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| gcp master data management: Mastering Google Cloud Platform Cybellium Ltd, 2023-09-06 Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books. |
| gcp master data management: AI Fundamentals Courseware Reinier van den Biggelaar, 2023-09-26 The AI Fundamentals courseware offers an AI training course designed for professionals in business or government environments who want to understand the benefits and applications of AI in their work environment. This course covers topics such as data management for AI, building and assessing AI applications, ethics and trustworthiness, and organizational success factors for enabling humans and machines to work together. The course addresses key questions such as “Where does Data Management end and AI application begin?” from a management perspective. Subjects covered include the applications and benefits of AI, data and robots, predictions and algorithms, machine and deep learning, building and reviewing AI applications, data management for AI, ethics and trustworthiness, organizational success factors for helping humans and machines work together, and the future of AI. This courseware educates for three certifications within it’s three-day combined program. It’s also possible to cut the material in pieces for a module teaching approach. The EXIN BCS Artificial Intelligence Essentials, testing the fundamental concepts of AI. This AI for Business and Government certification (the AI Brevet) which was established by the Netherlands AI Coalition (NL AIC) as a standard for professionals who want to use Artificial Intelligence. EXIN BCS Artificial Intelligence Foundation, which has a more IT-technical perspective. |
| gcp master data management: Google Certified Professional Cloud Architect Jamie Murphy, 2023-11-13 Are you aspiring to become a certified expert in cloud architecture on the Google Cloud Platform (GCP)? Look no further! This comprehensive guide is your key to mastering the essential concepts and skills needed to ace the Google Certified Professional Cloud Architect exam. Dive into the world of cloud computing with a focus on Google Cloud Platform. This book takes you on a journey from the fundamentals of cloud computing to in-depth discussions on GCP services, identity and access management, resource management, networking, compute, containers, storage, databases, data analytics, cloud operations, and more. Enhance your exam preparedness with a collection of practice exam questions. Each question is designed to mimic the format and content of the actual certification exam. Detailed explanations accompany each answer, providing valuable insights and clarifications to solidify your understanding. Key Features: Comprehensive Coverage: Explore a wide range of GCP services and topics, ensuring you have a well-rounded understanding of cloud architecture principles. Hands-On Insight: Gain practical insights through hands-on examples and scenarios, preparing you for real-world challenges in cloud architecture. Practice Exam Questions: Test your knowledge with a set of carefully crafted practice exam questions and receive detailed explanations for each answer. Strategic Learning Path: Follow a strategic learning path that progressively builds your skills and knowledge, making complex concepts accessible and understandable. Preparation Guidance: Receive guidance on exam preparation strategies, best practices, and tips to boost your confidence and performance on the certification exam. IT professionals aspiring to become Google Certified Professional Cloud Architects. Cloud enthusiasts seeking comprehensive insights into Google Cloud Platform services and practices. Professionals aiming to validate their cloud architecture skills with a globally recognized certification. Equip yourself with the knowledge and confidence to architect scalable, secure, and highly available solutions on Google Cloud Platform. Whether you're new to cloud technology or an experienced professional, this guide is tailored to elevate your skills and prepare you for success in the dynamic world of cloud architecture. Unlock the doors to your cloud journey. Get ready to pass the Google Certified Professional Cloud Architect exam with flying colors! |
| gcp master data management: Scaling Google Cloud Platform Swapnil Dubey, 2022-10-29 Managing Real-world Production-grade Challenges at Scale KEY FEATURES ● Built for GCP professionals and Cloud enthusiasts with cloud-agnostic tactics. ● Exhaustive coverage of automatic, manual, and predictive scaling and specialized strategies. ● Every concept is pragmatized with real-time production scenarios derived from prominent technologists. DESCRIPTION ‘Scaling Google Cloud Platform’ equips developers with the know-how to get the most out of its services in storage, serverless computing, networking, infrastructure monitoring, and other IT tasks. This book explains the fundamentals of cloud scaling, including Cloud Elasticity, creating cloud workloads, and selecting the appropriate cloud scaling key performance indicators (KPIs). The book explains the sections of GCP resources that can be scaled, as well as their architecture and internals, and best practices for using these components in an operational setting in detail. The book also discusses scaling techniques such as predictive scaling, auto-scaling, and manual scaling. This book includes real-world examples illustrating how to scale many Google Cloud services, including the compute