Big Data Everywhere New York is a half-day conference focused on Hadoop and surrounding technologies that will bring together users and developers to share their experience about these projects via multiple presentations and user success stories. Industry experts will exchange Hadoop knowledge, share best practices, and discuss Hadoop use cases.
Tickets are half-price for SQL/NoSQL NYC Meetup members (join at http://www.NYCSQL.com) - we can attend a big data conference for just 24-bucks!
Registration includes free breakfast and a networking lunch!
Register NOW, seats are limited!
50%-off discount code: SQLNYC
Hear about real-world Hadoop delployments and other tales from the trenches of big data!
• Vice President of IT for Morgan Stanley
• Chief Application Architect at MapR
• CTO of Nvent Data
• Cisco's Big Data Consulting Systems Engineer
• CIO of Pico
• Apache Mahout, Drill, & ZooKeeper Projects Committer
• CEO of Zaloni
• Morgan Stanley's Big Data Journey
• Secure Collaboration on Big Data: Locking Down Doesn't Mean Locking Out
• Leverage a Hadoop Data Lake to Address Risk Data Aggregation and Risk Reporting
• The Transformational Influence of Big Data in the Global Capital Markets
• Odyssey: A Look at The Evolution of Big Data Ingestion Pipelines
• Cisco IT's Hadoop Journey
Register TODAY, seats are limited!
50%-off code: SQLNYC
Leverage a Hadoop Data Lake to address Risk Data Aggregation and Risk Reporting by Ben Sharma, CEO, Zaloni
Addressing risk data aggregation and risk reporting (RDARR) is a challenge today for many reasons, including data accuracy and integrity, data completeness, and ensuring that you have a data architecture that can support normal and high stress scenarios. During this presentation, Ben Sharma will address how a “managed” Hadoop data lake can serve as an ideal data acquisition hub for RDARR analytics and reporting. He will address architectural considerations and required capabilities.
Odyssey: A Look at The Evolution of Big Data Ingestion Pipelines by Steve Morin, CTO, Nvent Data
Get an overview of the maturing Big Data ecosystem as companies move more towards real-time analytics tools that ingest, extract, translate, and then clean up data for analysis. You'll also get a look at a data ingestion pipeline architecture, how it has evolved over time, and its use cases in today's big data landscape.
Cisco IT's Hadoop Journey by Robert Novak, Big Data Consulting Systems Engineer, Cisco
In this talk, you'll get insights into Cisco’s own Hadoop journey and how Cisco implemented a highly agile enterprise Hadoop platform, delivering multiple use cases including ETL migration, content management, smart analytics and compliance.
The Transformational Influence of Big Data in the Global Capital Markets by Paul Cassell, CIO & Daniel Bartucci, Director of Corporate Development, Pico
The business of financial and global capital management is bursting with hundreds of millions of transactions every day. Recent volatility in the financial markets is driving increased message traffic from electronic trading, stretching systems that simply aren’t equipped to handle such volume. With growing financial data sources and data types (such as social media, audio, and video), the need for big data technologies that can store, process and analyze this financial data is more important than ever. Join Paul Cassell, Pico CIO and former U.S. chief information officer for NYSE Euronext and the New York Stock Exchange, along with Daniel Bartucci, Director of Corporate Development, as they provide details on scalable, cost-effective, best-of-breed big data technologies that you can leverage for financial data management, regulation, risk analytics, and trading analytics. You’ll come away with a better understanding of how you can harvest and leverage this data so that you can stay one step ahead of your competitors.
Secure Collaboration on Big Data: Locking Down Doesn't Mean Locking Out by Ted Dunning, Committer for Apache Mahout, Drill, & ZooKeeper Projects & Chief Application Architect, MapR
Mobile payments, online banking, smart kiosks, etc. are the platforms driving bank growth for the next 20 years. All of them produce gobs of data and all of them provide opportunities for fraudsters to steal. In order to keep up, new kinds of predictive analytical models will have to be built. In order to develop these new kinds of models, we need all hands on deck, both inside and outside of financial institutions. Unfortunately, cooperation on new modeling technologies is very difficult to do without sharing sensitive data in ways that just isn't acceptable.
I will describe some recently developed techniques that break this logjam. These methods are simple enough to deploy widely but provide very robust security against even the most advanced de-anonymization attacks.
Morgan Stanley's Big Data Journey by Erwan Le Doeuff, Vice President Information Technology, Risk and Security, Morgan Stanley
Morgan Stanley will highlight some of the exciting things they’re doing as they expand big data projects throughout the organization, including how to start out with test projects, choose open source projects, scale systems, and produce meaningful results.
50%-off code: SQLNYC
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