Download or read book Database Design and Modeling with Google Cloud written by Abirami Sukumaran and published by Packt Publishing Ltd. This book was released on 2023-12-29 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Database Design and Modeling with Google Cloud written by Abirami Sukumaran and published by . This book was released on 2023-12-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Database Design and Modeling with PostgreSQL and MySQL written by Alkin Tezuysal and published by Packt Publishing Ltd. This book was released on 2024-07-26 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Engineering with Google Cloud Platform written by Adi Wijaya and published by Packt Publishing Ltd. This book was released on 2024-04-30 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Google Cloud Database Engineer Certification written by and published by Cybellium . This book was released on 2024-10-26 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Official Google Cloud Certified Professional Data Engineer Study Guide written by Dan Sullivan and published by John Wiley & Sons. This book was released on 2020-05-18 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Business Intelligence with Looker Cookbook written by Khrystyna Grynko and published by Packt Publishing Ltd. This book was released on 2024-05-24 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Conceptual Data Modeling and Database Design A Fully Algorithmic Approach Volume 1 written by Christian Mancas and published by CRC Press. This book was released on 2016-01-05 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new book aims to provide both beginners and experts with a completely algorithmic approach to data analysis and conceptual modeling, database design, implementation, and tuning, starting from vague and incomplete customer requests and ending with IBM DB/2, Oracle, MySQL, MS SQL Server, or Access based software applications. A rich panoply of s

Download or read book Practical Applications of Data Processing Algorithms and Modeling written by Whig, Pawan and published by IGI Global. This book was released on 2024-04-29 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's data-driven era, the persistent gap between theoretical understanding and practical implementation in data science poses a formidable challenge. As we navigate through the complexities of harnessing data, deciphering algorithms, and unleashing the potential of modeling techniques, the need for a comprehensive guide becomes increasingly evident. This is the landscape explored in Practical Applications of Data Processing, Algorithms, and Modeling. This book is a solution to the pervasive problem faced by aspiring data scientists, seasoned professionals, and anyone fascinated by the power of data-driven insights. From the web of algorithms to the strategic role of modeling in decision-making, this book is an effective resource in a landscape where data, without proper guidance, risks becoming an untapped resource. The objective of Practical Applications of Data Processing, Algorithms, and Modeling is to address the pressing issue at the heart of data science – the divide between theory and practice. This book seeks to examine the complexities of data processing techniques, algorithms, and modeling methodologies, offering a practical understanding of these concepts. By focusing on real-world applications, the book provides readers with the tools and knowledge needed to bridge the gap effectively, allowing them to apply these techniques across diverse industries and domains. In the face of constant technological advancements, the book highlights the latest trends and innovative approaches, fostering a deeper comprehension of how these technologies can be leveraged to solve complex problems. As a practical guide, it empowers readers with hands-on examples, case studies, and problem-solving scenarios, aiming to instill confidence in navigating data challenges and making informed decisions using data-driven insights.

Download or read book Data Science on the Google Cloud Platform written by Valliappa Lakshmanan and published by "O'Reilly Media, Inc.". This book was released on 2022-03-29 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Hands On Big Data Modeling written by James Lee and published by Packt Publishing Ltd. This book was released on 2018-11-30 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve all big data problems by learning how to create efficient data models Key FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learnGet insights into big data and discover various data modelsExplore conceptual, logical, and big data modelsUnderstand how to model data containing different file typesRun through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modelingCreate data models such as Graph Data and Vector SpaceModel structured and unstructured data using Python and RWho this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.

Download or read book Modeling and Processing for Next Generation Big Data Technologies written by Fatos Xhafa and published by Springer. This book was released on 2014-11-04 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest advances in Big Data technologies and provides the readers with a comprehensive review of the state-of-the-art in Big Data processing, analysis, analytics, and other related topics. It presents new models, algorithms, software solutions and methodologies, covering the full data cycle, from data gathering to their visualization and interaction, and includes a set of case studies and best practices. New research issues, challenges and opportunities shaping the future agenda in the field of Big Data are also identified and presented throughout the book, which is intended for researchers, scholars, advanced students, software developers and practitioners working at the forefront in their field.

