Architecting Big Data solutions with AWS

Learn how to move from your on premise data center to AWS Cloud for leveraging its enterprise wide useful services. Learn how to use these services and how they fit in various Big data use cases. The course covers right from setting up the infrastructure to analysing data using AWS services.

Instructed by Abhishek Sinha

$ 19/ month $ 799
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  • The student will learn how to solve business critical problems related to Big Data implementations at various enterprises. They will learn how to use AWS services and similar cloud offerings to modernize any enterprise big data implementation.

The goal of this course is to learn, understand and compare the various components of an on-premise Big Data platform vs various AWS Services. You will also learn how to replicate them using AWS services over cloud.

 

In this course we will take a baseline of an on-premise Enterprise Analytics Platform Architecture for our reference and then we shall compare all the components with individual Amazon Web Services.

 

We will also demonstrate the various services and how to utilize them in our present environment. During the course we will take up some of the case studies. Course will also touch upon the best practices followed on AWS architecture principles.

  • The student must be familiar with the basic cloud concepts. Good to have AWS understanding and its basic services.
  • This course is intended for the audience who wants to understand the concepts on how to architect solutions for Big Data analytics problems using AWS as a platform. The course will focus on the various important AWS services that can be used to solve various enterpise level problems which an architect faces while building a solution for an enterprise. The focus will be to compare the on-premise and AWS platforms and try to build a solutions using AWS services.
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Section 1 : Introduction

  • Lecture 1 :
  • Introduction to the course and about the instrcutor. This lecture will set the path and expectation from the course. The intended audiance of this course are professionals , students and practitioners of Big Data and AWS services. The need of this course occured in my mind when I went out to search for an enterprise level architecting solutions of EAP on AWS platform. The content that I have found out on various platforms and articles were not sufficient to buil an understanding on how to build an AWS based EAP. This would be an evolving course and I will keep on updating the content of this course as in when I receive more content on the related topics or on requests from the subscribers. In case any of you think that you need more explanation on any of the published topics, you can write to me and I will be happy to add more content on the same. I will also be happy to recieve feedback on the course and would be more than happy to add/edit the contents that require more explanation. Please provide your valuable feedback as this is my first course on any learning platform and I hope to improve my content with your valuable feedback. Thank you! Please add my professional networking site and share yourfeedback on it. https://www.linkedin.com/theabhisheksinha

Section 2 : Agenda

  • Lecture 1 :
  • Agenda
  • Lecture 2 :
  • What will you learn.mp4

Section 3 : Introduction to Big Data and Enterprise Analytics

  • Lecture 1 :
  • What is Enterprise Analytics ?
  • Lecture 2 :
  • What is Big Data?
  • Lecture 3 :
  • Types and benefits
  • Lecture 4 :
  • Why Big Data?
  • Lecture 5 :
  • What is Hadoop?
  • Lecture 6 :
  • What is EAP?
  • Lecture 7 :
  • Choosing EAP Software for an enterprise
  • Lecture 8 :
  • Baseline reference Architecture
  • Lecture 9 :
  • Why AWS?

Section 4 : Security, Compliance and Auditing

  • Lecture 1 :
  • AWS IAM
  • Lecture 2 :
  • IAM best practices

Section 5 : Cluster Monitor and Event Management

  • Lecture 1 :
  • AWS CloudWatch
  • Lecture 2 :
  • AWS Auto Scaling
  • Lecture 3 :
  • CloudFormation
  • Lecture 4 :
  • AWS CloudTrail
  • Lecture 5 :
  • AWS Config
  • Lecture 6 :
  • AWS OPsWorks
  • Lecture 7 :
  • AWS Service Catalog
  • Lecture 8 :
  • AWS System Manager
  • Lecture 9 :
  • AWS Trusted Advisor

Section 6 : Backup and Disaster Recovery [DR]

  • Lecture 1 :
  • AWS S3
  • Lecture 2 :
  • AWS Glacier
  • Lecture 3 :
  • AWS EBS
  • Lecture 4 :
  • AWS EFS
  • Lecture 5 :
  • AWS Storage Gateway

Section 7 : Hardware and OS

  • Lecture 1 :
  • AWS EC2
  • Lecture 2 :
  • AWS Lambda
  • Lecture 3 :
  • AWS Batch

Section 8 : AWS EMR

  • Lecture 1 :
  • AWS EMR
  • Lecture 2 :
  • EMR :: Demo

Section 9 : WorkFlow and Scheduling

  • Lecture 1 :
  • AWS SWF
  • Lecture 2 :
  • AWS SNS
  • Lecture 3 :
  • AWS SQS

Section 10 : AWS Data Lake

  • Lecture 1 :
  • What is AWS DataLake?
  • Lecture 2 :
  • DataLake Formation

Section 11 : AWS Data Analytics Tools and Services

  • Lecture 1 :
  • AWS Athena
  • Lecture 2 :
  • Demo :: Athena
  • Lecture 3 :
  • AWS CloudSearch
  • Lecture 4 :
  • AWS ElasticSearch
  • Lecture 5 :
  • Amazon Kenisis
  • Lecture 6 :
  • AWS Managed Streaming for Kafka
  • Lecture 7 :
  • AWS RedShift
  • Lecture 8 :
  • AWS QuickSight
  • Lecture 9 :
  • Demo :: QuickSight
  • Lecture 10 :
  • AWS Glue

Section 12 : Conclusion

  • Lecture 1 :
  • Big Data Solutions with AWS Services
  • Lecture 2 :
  • Thank you!

Abhishek Sinha,

A seasoned IT profession who is currently working as a Technical Pre-Sales manager at one of the Software intelligence product company. He has around 15 years of work experience in IT product and services organizations. He has worked majorly with Telecommunications ,Banking and Pharma clients across India, US, Europe and Latin America. He has had the opportunity to architect and present Hadoop/Big Data and Cloud based solutions. Prior to joining CAST he was working with Happiest Minds Technologies for the past 5 years as a Solutions Architect and was responsible for delivering customer requirements for Big Data Analytics, CRM/Business Support System [BSS] applications. He is a certified TOGAF 9.1 EA professional along with many other technical certifications. He has been working on various Cloud platforms viz AWS, GCP and Azure for the customer application migration and Big Data implementations.
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