Big Data: It's Everywhere. And So Are We.

Boston
May 17, 2016

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Co-Presented By: MapR

Featured Talks

Big Data: Mind the Gap

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Beyond Hadoop – The Next Generation Data Platform

As customers begin to deal with data deluge, storage growth, and shrinking budgets, they have to evaluate how to best manage legacy and new applications based on old...

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Modern Streaming Analytics, Flow versus State

The leading edge of big data architectural practice is rapidly moving to flow-based computing using streaming architectures as opposed to state-based computing based on batch programs...

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Agenda: May 17, 2016

The Westin Boston Waterfront
425 Summer Street, Boston, MA 02210

FULL SCHEDULE
8:00am - 9:00am	Registration & Breakfast
9:00am - 9:15am	Introductions & Welcome
9:15am - 10:00am	Modern Streaming Analytics, Flow versus State Ted Dunning, Chief Application Architect, MapR
10:00am - 10:45am	Beyond Hadoop – The Next Generation Data Platform Bob Fosina, Sales BDM - Advanced Analytics & Data Science, Cisco
10:45am - 11:15am	Inside Eastern Bank's Big Data Journey Brian Griffith, Principal Data Engineer, Eastern Bank
11:15am - 11:45am	Morning Break & Book Signing
11:45am-12:15pm	Big Data: Mind the Gap Brad Anderson, Vice President, Big Data Informatics, Liaison Technologies
12:15pm - 12:45pm	Data Management as a Service to Drive Business Value Julio Gomez, Knowledgent
12:45pm - 1:15pm	The Successful Data Lake: How Data Wrangling Bridges IT & Business Chris Moore, Senior Sales Engineer, Trifacta
1:15pm - 2:00pm	Networking Lunch

Featured Speakers

Bob Fosina

Sales BDM - Advanced Analytics & Data Science, Cisco Bob Fosina holds a BA in Computer Science, a MS in Telecommunications and numerous certifications from companies like Microsoft and Gartner Group. Fosina has also attended HP sponsored Executive MBA classes at Harvard Business School.

Ted Dunning

Committer for Apache Mahout, Drill, & ZooKeeper Projects & Chief Application Architect, MapR Ted Dunning is Chief Applications Architect at MapR Technologies and committer and PMC member of the Apache Mahout, Apache ZooKeeper, and Apache Drill projects and mentor for Apache Storm, Apache Spark and Apache Flink. Ted is also now VP of Incubator for the Apache Software Foundation. Ted was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems. He built fraud detection systems for ID Analytics (LifeLock) and he has 24 patents issued to date and a dozen pending. Ted has a PhD in computing science from the University of Sheffield. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting.

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Brian Anderson

Vice President, Big Data Informatics at Liaison Technologies CAll executive teams have business questions to answer and problems to solve. Can you take actions or make changes which drive revenue or cut costs as a data-driven business? Can you in some way monetize the data exhaust from your business? The vendors in the market are happy to tell you about big data systems designed to answer these questions and solve these problems. They tend to gloss over a couple of the more difficult gaps you must fill to achieve these goals. First, 80% of the work to gain insight from data is spent cleansing and harmonizing, or 'data janitor' work. Second, the resulting workflows and systems are often hard-coded and not reusable in the future. There is a decided lack of frameworks that foster reuse between the different and complex systems. Third, regulatory compliance and data governance are largely unknown disciplines and missing features with these new systems. We will discuss the executive team’s business problems, the market’s new big data systems, and how to mind the gap between them.

Brian Griffith

Principal Data Engineer, Eastern Bank Brian Griffith’s career spans more than 15 years as an engineer in the software, entertainment, and financial industries. Prior to Eastern Bank, he was a data engineer at Blizzard Entertainment, where he helped architect and deploy their big data solution, supporting some of the largest video games on the planet. Currently at Eastern Bank, he leads the data engineering effort to traverse vast sets of data in order to enable business lines to better serve their customers. He holds a B.S. and an M.S. from Northeastern University, specializing in neuroanatomy and statistics. When he’s not thinking about data at his desk, he’s typically thinking about it while cycling around New England as an ultra endurance cyclist.