engine, GKE, VMWare Engine, Cloud Function, Cloud Run, App Engine, BigTable, Spanner, Composer, Dataproc, and Dataflow. At the end of the book, the author delves into the two most common architectures—Microservices and Bigdata to examine how you can perform reliability engineering for them on GCP. WHAT YOU WILL LEARN ● Learn workload migration strategy and execution, both within and between clouds. ● Explore methods of increasing Google Cloud capacity for running VMware Engine and containerized applications. ● Scaling up and down methods include manual, predictive, and automatic approaches. ● Increase the capacity of your Dataproc cluster to handle your big data computing needs. ● Learn Google Dataflow's scalability considerations for large-scale installations. ● Explore Google Composer 2 and scale up your Cloud Spanner instances. ● Learn to set up Cloud functions and Cloud run. ● Discuss general SRE procedures on microservices and big data. WHO THIS BOOK IS FOR This book is designed for Cloud professionals, software developers, architects, DevOps team, and engineering managers to explain scaling strategies for GCP services and assumes readers know GCP basics. TABLE OF CONTENTS 1. Basics of Scaling Cloud Resources 2. KPI for Cloud Scalability 3. Cloud Elasticity 4. Challenges of Infrastructure Complexity and the Way Forward 5. Scaling Compute Engine 6. Scaling Kubernetes Engine 7. Scaling VMware Engine 8. Scaling App Engine 9. Scaling Google Cloud Function and Cloud Run 10. Configuring Bigtable for Scale 11. Configuring Cloud Spanner for Scale 12. Scaling Google Composer 2 13. Scaling Google Dataproc 14. Scaling Google Dataflow 15. Site Reliability Engineering 16. SRE Use Cases |
| gcp master data management: Data Management at Scale Piethein Strengholt, 2023-04-10 As data management continues to evolve rapidly, managing all of your data in a central place, such as a data warehouse, is no longer scalable. Today's world is about quickly turning data into value. This requires a paradigm shift in the way we federate responsibilities, manage data, and make it available to others. With this practical book, you'll learn how to design a next-gen data architecture that takes into account the scale you need for your organization. Executives, architects and engineers, analytics teams, and compliance and governance staff will learn how to build a next-gen data landscape. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including regulatory requirements, privacy concerns, and new developments such as data mesh and data fabric Go deep into building a modern data architecture, including cloud data landing zones, domain-driven design, data product design, and more Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata |
| gcp master data management: Practical Guide to Clinical Data Management Susanne Prokscha, 2011-10-26 The management of clinical data, from its collection during a trial to its extraction for analysis, has become a critical element in the steps to prepare a regulatory submission and to obtain approval to market a treatment. Groundbreaking on its initial publication nearly fourteen years ago, and evolving with the field in each iteration since then, |
| gcp master data management: Data Governance: The Definitive Guide Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy-Grant, Jessi Ashdown, 2021-03-08 As your company moves data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure you meet compliance. Data governance incorporates the ways that people, processes, and technology work together to support business efficiency. With this practical guide, chief information, data, and security officers will learn how to effectively implement and scale data governance throughout their organizations. You'll explore how to create a strategy and tooling to support the democratization of data and governance principles. Through good data governance, you can inspire customer trust, enable your organization to extract more value from data, and generate more-competitive offerings and improvements in customer experience. This book shows you how. Enable auditable legal and regulatory compliance with defined and agreed-upon data policies Employ better risk management Establish control and maintain visibility into your company's data assets, providing a competitive advantage Drive top-line revenue and cost savings when developing new products and services Implement your organization's people, processes, and tools to operationalize data trustworthiness. |
| gcp master data management: Data Governance: The Definitive Guide Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy-Grant, Jessi Ashdown, 2021-03-08 As your company moves data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure you meet compliance. Data governance incorporates the ways that people, processes, and technology work together to support business efficiency. With this practical guide, chief information, data, and security officers will learn how to effectively implement and scale data governance throughout their organizations. You'll explore how to create a strategy and tooling to support the democratization of data and governance principles. Through good data governance, you can inspire customer trust, enable your organization to extract more value from data, and generate more-competitive offerings and improvements in customer experience. This book shows you how. Enable auditable legal and regulatory compliance with defined and agreed-upon data policies Employ better risk management Establish control and maintain visibility into your company's data assets, providing a competitive advantage Drive top-line revenue and cost savings when developing new products and services Implement your organization's people, processes, and tools to operationalize data trustworthiness. |
