Building Data Analytics Solutions Using Amazon Redshift
You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift.
In this course, you will learn to:
- Compare the features and benefits of data warehouses, data lakes, and modern data architectures
- Design and implement a data warehouse analytics solution
- Identify and apply appropriate techniques, including compression, to optimize data storage
- Select and deploy appropriate options to ingest, transform, and store data
- Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
- Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
- Secure data at rest and in transit
- Monitor analytics workloads to identify and remediate problems
- Apply cost management best practices
- This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines.
Students with a minimum one-year experience managing data warehouses will benefit from this course. We recommend that attendees of this course have:
- Completed either AWS Technical Essentials or Architecting on AWS
- Completed Building Data Lakes on AWS
Module A: 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 Data API
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 B: Developing Modern Data Architectures on AWS
Modern data architectures
Why choose Cloud Wizard
- Advanced Tier Training Partner
- Amazon Authorised Instructors
- Official AWS Content
- Hands-on Labs
Class Deliverables
- E-Content kit by AWS
- Hands-on labs
- Class completion certificates
- Exam Prep sessions
Dates Available
Choose a date that works for you and click on Book Now to proceed with your registration.
Method | Duration | Start Time | Start date | Price | Action |
---|---|---|---|---|---|
Classroom | 1 days | All Day | May 6, 2024 | ₹15,000 | |
Classroom | 1 days | All Day | May 20, 2024 | ₹15,000 | |
Classroom | 1 days | All Day | June 3, 2024 | ₹15,000 | |
Classroom | 1 days | All Day | June 17, 2024 | ₹15,000 |
Don't see a date that works for you?
Fill in the form below to let us know.
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