Amazon Web Services for Data Science

with Lynn Langit
online class - 2016

Learn what you need to know to implement cloud-based big data solutions using the right mix of Amazon Web Services- from big data and cloud architect and AWS community hero Lynn Langit. Starting with top-level categories of storage, data, computer, and services, Lynn guides you through planning your ideal AWS architecture, providing service demos using the AWS Console, command-line interface, and other tools. Learn when to use which service for which business case, such as Docker or Lambda or DynamoDB or Aurora? She shows how to script creation of services such as S3 buckets and EC2 instances, create and populate a managed data warehouse, and develop a data processing pipeline that works for you. Chapter 6 covers the AWS Internet of Things (IoT) services. These exercises can help you build proof-of-concepts, minimum viable products, and deployable solutions to scale and support big data initiatives at your company.

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Bibliographic Details
Corporate Author: Lynda.com (Firm)
Other Authors: Langit, Lynn (Speaker)
Format: Electronic Video
Language:English
Published: Carpenteria, CA lynda.com, 2016.
Subjects:
Online Access:Click here for information and access to this online class.

MARC

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520 |a Learn what you need to know to implement cloud-based big data solutions using the right mix of Amazon Web Services- from big data and cloud architect and AWS community hero Lynn Langit. Starting with top-level categories of storage, data, computer, and services, Lynn guides you through planning your ideal AWS architecture, providing service demos using the AWS Console, command-line interface, and other tools. Learn when to use which service for which business case, such as Docker or Lambda or DynamoDB or Aurora? She shows how to script creation of services such as S3 buckets and EC2 instances, create and populate a managed data warehouse, and develop a data processing pipeline that works for you. Chapter 6 covers the AWS Internet of Things (IoT) services. These exercises can help you build proof-of-concepts, minimum viable products, and deployable solutions to scale and support big data initiatives at your company. 
520 |a Learn what you need to know to implement cloud-based big data solutions using the right mix of Amazon Web Serviceśfrom big data and cloud architect and AWS community hero Lynn Langit. Starting with top-level categories of storage, data, computer, and services, Lynn guides you through planning your ideal AWS architecture, providing service demos using the AWS Console, command-line interface, and other tools. Learn when to use which service for which business case, such as Docker or Lambda or DynamoDB or Aurora? She shows how to script creation of services such as S3 buckets and EC2 instances, create and populate a managed data warehouse, and develop a data processing pipeline that works for you. Chapter 6 covers the AWS Internet of Things (IoT) services. These exercises can help you build proof-of-concepts, minimum viable products, and deployable solutions to scale and support big data initiatives at your company. 
500 0 |a 07/18/2016 
511 |a Presenter: Lynn Langit. ["a", "Founder of her own consulting firm, Lynn Langit creates big data and cloud architectures using Amazon Web Services (AWS), Microsoft, Google, and OpenStack technologies. She also works with SQL Server, MongoDB, Google Big Query, Redis, Neo4j, and Hadoop. Lynn is also the cofounder of Teaching Kids Programming, and has spoken on data and cloud technologies in many countries. She is an ACM Distinguished Speaker."] 
520 |a Learn what you need to know to implement cloud-based big data solutions using the right mix of Amazon Web Services. 
520 |a Learn what you need to know to implement cloud-based big data solutions using the right mix of Amazon Web Serviceśfrom big data and cloud architect and AWS community hero Lynn Langit. Starting with top-level categories of storage, data, computer, and services, Lynn guides you through planning your ideal AWS architecture, providing service demos using the AWS Console, command-line interface, and other tools. Learn when to use which service for which business case, such as Docker or Lambda or DynamoDB or Aurora? She shows how to script creation of services such as S3 buckets and EC2 instances, create and populate a managed data warehouse, and develop a data processing pipeline that works for you. Chapter 6 covers the AWS Internet of Things (IoT) services. These exercises can help you build proof-of-concepts, minimum viable products, and deployable solutions to scale and support big data initiatives at your company. 
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