Chris Moore

Senior Sales Engineer, Trifacta Chris is an enterprise technology veteran with more than 10 years in the data warehousing and ETL space. As a Senior Solutions Engineer for Trifacta, he focuses his expertise in the Financial Services industry on Big Data, Data Quality, and Master Data Management.

Big Data Everywhere

The Westin Boston Waterfront
425 Summer Street
Boston, MA 02210

Other Upcoming Cities

Singapore: May 10, 2016

Munich: May 11, 2016

Ft Lauderdale: May 12, 2016

Mumbai: May 13, 2016

Past Cities

Chicago: April 28, 2016

Minneapolis: April 26, 2016

San Diego: April 12, 2016

Mumbai: Jun 26, 2015

Full Big Data Everywhere Talks

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Big Data: Mind the Gap

Brad Anderson, Vice President, Big Data Informatics at Liaison Technologies

All executive teams have business questions to answer and problems to solve. Can you take actions or make changes which drive revenue or cut costs as a data-driven business? Can you in some way monetize the data exhaust from your business? The vendors in the market are happy to tell you about big data systems designed to answer these questions and solve these problems. They tend to gloss over a couple of the more difficult gaps you must fill to achieve these goals. First, 80% of the work to gain insight from data is spent cleansing and harmonizing, or 'data janitor' work. Second, the resulting workflows and systems are often hard-coded and not reusable in the future. There is a decided lack of frameworks that foster reuse between the different and complex systems. Third, regulatory compliance and data governance are largely unknown disciplines and missing features with these new systems. We will discuss the executive team’s business problems, the market’s new big data systems, and how to mind the gap between them.

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Beyond Hadoop – The Next Generation Data Platform

Bob Fosina, Sales BDM - Advanced Analytics & Data Science, Cisco

As customers begin to deal with data deluge, storage growth, and shrinking budgets, they have to evaluate how to best manage legacy and new applications based on old architectures for the newly acquired data sets and applications coming into the company. In this session, we’ll look at how to best optimize and augment your growing databases, data warehouses, and enterprise storage solutions. We’ll investigate how to take advantage of a new data platform that allows you to create a repeatable, extensible, and highly scalable platform for your entire company. MapR’s Converged Data Platform, along with Cisco's UCS Integrated Infrastructure, will help you build a data platform that will serve both your IT and Line of Business Users for years to come.

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Modern Streaming Analytics, Flow Versus State

Ted Dunning, Chief Application Architect, MapR

The leading edge of big data architectural practice is rapidly moving to flow-based computing using streaming architectures as opposed to state-based computing based on batch programs plus workflow schedulers. This transition is part of the larger movement towards micro-services and devOps oriented development and maintenance of large systems. This fashion is spreading quickly, but the understanding of why flow-based computing is different from state-based computing and what this means is practice is lagging behind. In fact, there is a huge difference and this has the potential of massively simplifying big data systems, thereby improving reliability and time to market. I will describe the necessary key concepts and illustrate them with practical examples. I will also describe why this matters in the real world.

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Data Management as a Service to Drive Business Value

Julio Gomez, Knowledgent

Over the past year, one Knowledgent client has pursued a unique data strategy that leverages Big Data and Cloud technologies, unlocks siloed enterprise data, and feeds hungry analytics users across business units. In this session, we will present the case study highlighting the current state of the art in “data management as a service,” and the impact on business value.

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The Successful Data Lake: How Data Wrangling Bridges IT & Business

Chris Moore, Senior Sales Engineer, Trifacta

Designing a Hadoop data lake has huge potential gains. But many organizations have shied away from the investment, fearing that only their most technologically capable (and scarce) data science resources could truly take advantage of the technology. How can IT best outfit its investment with the right supporting applications to entice business users, while also ensuring governance? In this presentation, we walk you through the major components of a data lake and how to make it successful. Specifically, you’ll learn: The advantages of designing a data lake and the components involved Why data wrangling offers a unique, self-service solution Common use-cases amongst Fortune 100 companies for data wrangling.

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Inside Eastern Bank's Big Data Journey

Brian Griffith, Principal Data Engineer, Eastern Bank

Interview session.

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