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Enterprise Data

In this track, we look at migrating and augmenting traditional Business Intelligence and Data Warehousing tools with innovations such as scale-out architectures, cloud data services, noSQL, and eventually-consistent platforms. And we look at the business cases, risks, and constraints of Big Data, helping you to embrace the leading edge—while dodging the bleeding edge.
Who should attend: IT managers, operators, project leads and practitioners

Track Hosts

Mona Vernon leads the Emerging Technologies group at Thomson Reuters. ]Mona is leading the charge on how to create an effective culture of Innovation at Thomson Reuters with a focus of external innovation and reaping the benefits of open innovation. She created and is running several successful initiatives that fall under the broad concept of “intrapreneurship” or applying “lean start-up” principles for the enterprise. She has also been instrumental in creating external innovation partnerships between Thomson Reuters on emerging and disruptive technologies. Mona holds a B.S. and M.S. in Mechanical Engineering from Tufts University and a S.M. from M.I.T. where her research focused on the role of customer experience in digital business strategy. Prior to joining Thomson Reuters, Mona worked in Technology start-ups in product development and management roles.

Mark Madsen designs and builds analysis and decision support systems, and building data management and access infrastructure. Research focus these days is on analysis techniques, emerging technology and practices in analytics, BI, information management, user experience for data access & delivery applications. I speak at a lot of conferences on anything data, with a bunch of history of science and technology mixed in.

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Grand Ballroom West
Matt Asay (MongoDB, Inc.)
Average rating: ***..
(3.89, 9 ratings)
For some, Hadoop is synonymous with "Big Data." But Hadoop is just one component of a successful Big Data architecture. NoSQL solutions like MongoDB also play a dominant role for storage and real-time data processing, and RDBMS has a place, too. This session will drill down on the different types of NoSQL databases and how they fill out Hadoop and RDBMS in a modern Big Data architecture. Read more.
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Grand Ballroom West
Stephen Brobst (Teradata Corporation), Ari Zilka (Hortonworks)
Average rating: ****.
(4.00, 6 ratings)
Hortonworks Chief Product Officer, Ari Zilka, and Teradata CTO, Stephen Brobst, show you when to use Hadoop and when to use an MPP relational data warehouse. At a conceptual level, it is easy to think they are interchangeable, but the differences overwhelm the similarities. Two of the most trusted experts in their fields examine how big data technologies are being used in practical deployments. Read more.
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Grand Ballroom West
Bill Schmarzo (EMC Consulting), John Akred (Silicon Valley Data Science), Anand Raman (Impetus Technologies, Inc.), Scott Rose (Think Big Analytics)
Average rating: ***..
(3.67, 3 ratings)
Opinions might be plentiful in big data, but experience is rare. Join this interactive session to quiz some of the industry's most seasoned minds about what works and what doesn't when it comes to bringing big data to business. Read more.
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Grand Ballroom West
Srini Srinivasan (Aerospike Inc.)
Average rating: *....
(1.80, 5 ratings)
Internet environments for consumer-facing applications routinely demand high throughput while SLAs require100% uptime. This session reviews 10 practices for ensuring high performance and availability based on the real-world lessons of large-scale ad sector deployments where speed means 5 milliseconds, scale is 200,000 to 2 million TPS against terabytes of data, and downtime is not an option. Read more.
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Grand Ballroom West
Average rating: *****
(5.00, 3 ratings)
Big data is transforming the cloud as it moves from web giants into the enterprise. To run today’s multiple workload types, infrastructure must be architected as a common software-defined platform that supports the key workload components for todays and tomorrow’s big data systems. We must plan now to accommodate explosive growth and the need for robust storage, networking and security. Read more.
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Grand Ballroom West
Sumeet Singh (Yahoo!)
Average rating: ***..
(3.33, 3 ratings)
Enterprises thinking of adopting Hadoop are increasingly debating between on-premise and cloud-based models for their needs. We lay out a set of criteria to help enterprises evaluate their options. For the ones who have already made or have plans to make significant on-premise investments, we present an approach to manage Hadoop as a service with a P&L, and metering & billing provisions. Read more.
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Grand Ballroom West
Q Ethan McCallum (@qethanm), Brett Goldstein (University of Chicago)
Average rating: **...
(2.78, 9 ratings)
Data analysis has become a key element of a business, yet there is painfully little guidance for leadership roles who are tasked with building and managing this critical function. We've spoken with various companies to get their take on how to build an analytics shop, and we'd like to share that information with you. Read more.
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Grand Ballroom West
John Akred (Silicon Valley Data Science), Stephen OSullivan (Silicon Valley Data Science)
Average rating: ****.
(4.50, 4 ratings)
A modern CIO rationalizing a company’s data architecture must consider a mix of deployment options like a utility executive has to invest in a good generation mix. We articulate a framework for applying the deployment levers available to architects as they plot a course forward in this era of big data technologies, born of our deep experience implementing the world's largest data platforms. Read more.
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Grand Ballroom West
Erin Shellman (Nordstrom), David Von Lehman (Nordstrom)
Average rating: ****.
(4.50, 10 ratings)
Nordstrom started modestly in 1901 as a small shoe store in Seattle, and has since expanded to 117 full-line department stores and 138 Rack stores across the country. The art of retailing has changed dramatically over the last century and retailers today are concerned with understanding customer behavior and preferences both in the physical world and online. Read more.
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Sutton Center - Sutton South
Micheline Casey (Federal Reserve Board)
Average rating: *....
(1.67, 3 ratings)
Traditionally, security has tended to mean "lock down and protect". But there is a balance between securing data while still supporting information sharing and reuse. This presentation is meant to educate data management professionals at all levels how to manage this balance. Read more.
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Sutton Center - Sutton South
Eddie Satterly (Splunk)
Average rating: ***..
(3.38, 8 ratings)
In this session you will hear from big data experts with real world experience on the architectural patterns and tools integrations used to solve real business problems with data. Read more.
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Sutton Center - Sutton South
Volkmar Uhlig (Adello)
Average rating: ****.
(4.00, 5 ratings)
Machine-generated data is getting stale fast. Operational data, sensor data, or video feeds requires new automated approaches to capture value. In this sessions we will show how to apply the lessons learned from automated trading systems and high-frequency trading to today’s Big Data problems to monetize information. Read more.

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