| gcp master data management: Professional Cloud Architect – Google Cloud Certification Guide Konrad Cłapa, Brian Gerrard, 2019-10-18 Become a Professional Cloud Architect by exploring essential concepts, tools, and services in GCP and working through tests designed to help you get certified Key FeaturesPlan and design a GCP cloud solution architectureEnsure the security and reliability of your cloud solutions and operationsTest yourself by taking mock tests with up-to-date exam questionsBook Description Google Cloud Platform (GCP) is one of the leading cloud service suites and offers solutions for storage, analytics, big data, machine learning, and application development. It features an array of services that can help organizations to get the best out of their infrastructure. This comprehensive guide covers a variety of topics specific to Google's Professional Cloud Architect official exam syllabus and guides you in using the right methods for effective use of GCP services. You'll start by exploring GCP, understanding the benefits of becoming a certified architect, and learning how to register for the exam. You'll then delve into the core services that GCP offers such as computing, storage, and security. As you advance, this GCP book will help you get up to speed with methods to scale and automate your cloud infrastructure and delve into containers and services. In the concluding chapters, you'll discover security best practices and even gain insights into designing applications with GCP services and monitoring your infrastructure as a GCP architect. By the end of this book, you will be well versed in all the topics required to pass Google's Professional Cloud Architect exam and use GCP services effectively. What you will learnManage your GCP infrastructure with Google Cloud management options such as CloudShell and SDKUnderstand the use cases for different storage optionsDesign a solution with security and compliance in mindMonitor GCP compute optionsDiscover machine learning and the different machine learning models offered by GCPUnderstand what services need to be used when planning and designing your architectureWho this book is for If you are a cloud architect, cloud engineer, administrator, or any IT professional who wants to learn how to implement Google Cloud services in your organization and become a GCP Certified Professional Cloud Architect, this book is for you. Basic knowledge of server infrastructure, including Linux and Windows Servers, is assumed. Knowledge of network and storage will also be helpful. |
| gcp master data management: Ultimate Big Data Analytics with Apache Hadoop Simhadri Govindappa, 2024-09-09 TAGLINE Master the Hadoop Ecosystem and Build Scalable Analytics Systems KEY FEATURES ● Explains Hadoop, YARN, MapReduce, and Tez for understanding distributed data processing and resource management. ● Delves into Apache Hive and Apache Spark for their roles in data warehousing, real-time processing, and advanced analytics. ● Provides hands-on guidance for using Python with Hadoop for business intelligence and data analytics. DESCRIPTION In a rapidly evolving Big Data job market projected to grow by 28% through 2026 and with salaries reaching up to $150,000 annually—mastering big data analytics with the Hadoop ecosystem is most sought after for career advancement. The Ultimate Big Data Analytics with Apache Hadoop is an indispensable companion offering in-depth knowledge and practical skills needed to excel in today's data-driven landscape. The book begins laying a strong foundation with an overview of data lakes, data warehouses, and related concepts. It then delves into core Hadoop components such as HDFS, YARN, MapReduce, and Apache Tez, offering a blend of theory and practical exercises. You will gain hands-on experience with query engines like Apache Hive and Apache Spark, as well as file and table formats such as ORC, Parquet, Avro, Iceberg, Hudi, and Delta. Detailed instructions on installing and configuring clusters with Docker are included, along with big data visualization and statistical analysis using Python. Given the growing importance of scalable data pipelines, this book equips data engineers, analysts, and big data professionals with practical skills to set up, manage, and optimize data pipelines, and to apply machine learning techniques effectively. Don’t miss out on the opportunity to become a leader in the big data field to unlock the full potential of big data analytics with Hadoop. WHAT WILL YOU LEARN ● Gain expertise in building and managing large-scale data pipelines with Hadoop, YARN, and MapReduce. ● Master real-time analytics and data processing with Apache Spark’s powerful features. ● Develop skills in using Apache Hive for efficient data warehousing and complex queries. ● Integrate Python for advanced data analysis, visualization, and business intelligence in the Hadoop ecosystem. ● Learn to enhance data storage and processing performance using formats like ORC, Parquet, and Delta. ● Acquire hands-on experience in deploying and managing Hadoop clusters with Docker and Kubernetes. ● Build and deploy machine learning models with tools integrated into the Hadoop ecosystem. WHO IS THIS BOOK FOR? This book is