Download or read book High Performance Computing in Biomimetics written by Kamarul Arifin Ahmad and published by Springer Nature. This book was released on with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Science for Decision Makers written by Jon Howells and published by Packt Publishing Ltd. This book was released on 2024-07-26 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridge the gap between business and data science by learning how to interpret machine learning and AI models, manage data teams, and achieve impactful results Key Features Master the concepts of statistics and ML to interpret models and guide decisions Identify valuable AI use cases and manage data science projects from start to finish Empower top data science teams to solve complex problems and build AI products Purchase of the print Kindle book includes a free PDF eBook Book DescriptionAs data science and artificial intelligence (AI) become prevalent across industries, executives without formal education in statistics and machine learning, as well as data scientists moving into leadership roles, must learn how to make informed decisions about complex models and manage data teams. This book will elevate your leadership skills by guiding you through the core concepts of data science and AI. This comprehensive guide is designed to bridge the gap between business needs and technical solutions, empowering you to make informed decisions and drive measurable value within your organization. Through practical examples and clear explanations, you'll learn how to collect and analyze structured and unstructured data, build a strong foundation in statistics and machine learning, and evaluate models confidently. By recognizing common pitfalls and valuable use cases, you'll plan data science projects effectively, from the ground up to completion. Beyond technical aspects, this book provides tools to recruit top talent, manage high-performing teams, and stay up to date with industry advancements. By the end of this book, you’ll be able to characterize the data within your organization and frame business problems as data science problems.What you will learn Discover how to interpret common statistical quantities and make data-driven decisions Explore ML concepts as well as techniques in supervised, unsupervised, and reinforcement learning Find out how to evaluate statistical and machine learning models Understand the data science lifecycle, from development to monitoring of models in production Know when to use ML, statistical modeling, or traditional BI methods Manage data teams and data science projects effectively Who this book is for This book is designed for executives who want to understand and apply data science methods to enhance decision-making. It is also for individuals who work with or manage data scientists and machine learning engineers, such as chief data officers (CDOs), data science managers, and technical project managers.

Download or read book Conceptual Modeling written by Gillian Dobbie and published by Springer Nature. This book was released on 2020-10-29 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 39th International Conference on Conceptual Modeling, ER 2020, which was supposed to be held in Vienna, Austria, in November 2020, but the conference was held virtually due to the COVID-19 pandemic. The 28 full and 16 short papers were carefully reviewed and selected from 143 submissions. This events covers a wide range of topics, and the papers are organized in the following sessions: foundations of conceptual modeling; process mining and conceptual modeling; conceptual modeling of business rules and processes; modeling chatbots, narratives and natural language; ontology and conceptual modeling; applications of conceptual modeling; schema design, evolution, NoSQL; empirical studies of conceptual modeling; networks, graphs and conceptual modeling; and conceptual modeling of complex and data-rich systems.

Download or read book Programming Google App Engine with Python written by Dan Sanderson and published by "O'Reilly Media, Inc.". This book was released on 2015-06-29 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical guide shows intermediate and advanced web and mobile app developers how to build highly scalable Python applications in the cloud with Google App Engine. The flagship of Google's Cloud Platform, App Engine hosts your app on infrastructure that grows automatically with your traffic, minimizing up-front costs and accommodating unexpected visitors. You’ll learn hands-on how to perform common development tasks with App Engine services and development tools, including deployment and maintenance. App Engine's Python support includes a fast Python 2.7 interpreter, the standard library, and a WSGI-based runtime environment. Choose from many popular web application frameworks, including Django and Flask. Get a hands-on introduction to App Engine's tools and features, using an example application Simulate App Engine on your development machine with tools from Google Cloud SDK Structure your app into individually addressable modules, each with its own scaling configuration Exploit the power of the scalable Cloud Datastore, using queries, transactions, and data modeling with the ndb library Use Cloud SQL for standard relational databases with App Engine applications Learn how to deploy, manage, and inspect your application on Google infrastructure

Download or read book The Cloud Computing Journey written by Divit Gupta and published by Packt Publishing Ltd. This book was released on 2024-01-05 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elevate your expertise and gain holistic insights into cloud technology with a focus on smoothly transitioning from on-premises to the cloud Key Features Analyze cloud architecture in depth, including different layers, components, and design principles Explore various types of cloud services from AWS, Microsoft Azure, Google Cloud, Oracle Cloud Infrastructure, and more Implement best practices and understand the use of various cloud deployment tools Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs the need for digital transformation and remote work surges, so does the demand for cloud computing. However, the complexity of cloud architecture and the abundance of vendors and tools can be overwhelming for businesses. This book addresses the need for skilled professionals capable of designing, building, and managing scalable and resilient cloud systems to navigate the complex landscape of cloud computing through practical tips and strategies. This comprehensive cloud computing guide offers the expertise and best practices for evaluating different cloud vendors and tools. The first part will help you gain a thorough understanding of cloud computing basics before delving deeper into cloud architecture, its design, and implementation. Armed with this expert insight, you'll be able to avoid costly mistakes, ensure that your cloud systems are secure and compliant, and build cloud systems that can adapt and grow with the business. By the end of this book, you’ll be proficient in leveraging different vendors and tools to build robust and secure cloud systems to achieve specific goals and meet business requirements.What you will learn Get to grips with the core concepts of cloud architecture and cost optimization Understand the different cloud deployment and service models Explore various cloud-related tools and technologies Discover cloud migration strategies and best practices Find out who the major cloud vendors are and what they offer Analyze the impact and future of cloud technology Who this book is for The book is for anyone interested in understanding cloud technology, including business leaders and IT professionals seeking insights into the benefits, challenges, and best practices of cloud computing. Those who are just starting to explore cloud technology, as well as those who are already using cloud technology and want to deepen their understanding to optimize usage, will find this resource especially useful.