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Data Warehousing on AWS

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Data Warehousing on AWS introduces you to the ideas, methods, and best practises for creating a cloud-based data warehousing system using Amazon Redshift, the petabyte-scale data warehouse in AWS.

Course description

Using Amazon Redshift, the petabyte-scale data warehouse in AWS, Data Warehousing on AWS exposes you to principles, techniques, and best practices for developing a cloud-based data warehousing system. This AWS course shows how to leverage AWS services, including Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to gather, store, and prepare data for the data warehouse. Additionally, this course shows you how to analyze your data using Amazon QuickSight.

Activities

The AWS data warehousing course includes the following activities: 

  • Live Demonstrations 
  • Group Discussions 
  • Frequent Knowledge Checks 
  • Hands-On Labs

Course Objectives

Here’s what you’ll learn in this course: 

  • Talk about the fundamental principles of data warehousing and how big data solutions and data warehousing connect. 
  • Launch an Amazon Redshift cluster and construct a cloud data warehouse using its components, features, and capabilities. 
  • Contribute to the data warehousing solution by leveraging other AWS data and analytical services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. 
  • The data warehouse’s design 
  • Recognize performance problems, improve queries, and tune the database for improved performance. 
  • To analyze data directly from an Amazon S3 bucket, utilize Amazon Redshift Spectrum. 
  • Perform data analysis and visualization tasks against the data warehouse using Amazon QuickSight.

Intended Audience

You can take on this course if you belong to the following category of individuals:

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

Prerequisites

We recommend that attendees of this course have:

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

Module Breakdown

Course outline

Module 1: Introduction to Data Warehousing

  • 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

Module 2: Introduction to Amazon Redshift

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

Module 3: Launching clusters

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

Module 4: Designing the database schema

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

Module 5: Identifying data sources

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

Module 6: Loading data

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

Module 7: Writing queries and tuning for performance

  • 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

Module 8: Amazon Redshift Spectrum

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

Module 9: Maintaining clusters

  • 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

Module 10: Analyzing and visualizing data

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

FAQ's

Is Cloud Wizard Consulting an official AWS training partner?

Yes, we have been since 2015.

Who should take up this course?

You can take on this course if you belong to the following category of individuals:

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

What prior experience do you need for this course?

We recommend that attendees of this course have:

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

Course Schedule

Course Name Date Register
Data Warehousing on AWS 14 Dec - 16 Dec Register

Course Overview

Duration 3D / 24 HRS
Modality ViLT/ Classroom
Data Sheet DOWNLOAD
Check Dates CLICK HERE
Price 49,500.00

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