Past Meetup

Big Data App Meetup 11/09

This Meetup is past

155 people went

Details

Shoutout to Cask (http://cask.co/) for kindly sponsoring and hosting this meetup!

Cask will also be giving away a Raspberry Pi 3 Starter Kit. Enter the raffle on the day of the event for a chance to win.

AGENDA

6:00 - 6:30 - Socialize over food and beer(s)

6:30 - 8:00 - Talks

TALKS

Talk #1: Peeling the onion: How data abstraction helps building big data applications, by Andreas Neumann, Cask

Talk #2: Big Data and Analytics in the Cloud, by Ryan Lippert, Cloudera

Talk #3: Designing Modern Data Pipelines with Apache Kafka, by Gwen Shapira, Confluent

ABSTRACTS

• Talk #1: Peeling the onion: How data abstraction helps building big data applications, by Andreas Neumann, Cask

Data abstractions have many benefits: They keep application code free from the details of how data is stored; they make applications portable between different environments and storage engines; they provide data access patterns that are reusable across applications; and they allow injection of enterprise-grade production capabilities, such as security and data lineage, at a platform level. This talk will illustrate the various levels of data abstractions with examples taken from the Cask Data Application Platform (CDAP).

• Talk #2: Big Data and Analytics in the Cloud, by Ryan Lippert, Cloudera

Cloud is a key component of the future of big data. In this talk, we’ll discuss current and future considerations for deploying big data within the cloud, including major public cloud vendors, the on-prem vs. cloud tradeoffs, and the advantages of portability and hybrid models. Ryan will present example use cases for AWS and Azure.

• Talk #3: Designing Modern Data Pipelines with Apache Kafka, by Gwen Shapira, Confluent

Modern data pipelines are real-time, flexible, reliable and scalable. Over years of building these pipelines, we recognized several design patterns required for implementing them successfully. In this session, we will introduce these patterns, show how to implement them using Apache Kafka and explain the benefits of building data architectures with Kafka at their core.

SPEAKER BIOS

• Andreas Neumann (@caskoid), Chief Architect, develops big data software at Cask and has previously done so at places that are known for massive scale. Prior to Cask, he was Chief Architect for Hadoop at Yahoo!, and previously he was a research engineer at Yahoo! and a search architect at IBM.

• Ryan Lippert (@lippertryan) is a Senior Product Marketing Manager at Cloudera. In this role, he is responsible for communicating the transformative value of Cloudera’s industry-leading Big Data platform to the market. Prior to Cloudera, he held a variety of roles at Cisco Systems. He holds an economics/finance degree from the University of Guelph and an MBA from Stanford.

• Gwen Shapira (@gwenshap) is a system architect at Confluent helping customers achieve success with their Apache Kafka implementation. She has 15 years of experience working with code and customers to build scalable data architectures, integrating relational and big data technologies. She currently specializes in building real-time reliable data processing pipelines using Apache Kafka. Gwen is an author of "Kafka - The Definitive Guide," a PMC member on the Apache Kafka project and a frequent presenter at industry conferences. When Gwen isn't coding or building data pipelines, you can find her pedaling on her bike exploring the roads and trails of California, and beyond.

ARRIVAL AND PARKING

Cask HQ is a few minutes walk from the California Avenue Caltrain Station.

Also, Cask HQ has its own parking lot, but it will certainly not accommodate all guests. Please use parking lots available nearby: