Building Data Analytics Solutions Using Amazon Redshift

The Building Data Analytics Solutions Using Amazon Redshift (DAREDS) course is designed for participants who want to gain in-depth knowledge of best practices for designing and managing data analytics solutions on Amazon Redshift. During the course, participants will become familiar with Amazon Redshift features, such as architecture, database design, and performance management. Additionally, participants will learn how to integrate Amazon Redshift with other AWS technologies to build large-scale data analytics solutions. This course helps prepare for the AWS Certified Data Engineer – Associate certification .

Course Objectives

Below is a summary of the main objectives of the Building Data Analytics Solutions using Amazon Redshift (DAREDS) course :

  1. Gain in-depth knowledge of best practices for designing and managing data analytics solutions on Amazon Redshift.
  2. Familiarize yourself with Amazon Redshift features, including database architecture and design.
  3. Learn performance management in Amazon Redshift.
  4. Integrate Amazon Redshift with other AWS technologies.
  5. Build large-scale data analytics solutions using Amazon Redshift and other AWS technologies
  6. Implement data security and compliance measures within Amazon Redshift.
  7. Optimize query performance and manage resource utilization effectively.
  8. Troubleshoot common issues and ensure high availability and reliability of Redshift clusters.

 

Course Certification

This course helps you prepare to take the:

AWS Certified Data Engineer – Associate Exam ;

Course Outline

Module 0: Overview of Data Analytics and the Data Pipeline

  • Data analytics use cases
  • Using the data pipeline for analytics

Module 1: Using Amazon Redshift in the Data Analytics Pipeline

  • Why Amazon Redshift for data warehousing?
  • Overview of Amazon Redshift

Module 2: Introduction to Amazon Redshift

  • Amazon Redshift architecture
  • Interactive Demo 1: Touring the Amazon Redshift console
  • Amazon Redshift features
  • Practice Lab 1: Load and query data in an Amazon Redshift cluster

Module 3: Ingestion and Storage

  • Ingestion
  • Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with
  • API Data
  • Data distribution and storage
  • Interactive Demo 3: Analyzing semi-structured data using the SUPER data type
  • Querying data in Amazon Redshift
  • Practice Lab 2: Data analytics using Amazon Redshift Spectrum

Module 4: Processing and Optimizing Data

  • Data transformation
  • Advanced querying
  • Practice Lab 3: Data transformation and querying in Amazon Redshift
  • Resource management
  • Interactive Demo 4: Applying mixed workload management on Amazon Redshift
  • Automation and optimization
  • Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster

Module 5: Security and Monitoring of Amazon Redshift Clusters

  • Securing the Amazon Redshift cluster
  • Monitoring and troubleshooting Amazon Redshift clusters

Module 6: Designing Data Warehouse Analytics Solutions

  • Data warehouse use case review
  • Activity: Designing a data warehouse analytics workflow

Module 7: Developing Modern Data Architectures on AWS

  • Modern data architectures

Course Mode

Instructor-Led Remote Live Classroom Training;

Trainers

Trainers are Amazon AWS accredited instructors and certified in other IT technologies, with years of practical experience in the sector and in training.

Lab Topology

For all types of delivery, the participant can access the equipment and actual systems in our laboratories or directly in international data centers remotely, 24/7. Each participant has access to implement various configurations, Thus immediately applying the theory learned. Below are some scenarios drawn from laboratory activities.

Course Details

Course Prerequisites

Participation in the following courses is recommended:

  • Architecting on AWS
  • Building Data Lakes on AWS
  • AWS Hadoop Fundamentals

Course Duration

Intensive duration 1 days;

Course Frequency

Course Duration: 1 days (9.00 to 17.00) - Ask for other types of attendance.

Course Date

  • Building Data Analytics Solutions Using Amazon Redshift (Intensive Formula) – On Request – 9:00 – 17:00

Steps to Enroll

Registration takes place by asking to be contacted from the following link, or by contacting the office at the international number +355 45 301 313 or by sending a request to the email info@hadartraining.com