AWS Big Data Certification Course

58,512

Huge Data preparing is the regular and mainstream utilization of cloud administrations and assets, particularly because of the need of sheer processing power. AWS (Amazon Web Services) has built up a bunch of administrations that help in the compelling usage of Big Data. This AWS accreditation for Big Data from Edutech Skills means to assist you with gaining the abilities and become capable in Big Data on AWS. In this course, you will get familiar with the fundamental just as cutting edge ideas of the field and will get confirmed.

What will you cover in this AWS Big Data training?

In this course, you will learn the following AWS and Big Data topics:

  • AWS IoT
  • Kinesis
  • AWS Snowmobile and AWS Snowball
  • Amazon Simple Storage Service (S3)
  • Processing
  • Lambda and AWS data pipeline
  • Big Data concepts and tools
  • Elasticsearch, Athena, and Redshift
  • Data visualization

What are the prerequisites to enroll in this AWS Big Data course?

To take up this course, you need to have some basic knowledge of Big Data. You also need to understand the working of Big Data on AWS, i.e., using Amazon Web Services solutions for handling Big Data.

Who can take up this online AWS certification for Big Data?

Professionals who can take up this course include:

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

Introduction to Big Data and Data Collection

  • Introduction to Big Data
  • Big Data tools available in AWS
  • Why Big Data on AWS?
  • What is AWS Kinesis?
  • How Kinesis works?
  • Features of AWS Kinesis
  • AWS Kinesis Components
  • Kinesis Data Streams
  • Enhanced Fan-Out in AWS Kinesis
  • Kinesis Data Firehose
  • Amazon SQS
  • AWS Data Pipeline

Hands-on Exercise:

Creating, Deleting, Managing an AWS Kinesis Stream.

Introduction to Cloud Computing & AWS

  • What is Cloud Computing
  • Cloud Service & Deployment Models
  • How AWS is the leader in the cloud domain
  • Various cloud computing products offered by AWS
  • Introduction to AWS S3, EC2, VPC, EBS, ELB, AMI
  • AWS architecture and the AWS Management Console, virtualization in AWS (Xen hypervisor)
  • What is auto-scaling
  • AWS EC2 best practices and cost involved.

Hands-on Exercise – Setting up of AWS account, how to launch an EC2 instance, the process of hosting a website and launching a Linux Virtual Machine using an AWS EC2 instance.

Elastic Compute and Storage Volumes

  • Introduction to EC2
  • Regions & Availability Zones(AZs)
  • Pre-EC2, EC2 instance types
  • Comparing Public IP and Elastic IP
  • Demonstrating how to launch an AWS EC2 instance
  • Introduction to AMIs, Creating and Copying an AMI
  • Introduction to EBS
  • EBS volume types
  • EBS Snapshots
  • Introduction to EFS
  • Instance tenancy- Reserved and Spot instances
  • Pricing and Design Patterns.

Hands-on Exercise –

  • Launching an EC2 instance
  • Creating an AMI of the launched instance
  • Copying the AMI to another region
  • Creating an EBS volume
  • Attaching the EBS volume with an instance
  • Taking backup of an EBS volume
  • Creating an EFS volume and mounting the EFS volume to two instances.

Virtual Private Cloud

  • What is Amazon VPC,
  • VPC as a networking layer for EC2,
  • IP address and CIDR notations,
  • Components of VPC – network interfaces, route tables, internet gateway, NAT,
  • Security in VPC – security groups and NACL, types of VPC, what is a subnet, VPC peering with scenarios, VPC endpoints, VPC pricing and design patterns.

Hands-on Exercise –

  • Creating a VPC and subnets,
  • Creating a 3 Tier architecture with security groups,
  • NACL, Internet gateway and NAT gateway,
  • Creating a complete VPC architecture.

