Building Data Lakes on AWSBDLAAWAmazon Web ServicesAW-BDLA1.0<ul>
<li>Anwenden von Data-Lake-Methoden bei der Planung und Gestaltung eines Data Lakes</li><li>Beschreibung der Komponenten und Services, die für den Aufbau eines AWS Data Lake erforderlich sind</li><li>Sichern eines Data Lakes mit entsprechenden Berechtigungen</li><li>Einlesen, Speichern und Transformieren von Daten in einem Data Lake</li><li>Abfragen, Analysieren und Visualisieren von Daten in einem Data Lake</li></ul><p>Wir empfehlen, dass die Teilnehmer dieses Kurses zuvor folgenden Kenntnisse haben:</p>
<ul>
<li>Abschluss des <span class="cms-link-marked"><a class="fl-href-prod" href="/swisscom/course/amazon-awse"><svg role="img" aria-hidden="true" focusable="false" data-nosnippet class="cms-linkmark"><use xlink:href="/css/img/icnset-linkmarks.svg#linkmark"></use></svg>AWS Technical Essentials <span class="fl-prod-pcode">(AWSE)</span></a></span> Trainings</li><li>Ein Jahr Erfahrung im Aufbau von Datenanalyse-Pipelines oder Abschluss des digitalen Kurses „Data Analytics Fundamentals“</li></ul><ul>
<li>Data platform engineers</li><li>Solutions architects</li><li>IT professionals</li></ul><h5>Module 1: Introduction to data lakes</h5><ul>
<li>Describe the value of data lakes</li><li>Compare data lakes and data warehouses</li><li>Describe the components of a data lake</li><li>Recognize common architectures built on data lakes</li></ul><h5>Module 2: Data ingestion, cataloging, and preparation</h5><ul>
<li>Describe the relationship between data lake storage and data ingestion</li><li>Describe AWS Glue crawlers and how they are used to create a data catalog</li><li>Identify data formatting, partitioning, and compression for efficient storage and query</li><li>Lab 1: Set up a simple data lake</li></ul><h5>Module 3: Data processing and analytics</h5><ul>
<li>Recognize how data processing applies to a data lake</li><li>Use AWS Glue to process data within a data lake</li><li>Describe how to use Amazon Athena to analyze data in a data lake</li></ul><h5>Module 4: Building a data lake with AWS Lake Formation</h5><ul>
<li>Describe the features and benefits of AWS Lake Formation</li><li>Use AWS Lake Formation to create a data lake</li><li>Understand the AWS Lake Formation security model</li><li>Lab 2: Build a data lake using AWS Lake Formation</li></ul><h5>Module 5: Additional Lake Formation configurations</h5><ul>
<li>Automate AWS Lake Formation using blueprints and workflows</li><li>Apply security and access controls to AWS Lake Formation</li><li>Match records with AWS Lake Formation FindMatches</li><li>Visualize data with Amazon QuickSight</li><li>Lab 3: Automate data lake creation using AWS Lake Formation blueprints</li><li>Lab 4: Data visualization using Amazon QuickSight</li></ul><h5>Module 6: Architecture and course review</h5><ul>
<li>Post course knowledge check</li><li>Architecture review</li><li>Course review</li></ul>- Anwenden von Data-Lake-Methoden bei der Planung und Gestaltung eines Data Lakes
- Beschreibung der Komponenten und Services, die für den Aufbau eines AWS Data Lake erforderlich sind
- Sichern eines Data Lakes mit entsprechenden Berechtigungen
- Einlesen, Speichern und Transformieren von Daten in einem Data Lake
- Abfragen, Analysieren und Visualisieren von Daten in einem Data LakeWir empfehlen, dass die Teilnehmer dieses Kurses zuvor folgenden Kenntnisse haben:
- Abschluss des AWS Technical Essentials (AWSE) Trainings
- Ein Jahr Erfahrung im Aufbau von Datenanalyse-Pipelines oder Abschluss des digitalen Kurses „Data Analytics Fundamentals“- Data platform engineers
- Solutions architects
- IT professionalsModule 1: Introduction to data lakes
- Describe the value of data lakes
- Compare data lakes and data warehouses
- Describe the components of a data lake
- Recognize common architectures built on data lakes
Module 2: Data ingestion, cataloging, and preparation
- Describe the relationship between data lake storage and data ingestion
- Describe AWS Glue crawlers and how they are used to create a data catalog
- Identify data formatting, partitioning, and compression for efficient storage and query
- Lab 1: Set up a simple data lake
Module 3: Data processing and analytics
- Recognize how data processing applies to a data lake
- Use AWS Glue to process data within a data lake
- Describe how to use Amazon Athena to analyze data in a data lake
Module 4: Building a data lake with AWS Lake Formation
- Describe the features and benefits of AWS Lake Formation
- Use AWS Lake Formation to create a data lake
- Understand the AWS Lake Formation security model
- Lab 2: Build a data lake using AWS Lake Formation
Module 5: Additional Lake Formation configurations
- Automate AWS Lake Formation using blueprints and workflows
- Apply security and access controls to AWS Lake Formation
- Match records with AWS Lake Formation FindMatches
- Visualize data with Amazon QuickSight
- Lab 3: Automate data lake creation using AWS Lake Formation blueprints
- Lab 4: Data visualization using Amazon QuickSight
Module 6: Architecture and course review
- Post course knowledge check
- Architecture review
- Course review1 Tag750.00750.00750.00750.00750.00695.00695.00590.002000.002610.00750.00750.00750.00900.00870.00675.00930.00