tailored for data engineers, analysts, software developers, data scientists, IT professionals, and engineering students seeking to enhance their skills in big data analytics with Hadoop. Prerequisites include a basic understanding of big data concepts, programming knowledge in Java, Python, or SQL, and basic Linux command line skills. No prior experience with Hadoop is required, but a foundational grasp of data principles and technical proficiency will help readers fully engage with the material. TABLE OF CONTENTS 1. Introduction to Hadoop and ASF 2. Overview of Big Data Analytics 3. Hadoop and YARN MapReduce and Tez 4. Distributed Query Engines: Apache Hive 5. Distributed Query Engines: Apache Spark 6. File Formats and Table Formats (Apache Ice-berg, Hudi, and Delta) 7. Python and the Hadoop Ecosystem for Big Data Analytics - BI 8. Data Science and Machine Learning with Hadoop Ecosystem 9. Introduction to Cloud Computing and Other Apache Projects Index |
| gcp master data management: Google Cloud Platform an Architect's Guide Alasdair Gilchrist, Learn fundamental to advanced GCP architectural techniques using 30 + real-world use cases. The 'Google Cloud Platform an Architect's Guide' is a comprehensive handbook that covers everything that you need to know from GCP fundamentals to advanced cloud architecture topics. The book covers what you need to understand to pass the Google certification exams but goes far further and deeper as it explores real-world use cases and business scenarios. But you don't need to be an IT expert as the book is designed to cater for both beginners and those experienced in other cloud or on other on-premises networks. To that end, the book is split into distinct parts that caters for all levels of expertise. Part -1 is aimed at the novice someone new to a cloud architecture environment that needs to become familiar with the fundamentals of cloud architecture and industry best practices so the more experienced reader may wish to skip this section. Part-2 takes a far deeper dive into GCP theory and practice as well as providing real-world use cases and practical tips that are beneficial for architects at all levels. Part-3 delves much deeper into GCP practical theory on elasticity, scalability and resilience. It also covers Kubernetes in greater detail and touches on High-Performance Computing and IoT designs. The book closes with a final part dealing with cloud-native design practices and as such it covers design, monitoring, notification and remediation techniques to ensure best practice in cloud-native application design, deployment, stabilisation and commissioning. |
| gcp master data management: The Data Science Framework Juan J. Cuadrado-Gallego, Yuri Demchenko, 2020-10-01 This edited book first consolidates the results of the EU-funded EDISON project (Education for Data Intensive Science to Open New science frontiers), which developed training material and information to assist educators, trainers, employers, and research infrastructure managers in identifying, recruiting and inspiring the data science professionals of the future. It then deepens the presentation of the information and knowledge gained to allow for easier assimilation by the reader. The contributed chapters are presented in sequence, each chapter picking up from the end point of the previous one. After the initial book and project overview, the chapters present the relevant data science competencies and body of knowledge, the model curriculum required to teach the required foundations, profiles of professionals in this domain, and use cases and applications. The text is supported with appendices on related process models. The book can be used to develop new courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines. |
| gcp master data management: Archiving Clinical Trial Documents Elizabeth Hooper, 2006-06 |
| gcp master data management: Official Google Cloud Certified Professional Cloud Architect Study Guide Dan Sullivan, 2019-10-10 Sybex's proven Study Guide format teaches Google Cloud Architect job skills and prepares you for this important new Cloud exam. The Google Cloud Certified Professional Cloud Architect Study Guide is the essential resource for anyone preparing for this highly sought-after, professional-level certification. Clear and accurate chapters cover 100% of exam objectives—helping you gain the knowledge and confidence to succeed on exam day. A pre-book assessment quiz helps you evaluate your skills, while chapter review questions emphasize critical points of learning. Detailed explanations of crucial topics include analyzing and defining technical and business processes, migration planning, and designing storage systems, networks, and compute resources. Written by Dan Sullivan—a well-known author and software architect specializing in analytics, machine learning, and cloud computing—this invaluable study guide includes access to the Sybex interactive online learning environment, which includes complete practice tests, electronic flash cards, a searchable glossary, and more. Providing services suitable for a wide range of applications, particularly in high-growth areas of analytics and machine learning, Google Cloud is rapidly gaining market share in the cloud computing world. Organizations are seeking certified IT professionals with the ability to deploy and operate infrastructure, services, and networks in the Google Cloud. Take your career to the next level by validating your skills and earning certification. Design and plan cloud solution architecture Manage and provision cloud infrastructure Ensure legal compliance and security standards Understand options for implementing hybrid clouds Develop solutions that meet reliability, business, and technical requirements The Google Cloud Certified Professional Cloud Architect Study Guide is a must-have for IT professionals preparing for certification to deploy and manage Google cloud services. |
