GK4375 | Data Warehousing on AWS | Training Course | Amazon Web Services. Skip to main Content

Data Warehousing on AWS

  • Course Code GK4375
  • Duration 3 days
  • Language English

Additional Payment Options

  • GTC 29 inc. VAT

    GTC, Global Knowledge Training Credit, please contact Global Knowledge for more details

Public Classroom Price

eur1.995,00

excl. VAT

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Course Delivery

This course is available in the following formats:

  • Class Connect HD

    Connect to a class in HD

  • Company Event

    Event at company

  • Public Classroom

    Traditional Classroom Learning

  • Virtual Learning

    Learning that is virtual

Request this course in a different delivery format.

Course Overview

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Nederlands:

Met de training Data Warehousing AWS krijgt u een introductie in de concepten, strategieën en best practices om een cloud-based data warehouse oplossing te ontwerpen met behulp van Amazon Redshift. U leert hoe u met andere AWS-diensten zoals Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose en Amazon S3 data verzamelt, opslaat en voorbereid voor het datacenter. Daarnaast ontdekt u hoe u Business Intelligence oplossingen in kunt zetten voor analyse van uw data.

Deze cursus wordt aangeboden als een klassikale training inclusief het gebruik van hands-on labs. U krijgt tijdens de training de mogelijkheid om door middel van veel praktijkgerichte oefeningen om uw nieuwe vaardigheden te testen en kennis toe te passen op uw werkomgeving.

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English:

Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose, and Amazon S3. Additionally, this course demonstrates how to use business intelligence tools to perform analysis on your data. 

This course will be delivered through a mix of Instructor-led Training (ILT) and hands-on Labs. This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.

Course Schedule

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    • Delivery Format: Virtual Learning
    • Date: 08-10 May, 2024
    • Location: Virtual

    eur1.995,00

    • Delivery Format: Virtual Learning
    • Date: 15-17 July, 2024
    • Location: Virtual

    eur1.995,00

    • Delivery Format: Virtual Learning
    • Date: 11-13 November, 2024
    • Location: Virtual

    eur1.995,00

    • Delivery Format: Virtual Learning
    • Date: 08-10 January, 2025
    • Location: Virtual

    eur1.995,00

Target Audience

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This course is intended for:

  • Database architects
  • Database administrators
  • Database developers
  • Data analysts and scientists

Course Objectives

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This course teaches you how to:

  • Discuss the core concepts of data warehousing.
  • Evaluate the relationship between Amazon Redshift and other big data systems.
  • Evaluate use cases for data warehousing workloads and review case studies that demonstrate implementation of AWS data and analytic services as part of a data warehousing solution.
  • Choose an appropriate Amazon Redshift node type and size for your data needs.
  • Discuss security features as they pertain to Amazon Redshift, such as encryption, IAM permissions, and database permissions.
  • Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud.
  • Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose, and Amazon S3, to contribute to the data warehousing solution.
  • Evaluate approaches and methodologies for designing data warehouses.
  • Identify data sources and assess requirements that affect the data warehouse design.
  • Design the data warehouse to make effective use of compression, data distribution, and sort methods.
  • Load and unload data and perform data maintenance tasks.
  • Write queries and evaluate query plans to optimize query performance.
  • Configure the database to allocate resources such as memory to query queues and define criteria to route certain types of queries to your configured query queues for improved processing.
  • Use features and services, such as Amazon Redshift database audit logging, Amazon CloudTrail, Amazon CloudWatch, and Amazon Simple Notification Service (Amazon SNS), to audit, monitor, and receive event notifications about activities in the data warehouse.
  • Prepare for operational tasks, such as resizing Amazon Redshift clusters and using snapshots to back up and restore clusters.
  • Use a business intelligence (BI) application to perform data analysis and visualization tasks against your data.

Course Content

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This course covers the following concepts:

Day 1

  • Course Introduction
  • Introduction to Data Warehousing
  • Introduction to Amazon Redshift
  • Understanding Amazon Redshift Components and Resources
  • Launching an Amazon Redshift Cluster

Day 2

  • Reviewing Data Warehousing Approaches
  • Identifying Data Sources and Requirements
  • Designing the Data Warehouse
  • Loading Data into the Data Warehouse

Day 3

  • Writing Queries and Tuning Performance
  • Maintaining the Data Warehouse
  • Analyzing and Visualizing Data
  • Course Summary

Course Prerequisites

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We recommend that attendees of this course have the following prerequisites:

  • Courses taken: AWS Technical Essentials (or equivalent experience with AWS)
  • Familiarity with relational databases and database design concepts
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