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Build faster and efficient real-world applications on the cloud with a fitting database model that's perfect for your needs Key Features Familiarize yourself with business and technical considerations involved in modeling the right database Take your data to applications, analytics, and AI with real-world examples Learn how to code, build, and deploy end-to-end solutions with expert advice Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently. The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you’ll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You’ll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples. By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.What you will learn Understand different use cases and real-world applications of data in the cloud Work with document and indexed NoSQL databases Get to grips with modeling considerations for analytics, AI, and ML Use real-world examples to learn about ETL services Design structured, semi-structured, and unstructured data for your applications and analytics Improve observability, performance, security, scalability, latency SLAs, SLIs, and SLOs Who this book is for This book is for database developers, data engineers, and architects looking to design, model, and build database applications on the cloud with an extended focus on operational consideration and taking their data to AI. Data scientists, as well ML and AI engineers who want to use Google Cloud services in the data to AI journey will also find plenty of useful information in this book. It will also be useful to data analysts and BI developers who want to use SQL impactfully to generate ML and generative AI insights from their data.
The book takes an objective, personalized and practical approach to designing the best database models while focusing on real-world examples and implementations with Google Cloud.
Become well-versed with database modeling and SQL optimization, and gain a deep understanding of transactional systems through practical examples and exercises Key Features Get to grips with fundamental-to-advanced database design and modeling concepts with PostgreSQL and MySQL Explore database integration with web apps, emerging trends, and real-world case studies Leverage practical examples and hands-on exercises to reinforce learning Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDatabase Design and Modeling with PostgreSQL and MySQL will equip you with the knowledge and skills you need to architect, build, and optimize efficient databases using two of the most popular open-source platforms. As you progress through the chapters, you'll gain a deep understanding of data modeling, normalization, and query optimization, supported by hands-on exercises and real-world case studies that will reinforce your learning. You'll explore topics like concurrency control, backup and recovery strategies, and seamless integration with web and mobile applications. These advanced topics will empower you to tackle complex database challenges confidently and effectively. Additionally, you’ll explore emerging trends, such as NoSQL databases and cloud-based solutions, ensuring you're well-versed in the latest developments shaping the database landscape. By embracing these cutting-edge technologies, you'll be prepared to adapt and innovate in today's ever-evolving digital world. By the end of this book, you’ll be able to understand the technologies that exist to design a modern and scalable database for developing web applications using MySQL and PostgreSQL open-source databases.What you will learn Design a schema, create ERDs, and apply normalization techniques Gain knowledge of installing, configuring, and managing MySQL and PostgreSQL Explore topics such as denormalization, index optimization, transaction management, and concurrency control Scale databases with sharding, replication, and load balancing, as well as implement backup and recovery strategies Integrate databases with web apps, use SQL, and implement best practices Explore emerging trends, including NoSQL databases and cloud databases, while understanding the impact of AI and ML Who this book is for This book is for a wide range of professionals interested in expanding their knowledge and skills in database design and modeling with PostgreSQL and MySQL. This includes software developers, database administrators, data analysts, IT professionals, and students. While prior knowledge of MySQL and PostgreSQL is not necessary, some familiarity with at least one relational database management system (RDBMS) will help you get the most out of this book.
Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions Key Features Get up to speed with data governance on Google Cloud Learn how to use various Google Cloud products like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream Boost your confidence by getting Google Cloud data engineering certification guidance from real exam experiences Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering. Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You’ll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you’ll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets. By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices.What you will learn Load data into BigQuery and materialize its output Focus on data pipeline orchestration using Cloud Composer Formulate Airflow jobs to orchestrate and automate a data warehouse Establish a Hadoop data lake, generate ephemeral clusters, and execute jobs on the Dataproc cluster Harness Pub/Sub for messaging and ingestion for event-driven systems Apply Dataflow to conduct ETL on streaming data Implement data governance services on Google Cloud Who this book is for Data analysts, IT practitioners, software engineers, or any data enthusiasts looking to have a successful data engineering career will find this book invaluable. Additionally, experienced data professionals who want to start using Google Cloud to build data platforms will get clear insights on how to navigate the path. Whether you're a beginner who wants to explore the fundamentals or a seasoned professional seeking to learn the latest data engineering concepts, this book is for you.
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. 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.
Use Looker for visualizing data, data analysis, and reporting, and learn how to connect to your data, build dashboards and reports, and share insights with your team Key Features Explore data visualization, analysis, and reporting with Looker to gain insights from your data Connect to data sources, build dashboards, and create reports to track and share key metrics Share insights with your team to make better business decisions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionLooker is a data analytics and business intelligence platform that allows organizations to explore, analyze, and visualize their data. It provides tools for data modeling, exploration, and visualization, enabling you to gain insights from your data to make informed business decisions. You’ll start with the basics, from setting up your Looker environments to configuring views and models using LookML. As you progress, you’ll delve into more advanced topics, such as navigating data in Explore, tailoring dashboards to your needs, and adding dynamic elements for interactivity. Along the way, you'll gain invaluable troubleshooting skills to tackle common issues and optimize your Looker usage, ensuring a smooth and seamless experience. Furthermore, the book extends your understanding beyond the basics, equipping you with the knowledge you need to develop Looker applications and seamlessly integrate them with other tools and applications. You'll also explore advanced techniques for harnessing Looker's full potential, empowering you to establish data-driven decision-making and innovation within your organization. By the end of this BI book, you'll have gained a solid understanding of how to use Looker to find important information, make tasks easier, and derive important insights.What you will learn Understand Looker's key components, including LookML, data models, and dashboards. Explore Looker's functionality, including custom fields, calculations, and visualizations. Work with Looker dashboards using dynamic elements like links and actions. Use different types of filters for dimensions to create dashboards Develop Looker applications using essential tools and frameworks Explore additional applications for the Looker organization Integrate Looker with other tools using APIs, connectors, and data pipelines Who this book is for If you’re a business analyst, data analyst, or BI developer who wants to get well-versed with the features of Looker, this book is for you. Basic knowledge of business intelligence is required to get started.
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers
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