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Data Engineer Learning Path

school 13 activities
update Last updated 13 giorni
person Managed by Google Cloud
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.
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01

Tour dei lab pratici su Google Cloud

book Lab
access_time 45 minuti
show_chart Introduttivi

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.

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02

Preparing for your Professional Data Engineer Journey

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access_time 8 ore
show_chart Avanzati

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.

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03

Modernizing Data Lakes and Data Warehouses with Google Cloud

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access_time 8 ore
show_chart Intermedio

The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this...

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04

Building Batch Data Pipelines on Google Cloud

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access_time 13 ore
show_chart Intermedio

Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course...

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05

Building Resilient Streaming Analytics Systems on Google Cloud

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access_time 12 ore 15 minuti
show_chart Intermedio

Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course...

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06

Smart Analytics, Machine Learning, and AI on Google Cloud

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access_time 7 ore
show_chart Intermedio

Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more...

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07

Serverless Data Processing with Dataflow: Foundations

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access_time 2 ore 15 minuti
show_chart Intermedio

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...

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08

Serverless Data Processing with Dataflow: Develop Pipelines

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access_time 28 ore 30 minuti
show_chart Avanzati

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,...

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09

Serverless Data Processing with Dataflow: Operations

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access_time 13 ore
show_chart Avanzati

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...

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10

Perform Foundational Data, ML, and AI Tasks in Google Cloud

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access_time 6 ore 30 minuti
show_chart Introduttivi

Big data, machine learning e intelligenza artificiale sono i temi più attuali nel campo dell'elaborazione dati. Tuttavia, questi settori sono piuttosto specialistici ed è difficile trovare materiale introduttivo. Fortunatamente, Google Cloud fornisce servizi facili da usare in questi ambiti e...

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11

Build a Data Warehouse with BigQuery

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access_time 5 ore 15 minuti
show_chart Intermedio

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...

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12

Engineer Data for Predictive Modeling with BigQuery ML

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access_time 5 ore 30 minuti
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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and...

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13

Build a Data Mesh with Dataplex

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access_time 5 ore 30 minuti
show_chart Introduttivi

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...

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