Google Data Engineer: Google Cloud Certified - Professional Data Engineer
Certification Exam:
- 15 Courses | 13h 54m 50s
- 2 Books | 17h 38m
- 14 Courses | 19h 22m 28s
Acquire knowledge of building and maintaining data processing systems, and data analysis as you prepare for the Data Engineer certification.
GETTING STARTED
GCP Data Engineer Pro: Becoming a Google Cloud Data Engineer
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1m 27s
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6m 22s
COURSES INCLUDED
Platform Fundamentals
Google Cloud Platform offers several solutions to streamline any enterprise while keeping costs low. Explore these benefits, including how to navigate GCP and choose between the various data processing products it provides.
9 videos |
43m
Assessment
Badge
Storage & Analytics
Google Cloud Platform (GCP) offers several services for analytics and storage. Explore the storage, compute, and analytics concepts and how they are tied together.
13 videos |
1h 7m
Assessment
Badge
Deeper through GCP Analytics & Scaling
The big data industry is getting bigger, and GCP has several management tools designed for common use cases. Explore common concepts and use cases, including analytics tools and operations.
10 videos |
38m
Assessment
Badge
GCP Network Data Processing Models
You can create and manage an assortment of data processes and network models using GCP. Explore the various types, including using a GPU and TensorFlow to create and manage GPU and instances.
10 videos |
35m
Assessment
Badge
Dataproc
GCP provides fully managed cloud services for running Apache Spark and Hadoop. Explore the concepts of cluster management with Dataproc, including machine types and workers.
10 videos |
35m
Assessment
Badge
Dataproc Architecture
Dataproc can be used to perform several operations when integrating platforms, including Pig and Hive. Explore Dataproc architecture while introducing the use of Pig and Hive.
10 videos |
40m
Assessment
Badge
Dataproc Operations
Executing Dataproc implementations with big data can provide a variety of methods. Examine Dataproc implementations with Spark and Hadoop using the cloud shell and introduce BigQuery PySpark REPL package.
10 videos |
52m
Assessment
Badge
Implementations with BigQuery for Big Data
You can query big data using the BigQuery tool in the Google Cloud Platform. Discover the concepts of using BigQuery, including querying data and using the Google API.
11 videos |
1h 11m
Assessment
Badge
Fundamentals of BigQuery
BigQuery is an essential tool for any data analyst using Google Cloud Platform. Explore BigQuery and examine several operations including multiple table queries, nested and repeated fields and building BigQueries.
10 videos |
1h 13m
Assessment
Badge
APIs & Machine Learning
Machine learning and ML APIs are part of the Cloud ML engine. Explore the various ML APIs and how to implement an app that uses the Vision API.
9 videos |
59m
Assessment
Badge
Dataflow Autoscaling Pipelines
Apache Beam, Cloud Dataflow, and Cloud Dataprep can be used to create data pipelines. Explore how areas of Beam, Apache Beam SDK, Cloud Dataflow, and Cloud Dataprep assist in pipeline management.
10 videos |
37m
Assessment
Badge
Machine Learning with TensorFlow & Cloud ML
Cloud ML combines the Google Cloud Platform with TensorFlow to create models at scale. Explore concepts behind TensorFlow and scaling, as well as training models locally and in the cloud.
14 videos |
1h 19m
Assessment
Badge
GCP Engineering & Streaming Architecture
Feature engineering can be an essential tool in applied machine learning when enhancing a dataset. Explore concepts of feature engineering, including areas of streaming architecture and implementations.
12 videos |
1h 9m
Assessment
Badge
Streaming Pipelines & Analytics
Streaming data pipelines require operations that are very different from batch operations. Explore data stream operations, analytics, and the Google Data Studio visualization tool.
12 videos |
1h 2m
Assessment
Badge
GCP Big Data & Security
Complex operations require more managed and secure systems. Explore the use of Cloud Spanner and Bigtable to create more complex data service configurations and managing secure data infrastructure.
