Description

This is a two-day specialty course that deep dives into Advanced Big Data services of AWS and enhances knowledge of AWS data services. This training is focused towards “AWS Big Data – Specialty” Certification, with hands-on labs for simulation of Hybrid Cloud Environment. AWS Big Data services will be a great utility to companies who are trying to move Big Data platform to the Cloud.

Highlights of this course:

• This course is for individuals who perform complex data analytical tasks
• All instructors for this course are AWS Certified Professionals and have vast knowledge and experience in this field
• This training includes implementation of core AWS data services according to the basic architectural best practices and ways to leverage tools to automate AWS data related tasks

Objectives

• To gain deep understanding of AWS Big Data technologies
• Design and implement Big Data solutions with AWS
• Choose appropriate AWS data storage / processing options
• Leverage various AWS services to automate data analysis
• Use AWS Glue to automate extract, transform, and load (ETL) workloads
• Be able to understand various stages of data lifecycle management
• Be able to understand Data security, cost and performance objectives
• Be able to understand various real-time use cases, best practise and design patterns

Who Should Attend

• Solutions Architects
• Data Analysts
• SysOps Administrators
• Data Scientists

Prerequisites

• Should have attended AWS Level-2 course and AWS Level – 3 Course offered by CloudThat Technologies
• Should have basic understanding of Big Data technologies
• Should have basic understanding of databases

Course Outline

Day 1

• Amazon Kinesis
  • Overview of Kinesis and Real-Time Analytics
  • Amazon Kinesis Capabilities
  • Kinesis Data Streams
  • Kinesis Data Firehose
  • Kinesis Data Analytics
  • Data Analytics – Batch V/S Realtime
  • Monitoring Streams

  Hands-on: Reading and Writing Data to Kinesis

• Simple Queue Service
  • Need for Queues
  • SQS APIs
  • Workflow Designs on Top of SQS
  • SQS Guarantees and Limitations
  • Messages Receiving Order
  • Distributed Queues
  • Dead Letter Queue
  • Message Lifecycle
  • Integration with SNS
  • Need for Queues
  • SQS VS Kinesis

  Use Cases of SQS

• Amazon EMR
  • Overview and Benefits of EMR
  • EMR Architecture
  • Data Processing Frameworks for EMR
  • Analyzing Big Data with EMR
  • AWS data Storage Options
  • In-memory Analytics with Apache Spark on Amazon EMR
  • Cluster Configuration
  • Storage
  • Configure Cluster Software, Custom AMI, Tagging
  • Monitoring
  • EMR Security

  Hands-on: Analysing Big Data with EMR Cluster (spark)

• Database Migration Service (DMS)
  • Introduction
  • Components of DMS
  • Homogenous & Heterogeneous Migration
  • Monitoring DMS Tasks
  • Migration Validation

  Demo: DMS (Migration and Ongoing Replication of MySql Database)

Day 2

• Amazon Redshift
  • Introduction to Data Warehousing
  • Redshift Data Warehouse System Architecture
  • Internal Architecture and System Operation
  • Redshift Performance
  • Workload Management
  • Redshift Best Practices
  • Working with Recommendations from Redshift Advisor
  • Managing Database Security
  • Creating User-Defined Functions
  • Moving Data Between Amazon Redshift and S3
  • Loading Data with the COPY command

  Hands-on: Create Redshift Database, Export Data From S3 to Redshift and Data Analysis

• Amazon Redshift Spectrum
  • Redshift Spectrum Overview
  • External Schemas
  • External Tables
  • Monitoring Metrics in Amazon Redshift Spectrum
  • Spectrum Query Performance

  Demo: Amazon Redshift Spectrum

• Amazon Athena
  • Athena Overview
  • Understanding Athena Data Catalog
  • Accessing Amazon Athena
  • Best Practices When Using Athena with AWS Glue
  • Working with Source Data
  • Connecting to Athena with ODBC and JDBC Drivers
  • Security
  • Data Querying

  Use Case Study and Lab Querying Data in Amazon Athena Tables

• Amazon Glue
  • ETL/ELT Overview
  • ETL Design Principles
  • Overview of Amazon Glue
  • Glue Terminology and Components
  • Glue Console Workflow Overview
  • Authentication and Access Control for AWS Glue
  • Running and Monitoring AWS Glue
  • Authoring Jobs in AWS Glue
  • Programming ETL Scripts
• Amazon QuickSight
  • QuickSight overview
  • Working with Data Sources in Amazon QuickSight
  • Working with Data Sets
  • Table and Query Limits
  • Working with Analyses
  • Working with Dashboards
  • Publishing a Dashboard
• Data Pipeline
  • Data Nodes
  • Activities
  • Schedules
  • Pipeline Lifecycle
• Security on AWS
  • AWS KMS
  • DDOS protection: AWS WAF and Shield
  • Inspector
  • GuardDuty

  Discussion on Whitepapers

• Other Services Used in Bigdata Specialty Course
  • Elasticsearch
  • AML
  • Amazon SageMaker
  • AWS Snowball and Snowmobile

About The Trainer

The trainer will be a certified AWS Professional

Other Details

Questions?

For latest batch dates, fees, location, technical queries and general inquiries, contact our sales team at: +91 8880002200 or email at sales@cloudthat.in