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AWS Big Data Certification Training

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The AWS Big Data certification training prepares you for all aspects of hosting big data and performing distributed processing on the AWS platform and has been aligned to the AWS Certified Data Analytics – Specialty exam. This course is developed by industry leaders and aligned with the latest best practices.
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Eligibility & Pre-requisites

  • Eligibility

    This AWS Big Data certification course is well-suited for experienced technology professionals who want to excel in the data engineering space.

  • Pre-requisites

    Participants in this AWS Big Data certification course should have basic knowledge of AWS technical essentials and a fair understanding of big data and Hadoop concepts.

AWS Big Data Training Overview

In this AWS Big Data certification course, you will become familiar with the concepts of cloud computing and its deployment models. This course covers Amazon’s AWS cloud platform, Kinesis Analytics, AWS big data storage, processing, analysis, visualization and security services, machine learning algorithms and much more.

Benefits

Worldwide revenues for Big Data and Business Analytics solutions will reach $260 billion in 2022 with a CAGR of 11.9% as per International Data Corporation (IDC)

Average Salary of Big Data Hadoop Developers is $135,000 (Indeed.com salary data)

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      Skills Covered​

      AWS Quicksight
      Kinesis streams
      AWS Lambda and Glue
      s3 and DynamoDB
      Redshift
      Amazon RDS
      Hive on EMR
      HBase with EMR
      AWS Aurora

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      • 2000 Step-by-Step Screenshots, SAP Books
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      • Professional Resume
      • Intense Interview Preparation
      • Linkedin Preparation
      • Free 6 Months On-the-Job Support

      One-on-One (Recommended)

      (Online, In-Class)​
      • EVERYTHING OF BATCHES PLUS...
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      • Access to Realtime Project Documents as Samples
      • Access to Exclusive VoiSAP Practice Guides

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      • Simulation test papers for self-assessment
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      Course Currilcum

