Planning and Designing Databases on AWS (PD-DB)

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Planning and Designing Databases on AWS (PD-DB)

Fast Lane Institute for Knowledge Transfer GmbH
Logo Fast Lane Institute for Knowledge Transfer GmbH
Provider rating: starstarstarstarstar_half 8.9 Fast Lane Institute for Knowledge Transfer GmbH has an average rating of 8.9 (out of 32 reviews)

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Starting dates and places

placeHamburg
19 Aug 2024 until 21 Aug 2024
placeMünchen
28 Oct 2024 until 30 Oct 2024
placeHamburg
25 Nov 2024 until 27 Nov 2024

Description

Kursinhalt

  • Course Introduction
  • AWS Purpose-Built Databases
  • Amazon Relational Database Service (Amazon RDS)
  • Amazon Aurora
  • Amazon DynamoDB
  • Amazon Keyspaces (for Apache Cassandra)
  • Amazon DocumentDB (with MongoDB compatibility)
  • Amazon Quantum Ledger Database (Amazon QLDB)
  • Amazon Neptune
  • Amazon Timestream
  • Amazon ElastiCache
  • Amazon MemoryDB for Redis
  • Amazon Redshift
  • Tools for Working with AWS Databases

Voraussetzungen

  • Kenntnisse der AWS-Datenbankservices, die der digitalen Schulung AWS-Datenbankangebote entsprechen
  • Verständnis von Datenbankdesignkonzepten und/oder Datenmodellierung für relationale oder nicht-relationale Datenbanken
  • Verständnis von Cloud Computing-Konzepten
  • Verständnis allgem…

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Kursinhalt

  • Course Introduction
  • AWS Purpose-Built Databases
  • Amazon Relational Database Service (Amazon RDS)
  • Amazon Aurora
  • Amazon DynamoDB
  • Amazon Keyspaces (for Apache Cassandra)
  • Amazon DocumentDB (with MongoDB compatibility)
  • Amazon Quantum Ledger Database (Amazon QLDB)
  • Amazon Neptune
  • Amazon Timestream
  • Amazon ElastiCache
  • Amazon MemoryDB for Redis
  • Amazon Redshift
  • Tools for Working with AWS Databases

Voraussetzungen

  • Kenntnisse der AWS-Datenbankservices, die der digitalen Schulung AWS-Datenbankangebote entsprechen
  • Verständnis von Datenbankdesignkonzepten und/oder Datenmodellierung für relationale oder nicht-relationale Datenbanken
  • Verständnis von Cloud Computing-Konzepten
  • Verständnis allgemeiner Netzwerkkonzepte und Verschlüsselungkonzepte
  • Verständnis der drei Vs für Daten (Volume, Velocity und Variety)

Zielgruppe

  • Dateningenieure
  • Lösungsarchitekten
  • Entwickler
  • IT-Fachleute

Detaillierter Kursinhalt

Day 1

Module 0: Course Introduction

  • Course overview

Module 1: AWS Purpose-Built Databases

  • Discussing well-architected databases
  • Analyzing workload requirements
  • Choosing the data model
  • Choosing the right purpose-built database
  • Knowledge check

Module 2: Amazon Relational Database Service (Amazon RDS)

  • Discussing a relational database
  • What is Amazon RDS?
  • Why Amazon RDS?
  • Amazon RDS design considerations
  • Knowledge check

Module 3: Amazon Aurora

  • What is Amazon Aurora?
  • Why Amazon Aurora?
  • Aurora design considerations
  • Knowledge check

Challenge Lab 1: Working with Amazon Aurora databases

Day 2

Class Activity 1: Choose the Right Relational Database

Module 4: Amazon DynamoDB

  • Discussing a key value database
  • What is DynamoDB?
  • Why DynamoDB?
  • DynamoDB design considerations
  • Knowledge check

Module 5: Amazon Keyspaces (for Apache Cassandra)

  • Discussing a wide-column database
  • What is Apache Cassandra?
  • What is Amazon Keyspaces?
  • Why Amazon Keyspaces?
  • Amazon Keyspaces design considerations
  • Knowledge check

Module 6: Amazon DocumentDB (with MongoDB compatibility)

  • Discussing a document database
  • What is Amazon DocumentDB?
  • Why Amazon DocumentDB?
  • Amazon DocumentDB design considerations
  • Knowledge check

Module 7: Amazon Quantum Ledger Database (Amazon QLDB)

  • Discussing a ledger database
  • What is Amazon QLDB?
  • Why Amazon QLDB?
  • Amazon QLDB design considerations
  • Knowledge check

Class Activity 2: Choose the Right Nonrelational Database

Challenge Lab 2: Working with Amazon DynamoDB Tables

Day 3

Module 8: Amazon Neptune

  • Discussing a graph database
  • What is Amazon Neptune?
  • Why Amazon Neptune?
  • Amazon Neptune design considerations
  • Knowledge check

Module 9: Amazon Timestream

  • Discussing a timeseries database
  • What is Amazon Timestream?
  • Why Amazon Timestream?
  • Amazon Timestream design considerations
  • Knowledge check

Module 10: Amazon ElastiCache

  • Discussing an in-memory database
  • What is ElastiCache?
  • Why ElastiCache?
  • ElastiCache design considerations
  • Knowledge check

Module 11: Amazon MemoryDB for Redis

  • What is Amazon MemoryDB (for Redis)?
  • Why Amazon MemoryDB?
  • Amazon MemoryDB design considerations
  • Knowledge check

Class Activity 3: Let’s Cache In

Module 12: Amazon Redshift

  • Discussing a data warehouse
  • What is Amazon Redshift?
  • Why Amazon Redshift?
  • Amazon Redshift design considerations
  • Knowledge check

Module 13: Tools for Working with AWS Databases

  • Data access and analysis with Amazon Athena
  • Data migration with SCT and DMS

Class Activity 4: Overall Picture

Challenge Lab 3: Working with Amazon Redshift clusters

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There are no frequently asked questions yet. If you have any more questions or need help, contact our customer service.