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Building Data Analytics Solutions Using Amazon Redshift

  • Length 1 day
  • Price  NZD 850 exc GST
Course overview
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Why study this course

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.

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What you’ll learn

This course is designed to teach participants how 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 optimise 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 visualisation 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

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AWS at Lumify Work

Lumify Work is an official AWS Training Partner for Australia, New Zealand, and the Philippines. Through our Authorised AWS Instructors, we can provide you with a learning path that’s relevant to you and your organisation, so you can get more out of the cloud. We offer virtual and face-to-face classroom-based training to help you build your cloud skills and enable you to achieve industry-recognised AWS Certification.

Who is the course for?

This course is intended for:

  • Data warehouse engineers

  • Data platform engineers

  • Architects and operators who build and manage data analytics pipelines

Course subjects

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: Analysing 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 Optimising 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 optimisation

  • 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

Please note: This is an emerging technology course. Course outline is subject to change as needed.


Students with a minimum one-year experience managing data warehouses will benefit from this course.

We recommend that attendees of this course have:

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.

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