11 videos |
1h 7m
Assessment
Badge
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COURSES INCLUDED
GCP Data Engineer Pro: Becoming a Google Cloud Data Engineer
Data engineers collect data points. Each of these points-representing sales, user interactions, website visits, and more-tells a story, waiting to be deciphered. In this course, you will explore the role of a cloud data engineer, including job responsibilities, main activities, and key skills. You will discover how the data engineer role differs from other cloud-focused roles, such as a cloud developer or DevOps engineer. Then, you will focus on the Google Professional Data Engineer exam, identifying exam preparation resources and investigating practice questions to see what the exam might be like. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
10 videos |
39m
Assessment
Badge
GCP Data Engineer Pro: Navigating the Google Cloud Platform
In the ever-evolving field of data engineering, a solid understanding of the foundational elements of Google Cloud Platform (GCP) is essential. In this course, you will ensure that your foundational knowledge of how Google Cloud Platform operates is in place before moving to the more specific elements that are core to the role of the data engineer. You will review the basic GCP services and configurations, including using the Google Cloud Console and command line interface (CLI) to define security settings using identity and access management (IAM) and navigate a new project and virtual machine. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
12 videos |
1h 5m
Assessment
Badge
GCP Data Engineer Pro: Building Robust Data Structures
Just as architects draft blueprints to create resilient structures, you'll learn to design robust data storage solutions, ensuring your data's integrity and accessibility. This course lays the cornerstone for building a comprehensive understanding of Google Cloud Platform's (GCP) data services, equipping you with the skills to erect a formidable edifice of knowledge in the cloud computing landscape. In this course you will explore the world of GCP's data management, covering everything from storage architectures to data lake best practices. You'll learn to choose and manage storage services, design data models for warehouses, and normalize data. Next, you will discover how data access shapes warehouse architecture, explore GCP data lakes, and master cost control and access best practices. Finally, you will gain proficiency in data processing, monitoring on GCP, and constructing a data mesh with robust governance. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
14 videos |
1h 23m
Assessment
Badge
GCP Data Engineer Pro: Creating a Pipeline of Services
Just as landmarks guide you on a journey, the services covered in this course will serve as pivotal markers, steering you through the construction and optimization of robust data pipelines in the expansive landscape of Google Cloud. In this course, you'll uncover the essentials of data pipelines for analysis, learn about Google Cloud's data storage services, and automate data ingestion with Cloud Datastream and Pub/Sub. You'll delve into Hadoop and Hadoop Distributed File System (HDFS), compare Apache Kafka with Google services, and explore use cases for Cloud Data Fusion, Dataproc, Dataflow, and Beam. You'll also analyze BigQuery's role in data analysis and contrast it with MapReduce and Apache Spark, culminating in integrating Google Vertex AI for enhanced data analytics. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
13 videos |
1h 11m
Assessment
Badge
GCP Data Engineer Pro: Google Cloud Unstructured Data
In today's data-driven world, effective data management is crucial for businesses to thrive. In this course you will learn to select the correct storage class, ensuring efficiency and cost-effectiveness. Discover how to strategically choose bucket locations, optimizing for latency and compliance. Then you will encounter how to configure storage settings to manage object life cycles and secure objects with access control. Next you will explore Google Persistent Disk and Google Filestore. Finally, you will navigate through the pricing of Google Cloud Storage. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
18 videos |
1h 40m
Assessment
Badge
GCP Data Engineer Pro: Google Cloud OLTP Structured Data Storage
Google Cloud online transaction processing (OLTP) structured data storage is essential for high availability, scalability, real-time processing, and data integrity, enabling businesses to handle large volumes of data efficiently and securely. In this course, you will explore the architecture and uses of Google Cloud SQL as an OLTP database platform. Discover how business goals like Recovery Point Objective (RPO) and Recovery Time Objective (RTO) influence the selection of Cloud SQL editions. Learn the core tasks involved in managing a Google Cloud SQL database instance, execute database-level management tasks, examine strategies to ensure data availability and access, and implement failback procedures. You will use Google Database Migration Service to migrate existing databases to the Google Cloud Platform (GCP), delve into the functionality of and use cases for Google Cloud Spanner, set up a Spanner instance, and manage it at a high level. Finally, you will establish a database on a Spanner instance and carry out database-level management tasks. This course is one of a collection that prepares learners for the Google Cloud Certified - Professional Data Engineer exam.
16 videos |
2h
Assessment
Badge
GCP Data Engineer Pro: Google Cloud Semi-structured Data
Google Cloud's semi-structured data storage is vital for flexibility and scalability. It efficiently handles diverse data formats, supports rapid querying and analytics, and integrates seamlessly with other services, enabling businesses to derive insights and make data-driven decisions quickly. In this course, you will explore the practical applications of Firebase within the Google Cloud ecosystem, starting with the identification of use cases for Firebase and its integration with Google Cloud Services. Then delve into the Firebase Realtime Database, learning to establish, configure, and populate it with data. Next, you will shift focus to Firestore to create a data model for storing document-centric data and set up a Firestore Database. Finally, you will discover the NoSQL Google Cloud Bigtable, including schema design best practices, instance setup, and the intricacies of creating new tables, equipping you with the knowledge to effectively implement and manage NoSQL databases in real-world scenarios. This course is one of a collection that prepares learners for the Google Cloud Certified - Professional Data Engineer exam.
