The proven Study Guide that prepares you for this new Google Cloud exam The Google Cloud Certified Professional Data Engineer Study Guide, 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. Beginning with a pre-book assessment quiz to evaluate what you know before you begin, each chapter features exam objectives and review questions, plus the online learning environment includes additional complete practice tests. Written by Dan Sullivan, a popular and experienced online course author for machine learning, big data, and Cloud topics, Google Cloud Certified Professional Data Engineer Study Guide is your ace in the hole for deploying and managing analytics and machine learning applications. • Build and operationalize storage systems, pipelines, and compute infrastructure • Understand machine learning models and learn how to select pre-built models • Monitor and troubleshoot machine learning models • Design analytics and machine learning applications that are secure, scalable, and highly available. This exam guide is designed to help you develop an in depth understanding of data engineering and machine learning on Google Cloud Platform.

Google Certification Guide - Google Professional Data Engineer Navigate the Data Landscape with Google Cloud Expertise Embark on a journey to become a Google Professional Data Engineer with this comprehensive guide. Tailored for data professionals seeking to leverage Google Cloud's powerful data solutions, this book provides a deep dive into the core concepts, practices, and tools necessary to excel in the field of data engineering. Inside, You'll Explore: Fundamentals to Advanced Data Concepts: Understand the full spectrum of Google Cloud data services, from BigQuery and Dataflow to AI and machine learning integrations. Practical Data Engineering Scenarios: Learn through hands-on examples and real-life case studies that demonstrate how to effectively implement data solutions on Google Cloud. Focused Exam Strategy: Prepare for the certification exam with detailed insights into the exam format, including key topics, study strategies, and practice questions. Current Trends and Best Practices: Stay abreast of the latest advancements in Google Cloud data technologies, ensuring your skills are up-to-date and industry-relevant. Authored by a Data Engineering Expert Written by an experienced data engineer, this guide bridges practical application with theoretical knowledge, offering a comprehensive and practical learning experience. Your Comprehensive Guide to Data Engineering Certification Whether you're an aspiring data engineer or an experienced professional looking to validate your Google Cloud skills, this book is an invaluable resource, guiding you through the nuances of data engineering on Google Cloud and preparing you for the Professional Data Engineer exam. Elevate Your Data Engineering Skills This guide is more than a certification prep book; it's a deep dive into the art of data engineering in the Google Cloud ecosystem, designed to equip you with advanced skills and knowledge for a successful career in data engineering. Begin Your Data Engineering Journey Step into the world of Google Cloud data engineering with confidence. This guide is your first step towards mastering the concepts and practices of data engineering and achieving certification as a Google Professional Data Engineer. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

The proven Study Guide that prepares you for this new Google Cloud exam The Google Cloud Certified Professional Data Engineer Study Guide, 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. Beginning with a pre-book assessment quiz to evaluate what you know before you begin, each chapter features exam objectives and review questions, plus the online learning environment includes additional complete practice tests. Written by Dan Sullivan, a popular and experienced online course author for machine learning, big data, and Cloud topics, Google Cloud Certified Professional Data Engineer Study Guide is your ace in the hole for deploying and managing analytics and machine learning applications. Build and operationalize storage systems, pipelines, and compute infrastructure Understand machine learning models and learn how to select pre-built models Monitor and troubleshoot machine learning models Design analytics and machine learning applications that are secure, scalable, and highly available. This exam guide is designed to help you develop an in depth understanding of data engineering and machine learning on Google Cloud Platform.

A Professional Data Engineer authorize data-driven decision making by collecting, transforming, and publishing data. A Data Engineer should be able to blueprint, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A Data Engineer should also be able to leverage, deploy, and continuous train pre-existing machine learning models. Here we’ve brought best Exam practice questions for Google Cloud so that you can prepare well for Professional Data Engineer exam. Unlike other online simulation practice tests, you get an eBook version that is easy to read & remember these questions. You can simply rely on these questions for successfully certifying this exam.

