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AWS Big Data – Specialty Certification BootCamp

Amazon Web Services

Duration: 2 Days

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
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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

Upcoming Batches

Bangalore Enroll
  • 7 Sep, 2019 - 8 Sep, 2019 (Sat - Sun)
  • Quick Inquiry: AWS Courses


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