Building Data Analytics Solutions Using Amazon Redshift Training

Live Online & Classroom Enterprise Certification Training

Building Data Analytics Solutions Using Amazon Redshift is a course that teaches how to design, implement, and optimize data warehousing and analytics solutions using Amazon Redshift for fast, scalable, and cost-effective data analysis.

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What is Building Data Analytics Solutions Using Amazon Redshift Certification Training about?

In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift.

What are the objectives of Building Data Analytics Solutions Using Amazon Redshift Certification Training ?

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

Who is Building Data Analytics Solutions Using Amazon Redshift Certification Training for?

This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines.

What are the prerequisites for Building Data Analytics Solutions Using Amazon Redshift Certification Training?

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

Available Training Modes

Live Online Training

Classroom Training

1 Days

Course Outline Expand All

Expand All

Module 1: Introduction to Data Analytics and Redshift

Introduction to data analytics on AWS

Use cases and benefits of Amazon Redshift

Key features: MPP architecture, columnar storage, SQL interface

Redshift vs. other data warehousing solutions

Module 2: Redshift Architecture and Core Concepts

Cluster architecture: leader node and compute nodes

Data distribution styles: EVEN, KEY, ALL

Sort keys and distribution keys

Compression (encoding) and columnar storage

Redshift Spectrum overview (querying S3 directly)

Module 3: Setting Up Amazon Redshift

Launching a Redshift cluster

Connecting via SQL client tools (e.g., DBeaver, Workbench)

Creating databases, schemas, and tables

Basic user and role management

Integrating with Amazon S3 and AWS Glue Catalog

Module 4: Loading and Unloading Data

COPY command (from S3, DynamoDB, EMR)

Best practices for high-performance loads

Data formats: CSV, JSON, Parquet, ORC

Using UNLOAD to export data back to S3

Monitoring and troubleshooting load jobs

Module 5: Data Modeling and Performance Tuning

Star and Snowflake schema design

Choosing appropriate distribution and sort keys

Analyzing queries with EXPLAIN and query plans

Vacuuming and analyzing tables

Workload management (WLM) queues

Module 6: Advanced Querying and Analytics

Complex joins, CTEs, and window functions

Redshift ML (Machine Learning in Redshift)

Federated querying (querying across RDS, Aurora)

Using user-defined functions (UDFs)

Module 7: Redshift Spectrum

Overview and benefits

Creating external schemas and tables

Querying data directly in S3 using Redshift SQL

Performance tips for Spectrum queries

Integration with Athena and Glue Data Catalog

Module 8: Security, Monitoring, and Backup

IAM roles and permissions for Redshift

Data encryption: at rest and in transit

VPC, security groups, and network isolation

Snapshot and backup management

Monitoring with CloudWatch and Redshift Console

Module 9: Visualization and BI Integration

Integrating with Amazon QuickSight

Connecting Redshift to Tableau, Power BI, etc.

Building dashboards and reports

Direct querying vs. extract mode

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Who is the instructor for this training?

The trainer for this Building Data Analytics Solutions Using Amazon Redshift Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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