      Section 1 Big Data on AWS Certification Course Overview
      • Overview of Big Data on AWS Certification Course
        04:22
      • 2.Course Introduction
        02:39
      Section 2 Big Data on AWS Introduction
      • 1. Learning Objective
        00:53
      • 2.Cloud computing and it’s advantages
        03:29
      • 3.Cloud Computing Models
        05:02
      • 4.Cloud Service Categories
        04:18
      • 5. AWS Cloud Platform
        03:54
      • 6.Design Principles – Part One
        04:16
      • 7. Design Principles – Part Two
        03:57
      • 8.Why AWS for Big Data – Reasons and Challenges
        01:48
      • 9.Databases in AWS
        06:47
      • 10.Data Warehousing in AWS
        02:00
      • 11.Redshift, Kinesis and EMR
        05:33
      • 12.DynamoDB, Machine Learning and Lambda
        05:01
      • 13.Elastic Search Services and EC2
        02:51
      • 14.Key Takeaways
        00:34
      Section 3 AWS Big Data Collection Services
      • 1.Learning Objective
        00:54
      • 2.Amazon Kinesis and Kinesis Stream
        02:42
      • 3.Kinesis Data Stream Architecture and Core Components
        04:01
      • 4.Data Producer
        04:45
      • 5.Data Consumer
        03:11
      • 6.Kinesis Stream Emitting Data to AWS Services and Kinesis Connector Library
        04:30
      • 7.Kinesis Firehose
        06:20
      • 8.Transferring Data Using Lambda
        04:35
      • 9.Amazon SQS, Lifecycle and Architecture
        06:25
      • 10.IoT and Big Data
        03:25
      • 11.IoT Framework
        04:21
      • 12.AWS Data Pipelines and Data Nodes
        05:08
      • 13.Activity, Pre-condition and Schedule
        02:47
      • 14Key Takeaways
        00:44
      Section 4 AWS Big Data Storage Services
      • 1.Learning Objective
        00:33
      • 2.Amazon Glacier and Big Data
        03:49
      • 3.DynamoDB Introduction
        05:41
      • 4.DynamoDB and EMR
        01:41
      • 5.DynamoDB Partitions and Distributions
        04:08
      • 6.DynamoDB GSI LSI
        02:55
      • 7.DynamoDB Stream and Cross Region Replication
        04:06
      • 8.DynamoDB Performance and Partition Key Selection
        03:24
      • 9.Snowball and AWS Big Data
        01:14
      • 10.AWS DMS
        01:23
      • 11.AWS Aurora in Big Data
        03:24
      • 12.Demo – Amazon Athena Interactive SQL Queries for Data in Amazon S3 – Part 2
        03:59
      • 13.Key Takeaways
        00:34
      Section 5 AWS Big Data Processing Services
      • 1.Learning Objective
        00:42
      • 2.Amazon EMR
        03:41
      • 3.Apache Hadoop
        04:10
      • 4.EMR Architecture
        06:53
      • 5.EMR Releases and Cluster
        02:12
      • 6.Choosing Instance and Monitoring
        06:07
      • 7.Demo – Advance EMR Setting Options
        03:30
      • 8.Hive on EMR
        01:06
      • 9.HBase with EMR
        05:50
      • 10.Presto with EMR
        02:07
      • 11.Spark with EMR
        06:12
      • 12.EMR File Storage
        02:48
      • 13.AWS Lambda
        03:49
      • 14.Key Takeaways
        00:32
      Section 6 Analysis
      • 1.Learning Objective
        00:44
      • 2.Redshift Intro and Use cases
        03:02
      • 3.Redshift Architecture
        06:17
      • 4.MPP and Redshift in AWS Eco-System
        05:13
      • 5.Columnar Databases
        03:37
      • 6.Redshift Table Design – Part 2
        05:06
      • 7.Demo – Redshift Maintenance and Operations
        01:44
      • 8.Machine Learning Introduction
        04:02
      • 9.Machine Learning Algorithm
        04:09
      • 10.Amazon SageMaker
        00:57
      • 11.Amazon Elasticsearch
        04:34
      • 12.Amazon Elasticsearch Services
        05:22
      • 13.Demo – Loading Dataset into Elasticsearch
        01:18
      • 14.Logstash and R Studio
        01:51
      • 15.Demo – Fetching the File and Analyzing it using RStudio
        03:48
      • 16.Athena
        02:41
      • 17.Demo – Running Query on S3 using the Serverless Athena
        04:57
      • 18.Key Takeaways
        00:26
      Section 7 Visualization
      • 1.Learning Objective
        00:37
      • 2. Introduction to Amazon QuickSight
        04:57
      • 3.Visual Types
        03:48
      • 4.Story
        02:15
      • 5.Big Data Visualization
        03:33
      • 6.Key Takeaways
        00:26
      Section 8 Security
      • 1.Learning Objective
        00:40
      • 2.EMR Security and Security Group
        02:19
      • 3.Roles and Private Subnet
        02:27
      • 4.Encryption at Rest and In-transit
        03:09
      • 5.Redshift Security
        05:33
      • 6.Encryption at Rest using HSM
        02:39
      • 7.Cloud HSM vs AWS KMS
        02:32
      • 8.Limit Data Access
        01:24
      • 9.Key Takeaways
        00:28
      Section 9 Live Virtual Class Curriculum Course Introduction
      • Overview of AWS Certified Data Analytics – Speciality Course
      • Overview of the Certification
      • Overview of the Course
      • Project highlights
      • Course Completion Criteria
      Section 10 Collection
      • AWS Big Data Collection Services
      • Fundamentals of Amazon Kinesis
      • Loading Data into Kinesis Stream
      • Assisted Practice: Loading Data into Amazon Storage
      • Kinesis Data Stream High-Level Architecture
      • Kinesis Stream Core Concepts
      • AWS Services and Amazon Kinesis Data Stream
      • How to Put Data into Kinesis Stream?
      • Kinesis Connector Library
      • Amazon Kinesis Data Firehose
      • Assisted Practice: Transfer Data into Delivery Stream using Firehose
      • Assisted Practice: Transfer VPC Flow log to Splunk using Firehose
      • Data Transfer using AWS Lambda
      • Assisted Practice: Backing up data in Amazon S3 using AWS Lambda
      • Amazon SQS
      • IoT and Big Data
      • Amazon IoT Greengrass
      • AWS Data Pipeline
      • Components of Data Pipeline
