I due componenti chiave di qualsiasi pipeline di dati sono costituiti dai data lake e dai data warehouse. In questo corso evidenzieremo i casi d'uso per ogni tipo di spazio di archiviazione e approfondiremo i dettagli tecnici delle soluzioni di data lake e data warehouse disponibili su Google Cloud. Inoltre, descriveremo il ruolo di un data engineer, illustreremo i vantaggi di una pipeline di dati di successo per le operazioni aziendali ed esamineremo i motivi per cui il data engineering dovrebbe essere eseguito in un ambiente cloud.
Modernizing Data Lakes & Data Warehouses with GC - Italiano
Instructor: Google Cloud Training
Included with
What you'll learn
Capire la differenza tra data lake e data warehouse.
Esplorare i casi d'uso per ogni tipo di spazio di archiviazione e le soluzioni di data lake e data warehouse disponibili su Google Cloud.
Discutere il ruolo di un data engineer e i vantaggi di una pipeline di dati di successo per le operazioni aziendali.
Esaminare i motivi per cui il data engineering dovrebbe avvenire in un ambiente cloud.
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October 2024
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There are 6 modules in this course
Questo modulo fornisce un'introduzione ai corsi della serie Data Engineering on Google Cloud e a questo corso specifico, dal titolo Modernizing Data Lakes and Data Warehouses with Google Cloud.
What's included
2 videos
In questo modulo viene illustrato il ruolo del data engineer, spiegando perché le attività di data engineering dovrebbero essere eseguite nel cloud
What's included
14 videos1 assignment1 app item
In questo modulo viene spiegato che cos'è un data lake e come utilizzare Cloud Storage come data lake su Google Cloud.
What's included
8 videos1 assignment1 app item
In questo modulo parleremo di BigQuery come opzione di data warehouse su Google Cloud
What's included
17 videos1 assignment3 app items
Riepilogo dei punti chiave per l'apprendimento
What's included
1 video
Link alle versioni PDF dei singoli moduli
What's included
1 reading
Instructor
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