Crickard Data Engineering with Python

Work with massive datasets to design data models and automate data pipelines using Python
1. Auflage 2024
ISBN: 978-1-83921-230-7
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 356 Seiten

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

Autoren/Hrsg.

Crickard, Paul

Fachgebiete

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

Inhaltsverzeichnis

Table of Contents - What is Data Engineering?
- Building Our Data Engineering Infrastructure

- Reading and Writing Files
- Working with Databases
- Cleaning, Transforming, and Enriching Data
- Building a 311 Data Pipeline
- Features of a Production Pipeline
- Version Control Using the NiFi Registry
- Monitoring and Logging Pipelines
- Deploying Your Pipelines

- Building a Production Data Pipeline
- Building a Kafka Cluster
- Streaming Data with Apache Kafka
- Data Processing with Apache Spark
- Real-Time Edge Data with MiNiFi, Kafka, and Spark
- Appendix

Über Autor(innen)

Crickard Paul :

Paul Crickard authored a book on the Leaflet JavaScript module. He has been programming for over 15 years and has focused on GIS and geospatial programming for 7 years. He spent 3 years working as a planner at an architecture firm, where he combined GIS with Building Information Modeling (BIM) and CAD. Currently, he is the CIO at the 2nd Judicial District Attorney's Office in New Mexico.