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Pipeline Pro: Erstellung von ETL-, Batch- und StreamingDatenpipelines für die Produktion mit Python und Airflow
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Publisher: Independently Published
Pages: 456
Weight: 1.20
Height: 1.13 Width: 6.00 Depth: 9.00
Language: German
PIPELINE PRO ist ein praxisorientierter Leitfaden für Data Engineers, Softwareentwickler, Analytics Engineers und Cloud-Architekten, die produktionsreife ETL-, Batch- und Streaming-Datenpipelines mit Python und Apache Airflow entwickeln möchten.
Moderne Unternehmen sind auf zuverlässige Datenpipelines angewiesen, die Informationen aus unterschiedlichen Quellen erfassen, verarbeiten und in Echtzeit oder im Batch-Modus bereitstellen. Dieses Buch zeigt, wie leistungsfähige Datenplattformen entworfen, automatisiert und für den produktiven Betrieb optimiert werden.
Von der Datenintegration über Workflow-Orchestrierung bis hin zu Überwachung und Skalierung vermittelt dieses Werk bewährte Methoden für den Aufbau robuster Data-Engineering-Lösungen.
Du lernst unter anderem:
- Wie ETL- und ELT-Pipelines mit Python entwickelt werden
- Wie Batch- und Streaming-Workloads effizient verarbeitet werden
- Wie Apache Airflow zur Workflow-Orchestrierung eingesetzt wird
- Wie Daten aus APIs, Datenbanken und Cloud-Diensten integriert werden
- Wie Datenqualität, Fehlerbehandlung und Wiederherstellung sichergestellt werden
- Wie Monitoring, Logging und Alarmierung für Datenpipelines eingerichtet werden
- Wie Datenpipelines für hohe Lasten und gro e Datenmengen skaliert werden
- Wie produktionsreife Data-Engineering-Architekturen aufgebaut und betrieben werden
Praxisnahe Beispiele, moderne Architekturkonzepte und reale Produktionsszenarien vermitteln das Wissen, um Datenpipelines zu entwickeln, die zuverlässig, skalierbar und langfristig wartbar sind.
Ob Business Intelligence, Echtzeitanalysen, Machine Learning oder Cloud-Data-Plattformen - dieses Buch vermittelt die Fähigkeiten, um professionelle Datenpipelines für anspruchsvolle Unternehmensanwendungen zu entwickeln.
PIPELINE PRO - Der umfassende Leitfaden für produktionsreife ETL-, Batch- und Streaming-Datenpipelines mit Python und Apache Airflow.
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