Data Warehousing on AWS [GK4375]

Tijdsduur
Startdatum en plaats
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Startdata en plaatsen

Eindhoven (Evoluon Noord Brabantlaan 1)
5 aug. 2019 tot 7 aug. 2019
Zoetermeer (Centrum West 21)
28 okt. 2019 tot 30 okt. 2019
Amsterdam (Kingsfordweg 43)
25 nov. 2019 tot 27 nov. 2019
Nieuwegein (Iepenhoeve 5)
20 jan. 2020 tot 22 jan. 2020

Beschrijving

OVERVIEW

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.

OBJECTIVES

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 ca…

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OVERVIEW

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.

OBJECTIVES

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.

AUDIENCE

This course is intended for:

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

CONTENT

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

Bij Global Knowledge worden de klassikale trainingen gegeven door trainers die ook werkelijk expertise hebben: hooggekwalificeerde instructeurs die allen een pedagogische achtergrond hebben en hun praktijkervaring meenemen naar het klaslokaal. Trainers bij Global Knowledge hebben oog voor de persoonlijke leerstijlen om zo de trainingservaring van de cursisten te optimaliseren.

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