Storage – Simple Storage Service (S3)

  • Introduction to AWS storage
  • Pre-S3 – online cloud storage
  • API, S3 consistency models
  • Storage hierarchy, buckets in S3
  • Objects in S3, metadata and storage classes, object versioning, object lifecycle management, cross-region replication, data encryption, connecting using VPC endpoint, S3 pricing.

Hands-on Exercise –

  • Creating an S3 bucket
  • Uploading objects to the S3 bucket
  • Enabling object versioning in the S3 bucket
  • Setting up lifecycle management for only a few objects
  • Setting up lifecycle management for all objects with the same tag
  • Static website hosting using S3.

Databases and In-Memory Data Stores

  • What is a database, types of databases, databases on AWS
  • Introduction to Amazon RDS
  • Multi-AZ deployments, features of RDS
  • Read replicas in RDS, reserved DB instances
  • RDS pricing and design patterns
  • Introduction to Amazon Aurora, benefits of Aurora, Aurora pricing and design patterns
  • Introduction to DynamoDB, components of DynamoDB, DynamoDB pricing and design patterns
  • What is Amazon Redshift, advantages of Redshift
  • What is ElastiCache, why ElastiCache.

Hands-on Exercise –

  • Launching a MySQL RDS instance
  • Modifying an RDS instance
  • Connecting to the DB instance from your machine
  • Creating a multi-az deployment
  • Create an Aurora DB cluster
  • Creating an Aurora replica
  • Creating a DynamoDB table.

Data Storage

  • What is S3 Glacier?
  • Accessing Amazon S3 Glacier
  • Glacier Vaults
  • Glacier Archives
  • What is Amazon DynamoDB?
  • How does DynamoDB work?
  • Accessing DynamoDB through Portal and CLI
  • DynamoDB Tables and Items
  • DynamoDB Indexes
  • DynamoDB Streams and Replication
  • Dynamo Backup and Restore
  • DynamoDB Best Practices
  • Introduction to RDS
  • Basics of RDS

Hands-on Exercise:

Creating a table and loading data, Replicating data to another table and backing up, Creating a MySQL database.

Data Processing

  • Amazon EMR
  • Apache Hadoop
  • Hue with EMR
  • HBase with EMR
  • Spark with EMR
  • AWS Lambda for Big Data Ecosystem
  • Hcatalog
  • Glue
  • Glue Lab

Hands-on Exercise:

EMR Cluster creation, Adding steps to EMR, Using Hue with EMR, Using HBase with EMR, Using Spark with EMR, Using HCatalog with Hive on EMR, Using Glue.

Data Analysis

  • What is Amazon Redshift?
  • Data Warehouse System Architecture
  • Redshift Concepts
  • Designing tables
  • Loading Data to Redshift
  • Redshift Workload Management
  • Tuning Query Performance
  • Best Practices using Redshift
  • Amazon Machine Learning
  • Amazon ML Key Concepts
  • Using Amazon ML
  • What is Amazon Athena?
  • When should you use Athena?
  • Running Queries using Athena
  • What Is Amazon Elasticsearch Service?
  • Features of Amazon Elasticsearch Service
  • ES Domains

Hands-on Exercise:

Creating a Redshift Cluster, Creating Read Replicas,  Loading data into the cluster, Running queries using the Redshift Query Editor, Backing up the cluster, Running a sample ML model in Amazon ML, Creating a database in Athena and running queries.

Data Visualization and Data Security

  • What is Amazon QuickSight?
  • How does Amazon QuickSight work?
  • QuickSight SPICE
  • Setting up Amazon QuickSight
  • Data Sources and Data Sets
  • Creating your own Analysis in QuickSight
  • QuickSight Visualization
  • QuickSight Dashboards
  • Security Best Practices
  • EMR Security
  • Redshift Security
  • Introduction to Microstrategy

Hands-on Exercise:

Setting up Amazon QuickSight, Creating a Data Set in QuickSight, Creating various Visualizations using the data set, Creating a QuickSight dashboard of the created visuals.