| gcp master data management: Google Cloud Associate Cloud Engineer Certification and Implementation Guide Agnieszka Koziorowska, Wojciech Marusiak, 2023-09-29 Gain practical knowledge and hands-on expertise in implementing Google Cloud Platform services and prepare to confidently pass the exam on your first attempt Key Features Explore Google Cloud Platform services and operations in depth Gain hands-on experience to effectively employ Google Cloud services Receive tailored guidance for Associate Cloud Engineer certification from Google experts Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGoogle Cloud Platform (GCP) is a leading cloud provider, helping companies and users worldwide to solve the most challenging business issues. This book will teach cloud engineers working with GCP how to implement, configure, and secure cloud environment, and help students gain confidence in utilizing various GCP services. The book begins by introducing you to Google Cloud and the ACE exam, including various resources that can help you pass. The next set of chapters will help you explore the various compute options in Google Cloud, such as Google Kubernetes Engine and Google Compute Engine. As you advance, you'll gain a clear understanding of the essence of the cloud, including networking and storage, as well as the data analytics products that Google Cloud provides. The chapters also cover key topics such as monitoring, logging, diagnostics, and price estimation along with the most crucial of subjects, security, with a particular focus on identity and access management. Finally, you'll be given the chance to test your newfound knowledge with the help of two mock exams. By the end of this book, you’ll have learned the difference between various Google Cloud Platform services, along with specific use cases, and be able to implement these services with the GCP console and command-line utilities.What you will learn Grasp the key topics needed to achieve ACE certification Import and export data to and from Google Cloud Implement and configure various networking options in Google Cloud Derive insights from data with Google Data Analytics Gain knowledge and experience in monitoring and logging Test yourself in various scenarios while reading the book Choose the optimal options to manage your solution's data Who this book is forThis book is for anyone preparing for Associate Cloud Engineer certification. It can be used by IT system administrators as well as DevOps and it will be most useful to cloud architects as it covers all areas of Google Cloud Platform. This guide is ideal for those who want to start working with Google Cloud, gain practical knowledge, and achieve certification. |
| gcp master data management: Ethical Hacking Andrew D. Chapman, 2023-12-06 In the rapidly evolving digital age, the line between the defenders and those they defend against is thinner than ever. Ethical Hacking is the essential guide for those who dare to challenge this line, ensuring it holds strong against those with malicious intent. This book is a clarion call to all aspiring cybersecurity enthusiasts to arm themselves with the tools and techniques necessary to safeguard the digital frontier. It is a carefully curated repository of knowledge that will take you from understanding the foundational ethics and legalities of hacking into the depths of penetrating and securing complex systems. Within these pages lies a comprehensive walkthrough of the ethical hacker’s arsenal, a deep dive into the world of Kali Linux, and a journey through the stages of a penetration test. The content is rich with practical advice, hands-on exercises, and real-world scenarios that bring the arcane art of ethical hacking into sharp focus. Beyond the technical expertise, Ethical Hacking stands as a testament to the ethical core that is vital to this discipline. It is a beacon of responsibility, guiding you through the dark waters of cybersecurity threats with a steady, ethical hand. Whether you're starting your journey or looking to refine your hacking prowess, this book is an indispensable companion. As the digital landscape continues to shift, let Ethical Hacking be the compass that guides you to becoming a guardian of the cyber world. Your mission begins here. |
| gcp master data management: Principles and Practice of Clinical Trials Steven Piantadosi, Curtis L. Meinert, 2022-07-19 This is a comprehensive major reference work for our SpringerReference program covering clinical trials. Although the core of the Work will focus on the design, analysis, and interpretation of scientific data from clinical trials, a broad spectrum of clinical trial application areas will be covered in detail. This is an important time to develop such a Work, as drug safety and efficacy emphasizes the Clinical Trials process. Because of an immense and growing international disease burden, pharmaceutical and biotechnology companies continue to develop new drugs. Clinical trials have also become extremely globalized in the past 15 years, with over 225,000 international trials ongoing at this point in time. Principles in Practice of Clinical Trials is truly an interdisciplinary that will be divided into the following areas: 1) Clinical Trials Basic Perspectives 2) Regulation and Oversight 3) Basic Trial Designs 4) Advanced Trial Designs 5) Analysis 6) Trial Publication 7) Topics Related Specific Populations and Legal Aspects of Clinical Trials The Work is designed to be comprised of 175 chapters and approximately 2500 pages. The Work will be oriented like many of our SpringerReference Handbooks, presenting detailed and comprehensive expository chapters on broad subjects. The Editors are major figures in the field of clinical trials, and both have written textbooks on the topic. There will also be a slate of 7-8 renowned associate editors that will edit individual sections of the Reference. |
