Database Design And Modeling With Google Cloud

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Database Design And Modeling With Google Cloud

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Author : Abirami Sukumaran
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-29

Database Design And Modeling With Google Cloud written by Abirami Sukumaran and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Computers categories.

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.

Building Machine Learning And Deep Learning Models On Google Cloud Platform

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Author : Ekaba Bisong
language : en
Publisher: Apress
Release Date : 2019-09-27

Building Machine Learning And Deep Learning Models On Google Cloud Platform written by Ekaba Bisong and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-27 with Computers categories.

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 dividedinto 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 results Know 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

Data Engineering With Google Cloud Platform

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Author : Adi Wijaya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-04-30

Data Engineering With Google Cloud Platform written by Adi Wijaya and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-30 with Computers categories.

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.

Data Science On The Google Cloud Platform

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Author : Valliappa Lakshmanan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-03-29

Data Science On The Google Cloud Platform written by Valliappa Lakshmanan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-29 with Computers categories.

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines

Data Science On The Google Cloud Platform

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Author : Valliappa Lakshmanan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-12-12

Data Science On The Google Cloud Platform written by Valliappa Lakshmanan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-12 with Computers categories.

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you’ll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You’ll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines

Google Professional Data Engineer

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Author : Jason Hoffman
language : en
Publisher: Book Collection Limited
Release Date : 2021-07-06

Google Professional Data Engineer written by Jason Hoffman and has been published by Book Collection Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-06 with categories.

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.

Data Engineering With Google Cloud Platform

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Author : Adi Wijaya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-31

Data Engineering With Google Cloud Platform written by Adi Wijaya and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-31 with Computers categories.

Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book 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 learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This 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.

Architecting Google Cloud Solutions

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Author : Victor Dantas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-05-14

Architecting Google Cloud Solutions written by Victor Dantas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-14 with Computers categories.

Achieve your business goals and build highly available, scalable, and secure cloud infrastructure by designing robust and cost-effective solutions as a Google Cloud Architect. Key FeaturesGain hands-on experience in designing and managing high-performance cloud solutionsLeverage Google Cloud Platform to optimize technical and business processes using cutting-edge technologies and servicesUse Google Cloud Big Data, AI, and ML services to design scalable and intelligent data solutionsBook Description Google has been one of the top players in the public cloud domain thanks to its agility and performance capabilities. This book will help you design, develop, and manage robust, secure, and dynamic solutions to successfully meet your business needs. You'll learn how to plan and design network, compute, storage, and big data systems that incorporate security and compliance from the ground up. The chapters will cover simple to complex use cases for devising solutions to business problems, before focusing on how to leverage Google Cloud's Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) capabilities for designing modern no-operations platforms. Throughout this book, you'll discover how to design for scalability, resiliency, and high availability. Later, you'll find out how to use Google Cloud to design modern applications using microservices architecture, automation, and Infrastructure-as-Code (IaC) practices. The concluding chapters then demonstrate how to apply machine learning and artificial intelligence (AI) to derive insights from your data. Finally, you will discover best practices for operating and monitoring your cloud solutions, as well as performing troubleshooting and quality assurance. By the end of this Google Cloud book, you'll be able to design robust enterprise-grade solutions using Google Cloud Platform. What you will learnGet to grips with compute, storage, networking, data analytics, and pricingDiscover delivery models such as IaaS, PaaS, and SaaSExplore the underlying technologies and economics of cloud computingDesign for scalability, business continuity, observability, and resiliencySecure Google Cloud solutions and ensure complianceUnderstand operational best practices and learn how to architect a monitoring solutionGain insights into modern application design with Google CloudLeverage big data, machine learning, and AI with Google CloudWho this book is for This book is for cloud architects who are responsible for designing and managing cloud solutions with GCP. You'll also find the book useful if you're a system engineer or enterprise architect looking to learn how to design solutions with Google Cloud. Moreover, cloud architects who already have experience with other cloud providers and are now beginning to work with Google Cloud will benefit from the book. Although an intermediate-level understanding of cloud computing and distributed apps is required, prior experience of working in the public and hybrid cloud domain is not mandatory.

Google Cloud Platform In Action

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Author : John J. (JJ) Geewax
language : en
Publisher: Simon and Schuster
Release Date : 2018-08-15

Google Cloud Platform In Action written by John J. (JJ) Geewax and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-15 with Computers categories.

Summary Google Cloud Platform in Action teaches you to build and launch applications that scale, leveraging the many services on GCP to move faster than ever. You'll learn how to choose exactly the services that best suit your needs, and you'll be able to build applications that run on Google Cloud Platform and start more quickly, suffer fewer disasters, and require less maintenance. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Thousands of developers worldwide trust Google Cloud Platform, and for good reason. With GCP, you can host your applications on the same infrastructure that powers Search, Maps, and the other Google tools you use daily. You get rock-solid reliability, an incredible array of prebuilt services, and a cost-effective, pay-only-for-what-you-use model. This book gets you started. About the Book Google Cloud Platform in Action teaches you how to deploy scalable cloud applications on GCP. Author and Google software engineer JJ Geewax is your guide as you try everything from hosting a simple WordPress web app to commanding cloud-based AI services for computer vision and natural language processing. Along the way, you'll discover how to maximize cloud-based data storage, roll out serverless applications with Cloud Functions, and manage containers with Kubernetes. Broad, deep, and complete, this authoritative book has everything you need. What's inside The many varieties of cloud storage and computing How to make cost-effective choices Hands-on code examples Cloud-based machine learning About the Reader Written for intermediate developers. No prior cloud or GCP experience required. About the Author JJ Geewax is a software engineer at Google, focusing on Google Cloud Platform and API design. Table of Contents PART 1 - GETTING STARTED What is "cloud"? Trying it out: deploying WordPress on Google Cloud The cloud data center PART 2 - STORAGE Cloud SQL: managed relational storage Cloud Datastore: document storage Cloud Spanner: large-scale SQL Cloud Bigtable: large-scale structured data Cloud Storage: object storage PART 3 - COMPUTING Compute Engine: virtual machines Kubernetes Engine: managed Kubernetes clusters App Engine: fully managed applications Cloud Functions: serverless applications Cloud DNS: managed DNS hosting PART 4 - MACHINE LEARNING Cloud Vision: image recognition Cloud Natural Language: text analysis Cloud Speech: audio-to-text conversion Cloud Translation: multilanguage machine translation Cloud Machine Learning Engine: managed machine learning PART 5 - DATA PROCESSING AND ANALYTICS BigQuery: highly scalable data warehouse Cloud Dataflow: large-scale data processing Cloud Pub/Sub: managed event publishing

Official Google Cloud Certified Professional Data Engineer Study Guide

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Author : Dan Sullivan
language : en
Publisher: John Wiley & Sons
Release Date : 2020-05-18

Official Google Cloud Certified Professional Data Engineer Study Guide written by Dan Sullivan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-18 with Computers categories.

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.