17 videos |
1h 50m
Assessment
Badge
GCP Data Engineer Pro: BigQuery Data Warehouse
In order to answer the big questions, you'll need to have the right data, arranged in the right way. BigQuery is the main Google repository for data that will be used in analysis and machine learning (ML). In this course, you will navigate the BigQuery UI and command line interface (CLI), explore public datasets, and learn the art of dataset replication. We will unveil the process of creating robust datasets, delve into the world of BigQuery tables, views, routines, and connections, and uncover the capabilities of BigQuery search and vector indexes. You'll also gain proficiency in importing data, batch loading options, and publishing datasets for collaboration. The course will guide you through optimizing costs with various pricing models, and introduce you to Looker and Looker Studio, where you'll create and share insightful reports. Finally, you'll be equipped to troubleshoot both BigQuery and Looker, ensuring a smooth data analysis experience. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
21 videos |
1h 56m
Assessment
Badge
GCP Data Engineer Pro: Messaging with Pub/Sub
From emails to voicemail to messaging, we are used to receiving information asynchronously and are grateful not to have to preplan a schedule for every single time someone wants to talk to us. In the world of Google Cloud data engineering, the Pub/Sub service functions as an asynchronous messaging tool that allows for data to be retrieved on demand rather than on a schedule. In this course, you will explore the benefits and concepts behind Pub/Sub messaging queues and the difference between Pub/Sub and Pub/Sub Lite. Then you will discover how to build a Pub/Sub messaging queue with push, pull, or even streaming configurations, as well as the security components that surround the service. This course is one of a collection that prepares learners for the Google Cloud Certified - Professional Data Engineer exam. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
11 videos |
59m
Assessment
Badge
GCP Data Engineer Pro: Using Google Datastream
Great data analysis is hard to achieve without bringing in data using a service like Datastream, which offers easy-to-use and serverless change data capture and replication. In this course, discover the integral role of Datastream within data pipelines, its primary use cases, how it seamlessly integrates into various stages, and the diverse sources and destinations that Datastream can connect with. Next, explore the network configurations necessary for optimal connectivity, build connection profiles, examine the life cycle of a stream, and maintain and manage streams effectively. Finally, learn how to configure Datastream to replicate data into BigQuery and stream data into Cloud Storage. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
11 videos |
50m
Assessment
Badge
GCP Data Engineer Pro: Dataset Processing
In the intricate world of data management, envisioning the flow of information as an oil pipeline offers a vivid analogy. Just as oil must be carefully extracted, transported, and refined, data too requires meticulous processes to ensure its value is maximized. In this course, learn about big data processing, including Dataproc cluster options, creating a Dataproc cluster and running a Spark job, and Dataprep flows, profiling, transforming, and sampling of data. Next, discover how to build and deploy robust Dataflow pipelines and options to fine-tune Dataflow pipeline performance. Finally, explore the setup and management of Data Fusion instances and pipelines, create a Data Fusion pipeline, and examine the pricing models for Dataproc, Dataprep, and Dataflow. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
19 videos |
2h 14m
Assessment
Badge
GCP Data Engineer Pro: Google Machine Learning and AI
Over time, humanity has learned from patterns, beginning with recognizing what characteristics indicate poisonous plants versus edible botanicals. In the same way, machine learning (ML) is all about recognizing the patterns in data so useful predictions can be made. In this course, explore ML systems tailored for diverse objectives, integrate ML into a data warehouse environment, different GCP ML products, and prebuilt models. Next, learn how to develop a project with a prebuilt ML model, the rationale for creating new models, and the ML data preparation process. Finally, discover how to create a custom-trained model using the Vertex AI SDK for Python and compare Vertex AI and BigQuery. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
13 videos |
1h 30m
Badge
GCP Data Engineer Pro: Optimizing a Google Data Warehouse
Managing Google Cloud Platform (GCP) resources is not unlike unlocking the doors of your own store, where every lesson on cost management and resource optimization added means your business can stay open another day, serve another customer, and become a profitable business operation. In this course, discover the intricacies of GCP cost-efficiency and resource management, how to balance expenses, and orchestrate resources in Dataproc clusters. Next, learn about automating workflows with Cloud Composer or Workflows and create and execute DAGs for Cloud Composer. Finally, explore how to fine-tune BigQuery processing and master the nuances of workload management for BigQuery. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
9 videos |
59m
Badge
GCP Data Engineer Pro: Data Migrations
Data warehouses, especially on-premises, commonly encounter growing pains, which is why many businesses choose to migrate their data to the Google Cloud Platform. However, migrations without loss of data can be tricky, so there are important aspects to consider. In this course, explore the intricacies of planning data migrations, the importance of validating migration plans, and ensuring seamless transitions. Next, discover the specifics of services like the Database Migration Service, Google Transfer Appliance, and BigQuery Data Transfer Service and how to integrate other services harmoniously within migration workflows. Finally, learn how to validate data migrations and address critical data governance concerns during the migration process. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.
11 videos |
58m
Badge
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EARN A DIGITAL BADGE WHEN YOU COMPLETE THESE COURSES
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.BOOKS INCLUDED
Book
Google Cloud Platform in ActionThis book teaches you to build and launch applications that scale, leveraging the many services on GCP to move faster than ever.
10h 19m
By JJ Geewax
Book
Official Google Cloud Certified Professional Data Engineer Study GuideYour ace in the hole for deploying and managing analytics and machine learning applications, this book provides everything you need to prepare for this important exam and master the skills necessary to land that coveted Google Cloud Professional Data Engineer certification.
7h 19m
By Dan Sullivan
