SOLD OUT: Building a serverless big data application on AWS

Jorge Lopez (Amazon Web Services), Radhika Ravirala (Amazon Web Services), Nikki Rouda (Amazon Web Services), Jesse Gebhardt (Amazon Web Services), Rajeev Chakrabarti (Amazon Web Services)

9:00am—5:00pm Monday, September 23—Tuesday, September 24

Location: 1A 17

Data Engineering and Architecture

Secondary topics: Cloud Platforms and SaaS, Data Integration and Data Processing, Data, Analytics, and AI Architecture, Deep dive into specific tools, platforms, or frameworks

SOLD OUT

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Participants should plan to attend both days of training course. Note: to attend training courses, you must be registered for a Platinum or Training pass; does not include access to tutorials on Tuesday.

Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. Join the AWS team to learn how to incorporate serverless concepts into your big data architectures. You'll explore design patterns to ingest, store, and analyze your data as you build a big data application using AWS technologies such as S3, Athena, Kinesis, and more.

What you'll learn, and how you can apply it

Understand serverless concepts and best practices for designing serverless analytic applications
Explore design patterns for ingesting, collecting, storing, analyzing, and visualizing big data
Learn how to build a serverless data pipeline using technologies such as Amazon S3, Amazon Athena, Amazon Kinesis, AWS Glue, AWS Lambda, and Amazon QuickSight

Who is this presentation for?

You're a big data architect.
You're a data analytics professional.
You're a data scientist.

Level

Intermediate

Prerequisites:

A basic understanding of Amazon Web Services concepts
Experience using AWS tools (useful but not required)

Hardware and/or installation requirements:

A laptop

Outline

Intro to big data on AWS
Serverless concepts and design patterns
Data collection and storage, including streaming data
Preparing your data for analytics: Data transformations and ETL patterns
Querying your data
Visualizing data

About your instructors

Jorge A. Lopez works in big data solutions at Amazon Web Services. Jorge has more than 15 years of business intelligence and DI experience. He enjoys intelligent design and engaging storytelling and is passionate about data, music, and nature.

Radhika Ravirala is a solutions architect at Amazon Web Services, where she helps customers craft
distributed big data applications on the AWS platform. Previously, she was a software engineer and designer for technology companies in Silicon Valley. She holds an MS in computer science from San Jose State University.

Nikki Rouda is a principal product marketing manager at Amazon Web Services (AWS). Nikki has decades of experience leading enterprise big data, analytics, and data center infrastructure initiatives. Previously, he held senior positions at Cloudera, Enterprise Strategy Group (ESG), Riverbed, NetApp, Veritas, and UK-based Alertme.com (an early consumer IoT startup). Nikki holds an MBA from Cambridge’s Judge Business School and an ScB in geophysics from Brown University.