      • Assisted Practice: Export MySQL Data to Amazon S3 Using AWS Data Pipeline
      • Key Takeaways
      • Streaming Data with Kinesis Data Analytics
      Section 11 Storage
      • AWS Bigdata Storage services
      • Data lakes and Analytics
      • Data Management
      • Data Life Cycle
      • Fundamentals of Amazon Glacier
      • Glacier and Big Data
      • DynamoDB Introduction
      • DynamoDB: Core Components
      • Assisted Practice: Perform operations on DynamoDB table
      • DynamoDB in AWS Eco-System
      • DynamoDB Partitions
      • Data Distribution
      • DynamoDB GSI and LSI
      • DynamoDB Streams
      • Use cases: Capturing Table Activity with DynamoDB Streams
      • Cross-Region Replication
      • Assisted Practice: Create a Global Table using DynamoDB
      • DynamoDB Performance: Deep Dive
      • Partition Key Selection
      • Snowball & AWS BigData
      • Assisted Practice: Data Migration using AWS Snowball
      • AWS DMS
      • AWS Aurora in BigData
      • Assisted Practice: Create and Modify Aurora DB Cluster
      • Storing and Retrieving the Data from DynamoDB
      Section 12 Processing I
      • AWS Bigdata Processing Services
      • Overview of Amazon Elastic MapReduce (EMR)
      • EMR Cluster Architecture
      • Apache Hadoop
      • Apache Hadoop Architecture
      • Storage Options
      • EMR Operations
      • AWS Cluster
      • Assisted Practice: Create a cluster in S3
      • Assisted Practice: Monitor a Cluster in S3
      • Using Hue with EMR
      • Assisted Practice: Launch HUE Web Interface on Amazon EMR
      • Setup Hue for LDAP
      • Assisted Practice: Configure HUE for LDAP Users
      • Hive on EMR
      • Assisted Practice: Set Up a Hive Table to Run Hive Commands
      • Key Takeaways
      Section 13 Processing II
      • Using HBase with EMR
      • HBase Architecture
      • Assisted Practice: Create a cluster with HBase
      • HBase and EMRFS
      • Presto with EMR
      • Presto Architecture
      • Fundamentals of Apache Spark
      • Apache Spark Architecture
      • Assisted Practice: Create a cluster with Spark
      • Apache Spark Integration with EMR
      • Fundamentals of EMR File System
      • Amazon Simple Workflow
      • AWS Lambda in Big Data Ecosystem
      • AWS Lambda and Kinesis Stream
      • AWS Lambda and RedShift
      • HCatalog
      • Key Takeaways
      • Real-Time Application with Apache Spark and AWS EMR
      Section 14 ETL with Redshift
      • Introduction to AWS Bigdata Analysis Services
      • Fundamentals of Amazon Redshift
      • Amazon RedShift Architecture
      • Assisted Practice: Launch a Cluster, Load Dataset, and Execute Queries
      • RedShift in the AWS Ecosystem
      • Columnar Databases
      • Assisted Practice: Monitor RedShift Maintenance and Operations
      • RedShift Table Design
      • Choosing the Distribution Style
      • Redshift Data types
      • RedShift Data Loading
      • COPY Command for Data Loading
      • RedShift Loading Data
      • Key Takeaways
      Section 15 Analysis with Machine Learning
      • Fundamentals of Machine Learning
      • Workflow of Amazon Machine Learning
      • Use cases
      • Machine learning Algorithms
      • Amazon SageMaker
      • Machine learning with Amazon Sagemaker
      • Assisted Practice: Build, Train, and Deploy a Machine Learning Model
      • Elasticsearch
      • Amazon Elasticsearch Service
      • Zone Awareness
      • Logstash
      • RStudio
      • Assisted Practice: Fetch the File and Run Analysis using RStudio
      • Amazon Athena
      • Assisted Practice: Execute Interactive SQL Queries in Athena
      • AWS Glue
      • Key Takeaways
      • Fraud Detection Using Classification Algorithms on AWS Sagemaker
      Section 16 Analysis and Visualization
      • Introduction to AWS Bigdata Visualization Services
      • Amazon QuickSight
      • Amazon QuickSight – Workflow and Use Cases
      • Assisted Practice: Analyze the marketing campaign
      • Working with data
      • Assisted Practice: Analyze the marketing campaign using data from Amazon S3
      • Assisted Practice: Analyze the marketing campaign using data from Presto
      • Amazon QuickSight: Visualization
      • Assisted Practice: Create Visuals
      • Amazon QuickSight: Stories
      • Assisted Practice: Create a Storyboard
      • Amazon QuickSight: Dashboard
      • Assisted Practice: Create a Dashboard
      • Data Visualization: Other Tools
      • Kibana
      • Assisted Practice: Create a Dashboard on Kibana
      • Key Takeaways
      • Exploratory Data Analysis Using AWS QuickSight
      Section 17 Big Data on AWS Introduction
      • Introduction to AWS Bigdata Visualization Services
      • Amazon QuickSight
      • Amazon QuickSight – Workflow and Use Cases
      • Assisted Practice: Analyze the marketing campaign
      • Working with data
      • Assisted Practice: Analyze the marketing campaign using data from Amazon S3
      • Assisted Practice: Analyze the marketing campaign using data from Presto
      • Amazon QuickSight: Visualization
      • Assisted Practice: Create Visuals
      • Amazon QuickSight: Stories
      • Assisted Practice: Create a Storyboard
      • Amazon QuickSight: Dashboard
      • Assisted Practice: Create a Dashboard
      • Data Visualization: Other Tools
      • Kibana
      • Assisted Practice: Create a Dashboard on Kibana
      • Key Takeaways
      • Exploratory Data Analysis Using AWS QuickSight
      Section 18 Security
      • Introduction to AWS Bigdata Security
      • EMR Security
      • EMR Security: Best Practices
      • Roles
      • Fundamentals of Redshift Security
      • Data Protection and Encryption
      • Master Key, Encryption, and Decryption Process
      • Amazon Redshift Database Encryption
      • Key Management Services(KMS) Overview
      • Encryption using Hardware Security Modules
      • STS and Cross Account Access
      • Cloud Trail
      • Key Takeaways
      Section 19 Practice Projects

