pds-it
['Produktdetailseite','nein']
Amazon Web Services / AWS Data Analytics
Die Illustrationen sind in Kooperation von Menschen und künstlicher Intelligenz entstanden. Sie zeigen eine Zukunft, in der Technologie allgegenwärtig ist, aber der Mensch im Mittelpunkt bleibt.
KI-generierte Illustration

Building Data Analytics Solutions Using Amazon Redshift

Mastering Advanced Techniques for Scalable Data Warehousing and Analytics with AWS
Online
1 day
English
PDF herunterladen
€ 730,–
zzgl. MwSt.
€ 868,70
inkl. MwSt.
Buchungsnummer
33823
Veranstaltungsort
Online
3 Events
€ 730,–
zzgl. MwSt.
€ 868,70
inkl. MwSt.
Buchungsnummer
33823
Veranstaltungsort
Online
3 Events
Werde zertifizierter
Machine Lerning Engineer
Dieser Kurs ist Bestandteil der zertifizierten Master Class "Machine Learning Engineer". Bei Buchung der gesamten Master Class sparst du über 15 Prozent im Vergleich zur Buchung dieses einzelnen Moduls.
Zur Master Class
Inhouse Training
Firmeninterne Weiterbildung nur für eure Mitarbeiter:innen - exklusiv und wirkungsvoll.
Anfragen
In Kooperation mit
In this course, you will build an end-to-end data analytics solution using Amazon Redshift, the comprehensive cloud data warehouse solution on AWS.
Content

This course focuses on 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.


Module 1: Overview of Data Analytics and the Data Pipeline

  • Data analytics use cases 
  • Using the data pipeline for analytics

Module 2: Using Amazon Redshift in the Data Analytics Pipeline

  • Why Amazon Redshift for data warehousing?
  • Overview of Amazon Redshift

Module 3: Introduction to Amazon Redshift

  • Amazon Redshift architecture
  • Interactive demo: Touring the Amazon Redshift console
  • Amazon Redshift features
  • Practice lab: Load and query data in an Amazon Redshift cluster

Module 4: Ingestion and Storage

  • Ingestion
  • Interactive demo: Connecting your Amazon Redshift cluster using a Jupyter notebook with 
  • Data API
  • Data distribution and storage
  • Interactive demo: Analyzing semi-structured data using the SUPER data type
  • Querying data in Amazon Redshift
  • Practice lab: Data analytics using Amazon Redshift Spectrum

Module 5: Processing and Optimizing Data

  • Data transformation
  • Advanced querying
  • Practice lab: Data transformation and querying in Amazon Redshift
  • Resource management
  • Interactive demo: Applying mixed workload management on Amazon Redshift
  • Automation and optimization
  • Interactive demo: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster

Module 6: Security and Monitoring of Amazon Redshift Clusters

  • Securing the Amazon Redshift cluster
  • Monitoring and troubleshooting Amazon Redshift clusters

Module 7: Designing Data Warehouse Analytics Solutions

  • Data warehouse use case review
  • Activity: Designing a data warehouse analytics workflow

Module 8: Developing Modern Data Architectures on AWS

  • Modern data architecture
Benefits
  • Comparing the features and benefits of data warehouses, data lakes, and modern data architectures
  • Designing and implementing a data warehouse analytics solution
  • Identifying and applying appropriate techniques, including compression, to optimize data storage
  • Selecting and deploying appropriate options to ingest, transform, and store data 
  • Choosing the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
  • Understanding how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
  • Securing data at rest and in transit
  • Monitoring analytics workloads to identify and remediate problems
  • Applying cost management best practices

This course prepares you for AWS Data Analytics certification, among other courses of the AWS Data Analytics job role track.

Instructor
Yuri Nikulin
Matthew Millward
Methods

This course includes presentations, interactive demos, practice labs, discussions, and class exercises.

Who should attend

This course is intended for the following job roles:

  • Data Analytics

Attending the following course or equivalent knowledge is required:

  • First knowledge in Building Data Lakes on AWS
Starttermine und Details

Lernform

Learning form

9.12.2024
Online
Plätze frei
Durchführung gesichert
Online
Plätze frei
Durchführung gesichert
3.2.2025
Online
Plätze frei
Durchführung gesichert
Online
Plätze frei
Durchführung gesichert
17.3.2025
Online
Plätze frei
Durchführung gesichert
Online
Plätze frei
Durchführung gesichert

The training is carried out in cooperation with an authorized training partner. For the purpose of implementation, participant data will be transferred to the training partner and the training partner assumes responsibility for the processing of these data. Please take note of the corresponding privacy policy.

Du hast Fragen zum Training?
Ruf uns an unter +49 761 595 33900 oder schreib uns auf service@haufe-akademie.de oder nutze das Kontaktformular.