Eagar Data Engineering with AWS

Learn how to design and build cloud-based data transformation pipelines using AWS
1. Auflage 2021
ISBN: 978-1-80056-904-1
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 482 Seiten

No detailed description available for "Data Engineering with AWS".

Autoren/Hrsg.

Eagar, Gareth

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

Table of Contents - An Introduction to Data Engineering
- Data Management Architectures for Analytics
- The AWS Data Engineer's Toolkit
- Data Cataloging, Security and Governance
- Architecting Data Engineering Pipelines
- Ingesting Batch and Streaming Data
- Transforming Data to Optimize for Analytics
- Identifying and Enabling Data Consumers
- Loading Data into a Data Mart
- Orchestrating the Data Pipeline
- Ad Hoc Queries with Amazon Athena
- Visualizing Data with Amazon QuickSight
- Enabling Artificial Intelligence and Machine Learning
- Wrapping Up the First Part of Your Learning Journey

Über Autor(innen)

Eagar Gareth:

Gareth Eagar has over 25 years of experience in the IT industry, starting in South Africa, working in the United Kingdom for a while, and now based in the USA. Having worked at AWS since 2017, Gareth has broad experience with a variety of AWS services, and deep expertise around building data platforms on AWS. While Gareth currently works as a Solutions Architect, he has also worked in AWS Professional Services, helping architect and implement data platforms for global customers. Gareth frequently speaks on data related topics.