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Beyond Relational: Applying Big Data Cloud Pipeline Patterns

YOW! Data 2017 - 15 Sep

In this full-day workshop, you will learn applied big data solution patterns. most often, but not always using the public cloud. We’ll cover Amazon Web Services and Google Cloud Platform, and work with in small groups to design data pipeline architectures for common scenarios.

RESERVE YOUR SEAT NOW

Lynn Langit

Big Data and Cloud Architect

Lynn Langit Consulting

United States

Lynn Langit is an independent software architect and educator. She is an AWS Community Hero, Google Cloud Developer Expert, Microsoft MVP and technical author for LinkedIn Learning. She has most recently worked as a lead architect on AWS IoT Enterprise project where she applied Mob Programming.

Lynn is also Director & Lead Courseware Author for “Teaching Kids Programming”. She has 8 years experience authoring technical courseware for middle school kids and has been a key contributor to TKPJava courseware library with 70+ open source kids coding lessons.

Workshop Details

Target Audience
Data engineers, software engineers, architects, technical leaders and anyone interested in understanding the merging patterns and technologies in the big data space.
Level
Intermediate
Duration
Full day

Learning Outcomes

Big Data solution patterns and pipeline architectures.

Approaches using Amazon Web Services and Google Cloud Platform.

Workshop Outline

In this workshop we will discuss database categories, products and understand actual cost to use one or more database types in your solution(s).

Using combinations of Big Relational (for hot, cold or cold data), and one or more types from the NoSQL category (Key-value, Wide-column, Document or Graph) and sometimes even along with NewSQL, we will design implementable solutions.

We will also cover what types of problems are best suited to the Hadoop ecosystem (including use of Spark and the associated libraries).

Prerequisites

Attendees will need to bring a suitable development laptop for working through the exercises.