that it has evolved considerably. What could you tell us about the current direction of Vitria and the implications for big data on the company? >>>

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Thought Leaders in Big Data: Franz Aman, Chief Marketing Officer, Silicon Graphics (Part 1)

Posted on Monday, Dec 31st 2012

Franz Aman is the chief marketing officer of SGI (Silicon Graphics), a leader in technical computing. Franz counts more than 20 years of leadership and innovation in global product marketing, brand strategy, and communications. In this interview, he talks about the development of SGI over the past two decades and the opportunities and possibilities that lie in big data in the coming years, especially with regards to real-time data processing.

Sramana Mitra: Franz, let’s start with an introduction to SGI. I have known the company for at least 20 years. We even used SGI machines when I was at university at MIT. We were designing chips using gap tools that were used in SGI or some workstations. Today SGI looks like a very different company. What would you like the world to see when it looks at SGI today? >>>

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Thought Leaders in Big Data: David Bernstein, Vice President of eQuest’s Big Data Division (Part 1)

Posted on Sunday, Dec 23rd 2012

David Bernstein is the vice president of the big data division at eQuest, a major job posting distribution company. Each year, more than 250 million job postings are delivered through eQuest. In this interview, David talks about how eQuest handles big data, how information is being gathered to provide customers with accurate consulting, and trends for the future of the field of human resources.ss

Sramana Mitra: David, let’s start with some context about eQuest and you. Our audience loves niches, but those niches need to be introduced before.

David Bernstein: eQuest is 18 years old and has been primarily serving as an infrastructure for productivity support tools [as] a component of talent acquisition, which [includes] job board posting services.  >>>

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Thought Leaders in Big Data: Omer Artun, CEO of AgilOne (Part 1)

Posted on Wednesday, Nov 28th 2012

Omer Artun is the founder of AgilOne, a company which provides cloud-based predictive customer analytics. He studied at Brown University and holds a PhD in computational neuroscience/machine learning and physics. He previously worked for McKinsey & Company and for the marketing division of Best Buy. Seven years ago he decided to found his own company to apply his expertise to medium-sized businesses.

Sramana Mitra: Omer, let’s start with some context.  Tell us a little bit about your company. How long has it been in business? I know you are moving from stealth mode to a more public launch, so please give us some context.

Omer Artun: I started the company about seven years ago. I bootstrapped it from no revenue to having about 40 employees when I received the first funding.  I started the company out of firsthand frustration that I had as a marketer. I used to run marketing for a division of Best Buy – Best Buy for Business – and before that I was VP of marketing at Microwarehouse, which was a direct marketer of computers and related products. Before that I did strategic consultant for McKinsey, and I have a PhD in machine learning. When I was running these marketing departments, which had millions of customers, millions of transactions, and billions of clicks, there was so much information in this data which could be utilized [to make] better marketing decisions. >>>

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