01
Tour dei lab pratici su Google Cloud
In questo primo lab pratico accederai alla console Google Cloud e utilizzerai le funzionalità di base di Google Cloud: progetti, risorse, utenti IAM, ruoli, autorizzazioni e API.
Data Engineer Learning Path
Un Data Engineer progetta e crea sistemi che raccolgono e trasformano i dati utilizzati per informare le decisioni aziendali. Questo percorso di apprendimento ti guida attraverso una raccolta selezionata di corsi on demand, lab e badge delle competenze che
ti offrono esperienza pratica con esempi realistici dell'uso delle tecnologie Google Cloud essenziali per il ruolo di Data Engineer. Al termine del percorso, controlla la pagina relativa
alla certificazione Google Cloud Data Engineer per intraprendere i passi successivi del tuo percorso professionale.
02
Preparing for your Professional Data Engineer Journey
This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
03
Introduction to Data Engineering on Google Cloud
In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.
04
Modernizing Data Lakes and Data Warehouses with Google Cloud - Italiano
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...
05
Building Batch Data Pipelines on Google Cloud - Italiano
Le pipeline di dati in genere rientrano in uno dei paradigmi EL (Extract, Load), ELT (Extract, Load, Transform) o ETL (Extract, Transform, Load). Questo corso descrive quale paradigma dovrebbe essere utilizzato e quando per i dati in batch. Inoltre, questo...
06
Building Resilient Streaming Analytics Systems on Google Cloud - Italiano
L'elaborazione dei flussi di dati sta diventando sempre più diffusa poiché la modalità flusso consente alle aziende di ottenere parametri in tempo reale sulle operazioni aziendali. Questo corso tratta la creazione di pipeline di dati in modalità flusso su Google...
07
Serverless Data Processing with Dataflow: Foundations
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache...
08
Serverless Data Processing with Dataflow: Develop Pipelines
In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows,...
09
Serverless Data Processing with Dataflow: Operations
In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best...
10
Build a Data Warehouse with BigQuery
Complete the intermediate Build a Data Warehouse with BigQuery skill badge to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in...
11
Build a Data Mesh with Dataplex
Complete the introductory Build a Data Mesh with Dataplex skill badge to demonstrate skills in the following: building a data mesh with Dataplex to facilitate data security, governance, and discovery on Google Cloud. You practice and test your skills in...
12
Boost Productivity with Gemini in BigQuery
This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on...
13
Work with Gemini Models in BigQuery
This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course...