Presented By O'Reilly and Cloudera
Make Data Work
Feb 17–20, 2015 • San Jose, CA
Gwen Shapira

Gwen Shapira
System Architect, Confluent

Website | @gwenshap

Gwen Shapira is a Solutions Architect at Cloudera and leader of IOUG Big Data SIG. Gwen Shapira studied computer science, statistics and operations research at the University of Tel Aviv, and then went on to spend the next 15 years in different technical positions in the IT industry. She specializes in scalable and resilient solutions and helps her customers build high-performance large-scale data architectures using Hadoop. Gwen Shapira is a frequent presenter at conferences and regularly publishes articles in technical magazines and her blog.

Sessions

9:00am–12:30pm Wednesday, 02/18/2015
Hadoop in Action
Location: 210 D/H
Mark Grover (Lyft), Jonathan Seidman (Cloudera), Gwen Shapira (Confluent), Ted Malaska (Capital One)
Average rating: ****.
(4.54, 13 ratings)
Are you looking for a deeper understanding of how to integrate components in the Apache Hadoop ecosystem to implement data management and processing solutions? Then this tutorial is for you. We'll provide a clickstream analytics example illustrating how to architect solutions with Apache Hadoop along with providing best practices and recommendations for using Hadoop and related tools. Read more.
1:30pm–2:10pm Thursday, 02/19/2015
Ask Us Anything
Location: 211 B
Moderated by:
Mark Grover (Lyft)
Panelists:
Jonathan Seidman (Cloudera), Gwen Shapira (Confluent), Ted Malaska (Capital One)
Join the authors of Hadoop Application Architectures for an open Q/A session on considerations and recommendations for architecture and design of applications using Hadoop. Talk to us about your use-case and its big data architecture, or just come to listen in. Read more.
10:40am–11:20am Friday, 02/20/2015
Hadoop in Action
Location: 210 B/F
Gwen Shapira (Confluent)
Average rating: ****.
(4.43, 7 ratings)
Organizations do not store, process and analyze data for their amusement. They plan to use the data to drive business decisions. If data validity is uncertain, the data is useless for decision making. In this session we will show how to design architectures that allow to prove and improve data validity at every step of the decision making process. Read more.