What is the main focus of 'Data Engineering With Google Cloud Platform'?

The book primarily focuses on operationalizing scalable data analytics systems using Google Cloud Platform. It covers essential concepts, tooling, and practical use cases needed to effectively manage data pipelines. Readers can gain insights into cloud architecture, data processing, and advanced analytics, enabling them to tackle complex data engineering challenges in their organizations.

Who is the target audience for this book?

This book is tailored for data engineers, data analysts, and IT professionals who are looking to deepen their understanding of data practices using Google Cloud Platform. It is also suitable for students and tech enthusiasts who aspire to build scalable data systems. First-time users of GCP will find the practical examples especially helpful for getting started in the cloud data space.

What skills will I gain from reading this book?

Readers will acquire skills in designing, building, and maintaining data analytics systems on GCP. The book provides insights into best practices in data warehousing, ETL processes, and managing large datasets. This knowledge is pivotal in a world increasingly reliant on cloud technologies, making it applicable for roles in data science and analytics.

Are there practical examples included in the book?

Yes, the book includes various practical examples and case studies that illustrate the implementation of GCP tools for data engineering tasks. These scenarios help bridge the gap between theory and practice, enabling readers to understand how to apply GCP solutions effectively in real-world contexts.

Is previous knowledge of Google Cloud necessary to understand this book?

While basic familiarity with cloud computing concepts can be beneficial, the book is designed to cater to both beginners and advanced users. It starts with foundational principles before progressing to more complex topics, ensuring that readers without prior GCP experience can still derive value from it.

What specific GCP tools and services are discussed in this book?

The book covers a variety of GCP tools, including BigQuery for analytics, Cloud Storage for data management, and Dataflow for processing streams of data. Each tool is explored in detail, providing readers with the knowledge to select the right services for their specific data needs and applications.

How does this book differentiate itself from others on data engineering?

This book stands out by focusing explicitly on operationalizing data systems using a cloud-native approach with GCP. It emphasizes practical implementation strategies rather than just theoretical concepts, providing readers with actionable insights and modern best practices tailored to today's data challenges.

Can this book help prepare me for GCP certification exams?

Absolutely! While primarily focused on practical applications, the book's coverage of GCP tools and best practices can serve as a valuable resource for those preparing for GCP certification exams. It reinforces critical knowledge and skills needed to excel in real-world applications, which align closely with the objectives of certification.

Are there resources for further learning after finishing the book?

Yes, the book often references additional resources, including online courses, documentation, and webinars that enable continuous learning. Engaging with these additional materials will help solidify and expand upon the concepts introduced in the book, ensuring readers stay updated with the latest GCP developments.

Where can I buy 'Data Engineering With Google Cloud Platform' in Liechtenstein?

You can purchase 'Data Engineering With Google Cloud Platform: A Practical Guide To Operationalizing Scalable Data Analytics Systems On GCP' from Ubuy in Liechtenstein. Ubuy offers a convenient online shopping experience, allowing you to easily place your order and have it delivered directly to your home.

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Data Engineering with Google Cloud Platform: A practical guide to operationalizing scalable data analytics systems on GCP

By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.

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Data Engineering with Google Cloud Platform: A practical guide to operationalizing scalable data analytics systems on GCP

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Besondere Merkmale

Practical Approach

Offers real-world examples and hands-on projects, ensuring users can effectively operationalize scalable data analytics systems in Google Cloud Platform, enhancing practical skills.

Comprehensive Coverage

Covers a wide range of GCP tools and services, giving users a thorough understanding of the data engineering ecosystem necessary for building robust analytics solutions.

Expert Insights

Written by industry experts, providing valuable best practices and tips that help users avoid common pitfalls and optimize their data engineering processes on the Google Cloud Platform.

Produktdetails

Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineerKey FeaturesUnderstand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solutionLearn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelinesDiscover tips to prepare for and pass the Professional Data Engineer examBook DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards.Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP.By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learnLoad data into BigQuery and materialize its output for downstream consumptionBuild data pipeline orchestration using Cloud ComposerDevelop Airflow jobs to orchestrate and automate a data warehouseBuild a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc clusterLeverage Pub/Sub for messaging and ingestion for event-driven systemsUse Dataflow to perform ETL on streaming dataUnlock the power of your data with Data StudioCalculate the GCP cost estimation for your end-to-end data solutionsWho this book is forThis book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book.Table of ContentsFundamentals of Data EngineeringBig Data Capabilities on GCPBuilding a Data Warehouse in BigQueryBuilding Orchestration for Batch Data Loading Using Cloud ComposerBuilding a Data Lake Using DataprocProcessing Streaming Data with Pub/Sub and DataflowVisualizing Data for Making Data-Driven Decisions with Data StudioBuilding Machine Learning Solutions on Google Cloud PlatformUser and Project Management in GCPCost Strategy in GCPCI/CD on Google Cloud Platform for Data EngineersBoosting Your Confidence as a Data Engineer

Publisher	Packt Publishing
Publication date	March 31, 2022
Language	English
Print length	440 pages
ISBN-10	1800561326
ISBN-13	978-1800561328
Item Weight	1.66 pounds (750 grams)
Dimensions	7.5 x 1 x 9.25 inches (19.1 x 2.5 x 23.5 cm)

Für wen ist das Produkt geeignet?

Data Engineers
Ideal for data engineers seeking to implement scalable data analytics solutions using Google Cloud Platform tools and services.
Cloud Professionals
Beneficial for cloud professionals wanting to gain practical experience in managing data analytics systems on GCP.
Students & Learners
Suitable for students and new learners interested in exploring data engineering concepts and practices using GCP.

Beginner Users
Not suitable for absolute beginners with no prior understanding of data engineering or cloud computing concepts.

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Understand data engineering concepts and the benefits of using GCP
Learn to use various GCP products for data ingestion, transformation, orchestration, and visualization
Gain tips to prepare for and pass the Professional Data Engineer exam
Build data pipeline orchestration using Cloud Composer and develop Airflow jobs
Leverage Pub/Sub for messaging and ingestion for event-driven systems
Calculate the GCP cost estimation for your end-to-end data solutions

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Data Engineering with Google Cloud Platform: A practical guide to operationalizing scalable data analytics systems on GCP

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