| gcp master data management: Google Cloud Certified Professional Cloud Developer Exam Guide Sebastian Moreno, 2021-09-13 Discover how Google Cloud services can help you to reduce operational tasks and focus on delivering business value with your applications Key FeaturesDesign, develop, and deploy end-to-end cloud-native applications using Google Cloud servicesPrepare for the GCP developer exam with the help of a fictitious business case and a Q&A sectionGet hands-on with implementing code examples of different GCP services in your applicationsBook Description Google Cloud Platform is one of the three major cloud providers in the industry, exhibiting great leadership in application modernization and data management. This book provides a comprehensive introduction for those who are new to cloud development and shows you how to use the tools to create cloud-native applications by integrating the technologies used by Google. The book starts by taking you through the basic programming concepts and security fundamentals necessary for developing in Google Cloud. You'll then discover best practices for developing and deploying applications in the cloud using different components offered by Google Cloud Platform such as Cloud Functions, Google App Engine, Cloud Run, and other GCP technologies. As you advance, you'll learn the basics of cloud storage and choosing the best options for storing different kinds of data as well as understand what site reliability engineers do. In the last part, you'll work on a sample case study of Hip Local, a community application designed to facilitate communication between people nearby, created by the Google Cloud team. By the end of this guide, you'll have learned how to design, develop, and deploy an end-to-end application on the Google Cloud Platform. What you will learnGet to grips with the fundamentals of Google Cloud Platform developmentDiscover security best practices for applications in the cloudFind ways to create and modernize legacy applicationsUnderstand how to manage data and databases in Google CloudExplore best practices for site reliability engineering, monitoring, logging, and debuggingBecome well-versed with the practical implementation of GCP with the help of a case studyWho this book is for This book is for cloud engineers or developers working or starting to work on Google Cloud Platform and looking to take advantage of cloud-native applications. You'll also find this book useful if you are preparing for the GCP developer exam. |
| gcp master data management: Solid State Development and Processing of Pharmaceutical Molecules Michael Gruss, 2021-11-15 Solid State Development and Processing of Pharmaceutical Molecules A guide to the lastest industry principles for optimizing the production of solid state active pharmaceutical ingredients Solid State Development and Processing of Pharmaceutical Molecules is an authoritative guide that covers the entire pharmaceutical value chain. The authors—noted experts on the topic—examine the importance of the solid state form of chemical and biological drugs and review the development, production, quality control, formulation, and stability of medicines. The book explores the most recent trends in the digitization and automation of the pharmaceutical production processes that reflect the need for consistent high quality. It also includes information on relevant regulatory and intellectual property considerations. This resource is aimed at professionals in the pharmaceutical industry and offers an in-depth examination of the commercially relevant issues facing developers, producers and distributors of drug substances. This important book: Provides a guide for the effective development of solid drug forms Compares different characterization methods for solid state APIs Offers a resource for understanding efficient production methods for solid state forms of chemical and biological drugs Includes information on automation, process control, and machine learning as an integral part of the development and production workflows Covers in detail the regulatory and quality control aspects of drug development Written for medicinal chemists, pharmaceutical industry professionals, pharma engineers, solid state chemists, chemical engineers, Solid State Development and Processing of Pharmaceutical Molecules reviews information on the solid state of active pharmaceutical ingredients for their efficient development and production. |