      • Practice Projects

        • Real-time Analytics on Streaming Data
        • Truegate S3 Replication Big Data Assignment
      Section 20 AWS Technical Essentials

      • Lesson 01 Introduction to Cloud Computing

        01:31:19Preview
        • 01 Course Introduction – Simplilearn
          01:45
        • 02 Course Agenda
          02:46
        • 03 Need for Cloud Computing
          12:31
        • 04 what is cloud computing? – A
          05:24
        • 05 What is Cloud Computing? – B
          05:56
        • 06 What is Cloud Made up of?
          12:01
        • 07 benefits of cloud computing
          09:11
        • 08 Key concepts and Terminology
          05:38
        • 09 Economies of scale
          01:20
        • 10 capex vs opex
          02:54
        • 11 What is a Public cloud
          01:46
        • 12 characteristics of Public Cloud
          01:21
        • 13 What is Private CLoud?
          01:22
        • 14 Characteristics of Private CLoud
          01:34
        • 15 What is Hybrid cloud?
          01:01
        • 16 Characteristics of Hybrid CLoud
          01:11
        • 17 review and what next
          00:29
        • 18 What is IAAS?
          03:54
        • 19 Use cases of IAAS
          01:45
        • 20 what is paas?
          02:06
        • 21 Use Cases of PAAS
          03:35
        • 22 What is saas?
          02:28
        • 23 What is Shared Responsibility Model?
          09:21

      • Lesson 02 First Steps into Amazon Web Services

        29:20
        • 1 Foot Prints of Amazon Web Services – Datacenters
          13:58
        • 2 AWS Console Tour
          09:32
        • 3 Free access to AWS
          02:58
        • 4 Creating a Free AWS Account
          02:52

      • Lesson 03 Identity and Access Management (IAM)

        27:16
        • 1 Identity Access Management ( IAM ) – Part A
          08:50
        • 2 Identity Access Management ( IAM ) – Part B
          03:19
        • 3 Identity Access Management ( IAM ) – Part C
          08:23
        • 4 Identity Access Management ( IAM ) – Part D
          04:19
        • 5 Identity Access Management ( IAM ) – Part E
          02:25

      • Lesson 04 Networking in AWS – Virtual Private Clouds

        40:46Preview
        • 1 Networking Fundamentals – Part A
          03:58
        • 2 Networking Fundamentals – Part B
          08:06
        • 3 Conceptial Overview of VPC
          04:45
        • 4 AWS VPC – Walkthrough
          16:51
        • 5 NACLS and Security Groups
          07:06

      • Lesson 05 Elastic Compute Cloud (EC2)

