Presented By O'Reilly and Cloudera
Make Data Work
March 28–29, 2016: Training
March 29–31, 2016: Conference
San Jose, CA

Office Hours conference sessions

Office Hours gives you a chance to meet face-to-face in a small group setting with expert Strata + Hadoop World presenters. Discuss the speaker’s area of expertise, give feedback about their sessions, or ask questions.

Sign-up now by adding it to your personal schedule. Seating is limited.

Office Hours will take place in the Expo Hall.

    Wednesday, March 30

    11:00am–11:40am Wednesday, 03/30/2016
    Location: Table A (O'Reilly Booth)
    Stephen Elston (Quantia Analytics, LLC)
    Come talk with Stephen about R topics like scaling R for the exploration and analysis of large, complex datasets, using R with MapReduce methods on parallel backends, such as Hadoop or Spark, and visualization of large, complex datasets with R. Read more.
    11:00am–11:40am Wednesday, 03/30/2016
    Location: Table B (O'Reilly Booth)
    Ben Sharma (Zaloni)
    If you’re interested in next-generation data architectures and Hadoop big data lakes, your time with Ben could be very productive. He’ll answer questions about deploying a hybrid Hadoop architecture, the benefits and challenges associated with the cloud for big data management, and how to overcome governance, security, and metadata challenges associated with data lakes. Read more.
    11:50am–12:30pm Wednesday, 03/30/2016
    Location: Table A (O'Reilly Booth)
    Tags: real-time
    Jay Kreps (Confluent)
    Working with distributed streaming data architectures? Jay is available to answer all your questions about Apache Kafka, stream processing and streaming data architectures, and Confluent and the Confluent platform. Read more.
    11:50am–12:30pm Wednesday, 03/30/2016
    Location: Table B (O'Reilly Booth)
    Tags: real-time
    Patrick McFadin (DataStax)
    Average rating: *****
    (5.00, 1 rating)
    Have some questions about using Apache Cassandra on your next project? Patrick will be around to talk about the following: data modeling for specific use cases, using Apache Spark with Cassandra data, and deployment and operation topics. Read more.
    1:50pm–2:30pm Wednesday, 03/30/2016
    Location: Table A (O'Reilly Booth)
    Jake Porway (DataKind)
    If you're already solving tough social issues—or just want to see how you can make a difference—stop by to chat with Jake about how data science is being applied to tackle tough social issues, DataKind's five principles for designing data science for social good projects, and how you can join thousands of other data scientists donating your skills for the greater good. Read more.
    1:50pm–2:30pm Wednesday, 03/30/2016
    Location: Table B (O'Reilly Booth)
    Tags: ai
    Eric Colson (Stitch Fix)
    Average rating: *****
    (5.00, 1 rating)
    Stop by to talk to Eric about the (current) limits to machine learning and find out when you should include a human in the loop, how to set up an organization to leverage both machine-learning and human-learning algorithms, how to gain insights into human decision making, and the various domains where machines and humans can be combined to produce new capabilities and value. Read more.
    2:40pm–3:20pm Wednesday, 03/30/2016
    Location: Table A (O'Reilly Booth)
    Tags: real-time
    Jesse Anderson (Big Data Institute)
    If you are a manager or CxO about to launch a big data project, come see Jesse. He’ll offer advice on how to create successful data projects, the patterns of successful data engineering teams and projects, and how to avoid the most common—and costly—pitfalls of a large Hadoop deployment. Read more.
    2:40pm–3:20pm Wednesday, 03/30/2016
    Location: Table B (O'Reilly Booth)
    Thomas Phelan (BlueData)
    Average rating: *****
    (5.00, 1 rating)
    Looking at Hadoop in the cloud? Tom can answer your questions about running Hadoop or Spark in Docker containers, compute and storage separation for Hadoop, and big data as a service (BDaaS) in an on-premises deployment. Read more.
    3:30pm–4:10pm Wednesday, 03/30/2016
    Location: Table A (O'Reilly Booth)
    Christopher Nguyen (Arimo), Anh Trinh (Arimo, Inc.)
    Christopher and Anh are happy to answer questions about Distributed DataFrame (The DDF Project), visual DDFs and their role in collaborative data visualization, and distributed deep learning on Spark/DDF. Read more.
    3:30pm–4:10pm Wednesday, 03/30/2016
    Location: Table B (O'Reilly Booth)
    Robert Grossman (University of Chicago)
    Interested in moving machine learning and predictive analytics to operational environments? Stop by to talk with Robert. He’ll answer questions about how to avoid the common problems around deploying solutions in operations, integrating DevOps with analytic operations (AnalyticOps), or any questions that you may have about his session. Read more.
    4:20pm–5:00pm Wednesday, 03/30/2016
    Location: Table A (O'Reilly Booth)
    Rajat Monga (Google), Amy Unruh (Google), Kaz Sato (Google)
    Googlers Rajat, Amy, and Kazunori can answer all your TensorFlow questions, including how to use TensorFlow to utilize interactive queries on petabyte-sized datasets, empower large-scale distributed training of neural networks, and train and deploy machine-learning models. Read more.

    Thursday, March 31

    11:00am–11:40am Thursday, 03/31/2016
    Location: Table A (O'Reilly Booth)
    Ted Dunning (MapR)
    If you have questions about streaming data architectures, come see Ted. He’ll talk about things like the differences between state-oriented and flow-oriented systems, why streaming is critical, and how to practically apply modern streaming architectures to your problems. Read more.
    11:00am–11:40am Thursday, 03/31/2016
    Location: Table B (O'Reilly Booth)
    Tags: real-time
    Dean Wampler (Lightbend)
    If you’re using (or considering) Scala and JVM as a big data platform, Dean can answer all your questions about Spark, Mesos, and fast data. Read more.
    11:50am–12:30pm Thursday, 03/31/2016
    Location: Table A (O'Reilly Booth)
    Donald Miner (Miner & Kasch)
    Need answers to enterprise-level problems? Donald is happy to talk about modern enterprise data architecture (with Hadoop in mind), successful (and unsuccessful) enterprise adoption of Hadoop, and migrating from older RDBMS and data systems to Hadoop. Read more.
    11:50am–12:30pm Thursday, 03/31/2016
    Location: Table B (O'Reilly Booth)
    Fangjin Yang (Imply)
    Fangjin is coauthor of the open source Druid project, so he's in a unique position to help you with all your questions about architecting distributed databases for scale, Druid, or streaming architecture. Read more.
    1:50pm–2:30pm Thursday, 03/31/2016
    Location: Table A (O'Reilly Booth)
    Holden Karau (Google)
    If you’re interested in testing and validating Spark programs, you need to talk to Holden. She’ll answer your questions about things like high-performance Spark, using Spark with non-JVM languages (e.g., Python), and contributing to Spark. Read more.
    1:50pm–2:30pm Thursday, 03/31/2016
    Location: Table B (O'Reilly Booth)
    Travis Oliphant (Continuum Analytics)
    Are you integrating Python with Hadoop and Spark in production-deployment environments? Travis is your man. He’ll answer questions about common antipatterns in Python scalabilty; NumPy, SciPy, pandas, or other Python packages; and Hadoop and Spark, Numba, Bokeh, Blaze, and Dask. Read more.