Data Warehousing on AWS Overview

Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloudbased data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This
course demonstrates how to collect, store, and prepare data for the data warehouse by using AWS services
such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course
demonstrates how to use Amazon QuickSight to perform analysis on your data.

After completing Architecting on AWS course, students will be able to:

  • Apply database concepts, database management, and data modeling techniques
  • Evaluate relational database services (Amazon RDS, Amazon Aurora, and Amazon Redshift) and their features
  • Evaluate nonrelational database services (Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB) and their features
  • Examine how the design criteria apply to each service
  • Apply management principles based on the unique features of each service

Upcoming Batches

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Start Date End Date

2024-09-23

2024-09-26

2024-09-30

2024-10-03

2024-10-07

2024-10-10

2024-10-14

2024-10-17

2024-10-21

2024-10-24

Data Warehousing on AWS Course Key Features

  • Our Data Warehouse in AWS training modules have 50% - 60% hands-on lab sessions to encourage Thinking-Based Learning (TBL).
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL).
  • AWS certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL).
  • Well-structured use-cases to simulate challenges encountered in a Real-World environment.
  • Being an authorized AWS Training Partner gives us an edge over competition.
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform.

Who Should Attend this AWS Data Warehousing Training

  • Database Architects
  • Database Administrators
  • Database Developers
  • Data Analysts
  • Data Scientists

What are the prerequisites for the training?

We recommend that attendees of this course have:

  • Taken AWS Technical Essentials (or equivalent experience with AWS)
  • Familiarity with relational databases and database design concepts

In this course, you will:

  • Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions
  • Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud
  • Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution
  • Architect the data warehouse
  • Identify performance issues, optimize queries, and tune the database for better performance
  • Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket
  • Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse

AWS Data Warehousing Certification Course Outline Download Course Outline

  • Relational databases
  • Data warehousing concepts
  • The intersection of data warehousing and big data
  • Overview of data management in AWS
  • Hands-on lab 1: Introduction to Amazon Redshift

  • Conceptual overview
  • Real-world use cases
  • Hands-on lab 2: Launching an Amazon Redshift cluster

  • Building the cluster
  • Connecting to the cluster
  • Controlling access
  • Database security
  • Load datanowledge check
  • Hands-on lab 3: Optimizing database schemas

  • Schemas and data types
  • Columnar compression
  • Data distribution styles
  • Data sorting methods

  • Data sources overview
  • Amazon S3
  • Amazon DynamoDB
  • Amazon EMR
  • Amazon Kinesis Data Firehose
  • Hands-on lab 4: Loading real-time data into an Amazon Redshift database

  • Preparing Data
  • Loading data using COPY
  • Maintaining tables
  • Concurrent write operations
  • Troubleshooting load issues
  • Hands-on lab 5: Loading data with the COPY command

  • Amazon Redshift SQL
  • User-Defined Functions (UDFs)
  • Factors that affect query performance
  • The EXPLAIN command and query plans
  • Workload Management (WLM)
  • Hands-on lab 6: Configuring workload management

  • Amazon Redshift Spectrum
  • Configuring data for Amazon Redshift Spectrum
  • Amazon Redshift Spectrum Queries
  • Hands-on lab 7: Using Amazon Redshift Spectrum

  • Audit logging
  • Performance monitoring
  • Events and notifications
  • Lab 8: Auditing and monitoring clusters
  • Resizing clusters
  • Backing up and restoring clusters
  • Resource tagging and limits and constraints
  • Hands-on lab 9: Backing up, restoring and resizing clusters

  • Power of visualizations
  • Building dashboards
  • Amazon QuickSight editions and features

Certification details:

    • By earning Amazon Cloud Data Warehouse certification, you will show your future or current employer that you have knowledge of AWS Cloud concepts.
    • Data Warehousing on AWS certification can be used to learn cloud-based best practices for data-warehousing using Amazon platform.
    • On successful completion of AWS Data Warehouse course, aspirants receive a Course Completion Certificate from us.
    • By successfully clearing the Data Warehousing on AWS certification exams, aspirants earn AWS Certification.

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Course ID: 13499

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