        55:31
        • 1 What is Compute
          04:42
        • 2 AWS Compute Services
          13:25
        • 3 EC2 Instance – Lab Activity
          23:05
        • 4 EC2- Connecting to Windows Machine
          06:29
        • 5 Ec2 Instance – Linux Instance
          07:50

      • Lesson 06 AWS Storage

        45:25Preview
        • 1 Storage Fundamentals
          08:21
        • 2 AWS S3 – Simple Storage Services
          11:32
        • 3 AWS S3 – Simple Storage Services – B
          06:25
        • 4 AWS S3 Storage Classes and Data Lifecycle
          13:10
        • 5 AWS Storage Gateway
          05:57

      • Lesson 07 Load Balancing and Autoscaling

        14:12Preview
        • 1 AutoScaling
          06:01
        • 2 Elastic Load Balancer Lab
          03:51
        • 3 Load balancing and Autoscaling Introduction
          04:20

      • Lesson 08 DNS and Content Delivery Networks

        23:40
        • 1 Route 53
          12:16
        • 2 Cloud Front
          11:24

      • Lesson 09 Monitoring, Auditing and Alerts

        45:04Preview
        • 1 Cloud Watch
          15:47
        • 2 Cloud Trail
          05:53
        • 3 Simple Notification Services
          07:46
        • 4 AWS Config
          03:32
        • 5 AWS Config LAB
          09:50
        • 6 AWS CloudTrail vs. CloudWatch vs. Config
          02:16

      • Lesson 10 Databases

        18:22
        • 1 SQL – RDS
          09:34
        • 2 NO SQL Dynamo DB
          04:20
        • 3 ElastiCache and Redis
          04:28

      • Lesson 11 Serverless Computing

        05:34
        • 1 AWS Lambda
          05:34

      • Lesson 12 Security and Compliance

        15:04Preview
        • 1 Shared Responsibilty Model
          05:06
        • 2 Security and Compliance Services
          07:39
        • 3 AWS KMS
          02:19

      • Lesson 13 AWS Pricing, Billing, and Support Services

        29:02Preview
        • 1 AWS organizations
          03:00
        • 2 AWS Organizations – Lab Demonstration
          07:43
        • 3 AWS Pricing
          05:16
        • 4 AWS Billing and Cost Tools
          04:24
        • 4 AWS Support Plans and Trusted Advisor
          05:51
        • 5 AWS Whitepapers
          02:48

      • Lesson 14 Conclusion

        02:31Preview
        • 1 Course Conclusion
          02:31

      • Practice Project

        • AWS Tech Essentials Project – Media

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          As part of our eLearning program, you will be practically involved in various projects and assignments, which include Realtime Project Scenarios as well. This gives you realtime practical industry exposure. 

          VoiSAP’s certificate will be issued once you successfully complete the training which includes practicals, assignments and quiz.  

          VoiSAP’s certification training is recognized by more than 500  top MNCs, including CGI, Accenture, Walmart, Amazon, IMAX, Sony, RBC, HSBC, Standard Chartered Bank, IBM, Infosys, Lafarge, TCS, and many more.

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          SAP FICO Training FAQs

          Big Data on AWS is all about fitting AWS solutions inside a Big Data ecosystem. It includes knowledge of cloud-based Big data solutions such as Amazon EMR, Amazon Kinesis, Amazon Redshift, and Amazon Athena. Moreover, you’ll understand how to leverage best practices for designing Big Data environments for security, analysis, and cost-effectiveness.
          Beginners who are interested to learn how to build Big Data solutions on AWS can get started by referring to project guides, tutorials, or guided labs offered by AWS. However, this AWS Big Data certification training is curated for beginners, and enrolling in it can help you learn all the important concepts clearly.
          Yes, the training and course material offered by Simplilearn is aligned with the exam changes introduced by AWS and assist you in preparing for the DAS-C01 exam.

          You can enroll for this AWS Big Data certification training on our website and make an online payment using any of the following options:

          • Visa Credit or Debit Card
          • MasterCard
          • American Express
          • Diner’s Club
          • PayPal 

          Once payment is received, you will automatically receive a payment receipt and access information via email.

          You will get access to our e-learning content, practice simulation tests, and an online participant handbook that cross-references the e-learning to reinforce what you’ve learned.
          Online classroom training for the AWS Big Data certification course is conducted via online live streaming of each class. The classes are conducted by an AWS Big Data certified trainer with more than 15 years of work and training experience.