Do you want to learn the skills needed to be successful in a data engineer role? Do you want to learn about the infrastructure and platform services provided by Google Cloud Platform? If You Answered "Yes" To Any of The Above, Look No Further. This is the book for you! Hello! Welcome to "GOOGLE PROFESSIONAL DATA ENGINEERING". People looking to qualify in each job market are becoming increasingly competitive, and the qualifications required for a candidate to fill a vacancy are becoming increasingly demanding. Data engineers have a wide range of skills including the ability to design systems to ingest large volumes of data, store data cost-effectively, and efficiently process and analyze data with tools ranging from reporting and visualization to machine learning. You'll also have the opportunity to practice key job skills, including designing, building, and running data processing systems; and operationalizing machine-learning models. By the end of this book, you will be ready to use Google Cloud Data Engineering services to design, deploy and monitor data pipelines, deploy advanced database systems, build data analysis platforms, and support production machine learning environments. This book provides the skills you need to advance your career as a data engineer and provides training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification. Preparing in advance and getting to the market as soon as possible, puts the professional closer to winning a job. Once again as IT professionals.Here's what makes this book special: Google Professional Data Engineering Overview Design Data Processing Systems Building and Operationalizing A Data Processing System Ensuring Quality Solution Data Engineering on Google Cloud Preparing for A Google Cloud Exam Data Engineering Examination Much, much more! This book is different from others because in this book: You will be able to move forward architecting real-world data engineering solutions You will understand all the core services you'll need to know for the Data Engineer You will understand how to use Google's Big Data Services on the Google Cloud Platform. If you are interested in becoming a data engineer on Google's Cloud Platform then this book is for you.Interested?Then Scroll up, Click on "Buy now with 1-Click", and Get Your Copy Now!

All cloud architects need to know how to build data platforms that enable businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way. This handbook shows you how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, Google Cloud, and multicloud tools like Snowflake and Databricks. Authors Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire data lifecycle from ingestion to activation in a cloud environment using real-world enterprise architectures. You'll learn how to transform, secure, and modernize familiar solutions like data warehouses and data lakes, and you'll be able to leverage recent AI/ML patterns to get accurate and quicker insights to drive competitive advantage. You'll learn how to: Design a modern and secure cloud native or hybrid data analytics and machine learning platform Accelerate data-led innovation by consolidating enterprise data in a governed, scalable, and resilient data platform Democratize access to enterprise data and govern how business teams extract insights and build AI/ML capabilities Enable your business to make decisions in real time using streaming pipelines Build an MLOps platform to move to a predictive and prescriptive analytics approach

Learn the foundations of business intelligence, sector trade-offs, organizational structures, and technology stacks while mastering coursework, certifications, and interview success strategies Purchase of the print or Kindle book includes a free PDF eBook Key Features Identify promising job opportunities and ideal entry point into BI Build, design, implement, and maintain BI systems successfully Ace your BI interview with author's expert guidance on certifications, trainings, and courses Book DescriptionNavigating the challenging path of a business intelligence career requires you to consider your expertise, interests, and skills. Business Intelligence Career Master Plan explores key skills like stacks, coursework, certifications, and interview advice, enabling you to make informed decisions about your BI journey. You’ll start by assessing the different roles in BI and matching your skills and career with the tech stack. You’ll then learn to build taxonomy and a data story using visualization types. Additionally, you’ll explore the fundamentals of programming, frontend development, backend development, software development lifecycle, and project management, giving you a broad view of the end-to-end BI process. With the help of the author’s expert advice, you’ll be able to identify what subjects and areas of study are crucial and would add significant value to your skill set. By the end of this book, you’ll be well-equipped to make an informed decision on which of the myriad paths to choose in your business intelligence journey based on your skill set and interests.What you will learn Understand BI roles, roadmap, and technology stack Accelerate your career and land your first job in the BI industry Build the taxonomy of various data sources for your organization Use the AdventureWorks database and PowerBI to build a robust data model Create compelling data stories using data visualization Automate, templatize, standardize, and monitor systems for productivity Who this book is for This book is for BI developers and business analysts who are passionate about data and are looking to advance their proficiency and career in business intelligence. While foundational knowledge of tools like Microsoft Excel is required, having a working knowledge of SQL, Python, Tableau, and major cloud providers such as AWS or GCP will be beneficial.