| gcp master data management: AI-Powered Productivity Dr. Asma Asfour, 2024-07-29 This book, AI-Powered Productivity, aims to provide a guide to understanding, utilizing AI and generative tools in various professional settings. The primary purpose of this book is to offer readers a deep dive into the concepts, tools, and practices that define the current AI landscape. From foundational principles to advanced applications, this book is structured to cater to both beginners and professionals looking to enhance their knowledge and skills in AI. This book is divided into nine chapters, each focusing on a specific aspect of AI and its practical applications: Chapter 1 introduces the basic concepts of AI, its impact on various sectors, and key factors driving its rapid advancement, along with an overview of generative AI tools. Chapter 2 delves into large language models like ChatGPT, Google Gemini, Claude, Microsoft's Turing NLG, and Facebook's BlenderBot, exploring their integration with multimodal technologies and their effects on professional productivity. Chapter 3 offers a practical guide to mastering LLM prompting and customization, including tutorials on crafting effective prompts and advanced techniques, as well as real-world examples of AI applications. Chapter 4 examines how AI can enhance individual productivity, focusing on professional and personal benefits, ethical use, and future trends. Chapter 5 addresses data-driven decision- making, covering data analysis techniques, AI in trend identification, consumer behavior analysis, strategic planning, and product development. Chapter 6 discusses strategic and ethical considerations of AI, including AI feasibility, tool selection, multimodal workflows, and best practices for ethical AI development and deployment. Chapter 7 highlights the role of AI in transforming training and professional development, covering structured training programs, continuous learning initiatives, and fostering a culture of innovation and experimentation. Chapter 8 provides a guide to successfully implementing AI in organizations, discussing team composition, collaborative approaches, iterative development processes, and strategic alignment for AI initiatives. Finally, Chapter 9 looks ahead to the future of work, preparing readers for the AI revolution by addressing training and education, career paths, common fears, and future trends in the workforce. The primary audience for the book is professionals seeking to enhance productivity and organizations or businesses. For professionals, the book targets individuals from various industries, reflecting its aim to reach a broad audience across different professional fields. It is designed for employees at all levels, offering valuable insights to both newcomers to AI and seasoned professionals. Covering a range of topics from foundational concepts to advanced applications, the book is particularly relevant for those interested in improving efficiency, with a strong emphasis on practical applications and productivity tools to optimize work processes. For organizations and businesses, the book serves as a valuable resource for decision-makers and managers, especially with chapters on data-driven decision-making, strategic considerations, and AI implementation. HR and training professionals will find the focus on AI in training and development beneficial for talent management, while IT and technology teams will appreciate the information on AI tools and concepts. |
| gcp master data management: The Definitive Guide to Google Vertex AI Jasmeet Bhatia, Kartik Chaudhary, 2023-12-29 Implement machine learning pipelines with Google Cloud Vertex AI Key Features Understand the role of an AI platform and MLOps practices in machine learning projects Get acquainted with Google Vertex AI tools and offerings that help accelerate the creation of end-to-end ML solutions Implement Vision, NLP, and recommendation-based real-world ML models on Google Cloud Platform Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWhile AI has become an integral part of every organization today, the development of large-scale ML solutions and management of complex ML workflows in production continue to pose challenges for many. Google’s unified data and AI platform, Vertex AI, directly addresses these challenges with its array of MLOPs tools designed for overall workflow management. This book is a comprehensive guide that lets you explore Google Vertex AI’s easy-to-advanced level features for end-to-end ML solution development. Throughout this book, you’ll discover how Vertex AI empowers you by providing essential tools for critical tasks, including data management, model building, large-scale experimentations, metadata logging, model deployments, and monitoring. You’ll learn how to harness the full potential of Vertex AI for developing and deploying no-code, low-code, or fully customized ML solutions. This book takes a hands-on approach to developing u deploying some real-world ML solutions on Google Cloud, leveraging key technologies such as Vision, NLP, generative AI, and recommendation systems. Additionally, this book covers pre-built and turnkey solution offerings as well as guidance on seamlessly integrating them into your ML workflows. By the end of this book, you’ll have the confidence to develop and deploy large-scale production-grade ML solutions using the MLOps tooling and best practices from Google.What you will learn Understand the ML lifecycle, challenges, and importance of MLOps Get started with ML model development quickly using Google Vertex AI Manage datasets, artifacts, and experiments Develop no-code, low-code, and custom AI solution on Google Cloud Implement advanced model optimization techniques and tooling Understand pre-built and turnkey AI solution offerings from Google Build and deploy custom ML models for real-world applications Explore the latest generative AI tools within Vertex AI Who this book is for If you are a machine learning practitioner who wants to learn end-to-end ML solution development on Google Cloud Platform using MLOps best practices and tools offered by Google Vertex AI, this is the book for you. |
| gcp master data management: Google Cloud Platform for Architects Vitthal Srinivasan, Janani Ravi, Judy Raj, 2018-06-26 Get acquainted with GCP and manage robust, highly available, and dynamic solutions to drive business objective Key Features Identify the strengths, weaknesses and ideal use-cases for individual services offered on the Google Cloud Platform Make intelligent choices about which cloud technology works best for your use-case Leverage Google Cloud Platform to analyze and optimize technical and business processes Book Description Using a public cloud platform was considered risky a decade ago, and unconventional even just a few years ago. Today, however, use of the public cloud is completely mainstream - the norm, rather than the exception. Several leading technology firms, including Google, have built sophisticated cloud platforms, and are locked in a fierce competition for market share. The main goal of this book is to enable you to get the best out of the GCP, and to use it with confidence and competence. You will learn why cloud architectures take the forms that they do, and this will help you become a skilled high-level cloud architect. You will also learn how individual cloud services are configured and used, so that you are never intimidated at having to build it yourself. You will also learn the right way and the right situation in which to use the important GCP services. By the end of this book, you will be able to make the most out of Google Cloud Platform design. What you will learn Set up GCP account and utilize GCP services using the cloud shell, web console, and client APIs Harness the power of App Engine, Compute Engine, Containers on the Kubernetes Engine, and Cloud Functions Pick the right managed service for your data needs, choosing intelligently between Datastore, BigTable, and BigQuery Migrate existing Hadoop, Spark, and Pig workloads with minimal disruption to your existing data infrastructure, by using Dataproc intelligently Derive insights about the health, performance, and availability of cloud-powered applications with the help of monitoring, logging, and diagnostic tools in Stackdriver Who this book is for If you are a Cloud architect who is responsible to design and manage robust cloud solutions with Google Cloud Platform, then this book is for you. System engineers and Enterprise architects will also find this book useful. A basic understanding of distributed applications would be helpful, although not strictly necessary. Some working experience on other public cloud platforms would help too. |
| gcp master data management: MySQL Text Book Manish Soni, 2024-11-13 This book is your companion on a journey through the intricate and dynamic world of MySQL, an open-source relational database management system that has captivated the hearts of developers, database administrators, and businesses worldwide. |
| gcp master data management: Medical Data Management Florian Leiner, Wilhelm Gaus, Reinhold Haux, Petra Knaup-Gregori, 2006-04-18 Medical Data Management is a systematic introduction to the basic methodology of professional clinical data management. It emphasizes generic methods of medical documentation applicable to such diverse tasks as the electronic patient record, maintaining a clinical trials database, and building a tumor registry. This book is for all students in medical informatics and health information management, and it is ideal for both the undergraduate and the graduate levels. The book also guides professionals in the design and use of clinical information systems in various health care settings. It is an invaluable resource for all health care professionals involved in designing, assessing, adapting, or using clinical data management systems in hospitals, outpatient clinics, study centers, health plans, etc. The book combines a consistent theoretical foundation of medical documentation methods outlining their practical applicability in real clinical data management systems. Two new chapters detail hospital information systems and clinical trials. There is a focus on the international classification of diseases (ICD-9 and -10) systems, as well as a discussion on the difference between the two codes. All chapters feature exercises, bullet points, and a summary to provide the reader with essential points to remember. New to the Third Edition is a comprehensive section comprised of a combined Thesaurus and Glossary which aims to clarify the unclear and sometimes inconsistent terminology surrounding the topic. |
| gcp master data management: Architecting Google Cloud Solutions Victor Dantas, 2021-05-14 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. |
| gcp master data management: Oxford Handbook of Clinical and Healthcare Research Sumantra Ray, Sue Fitzpatrick, Rajna Golubic, Susan Fisher, Sarah Gibbings, 2016-03-03 The Oxford Handbook of Clinical and Healthcare Research is an evidence-based, succinct, and easy-to-use reference for the full range of clinical and healthcare research topics. Providing a wide breadth of essential knowledge, this comprehensive text takes the researcher through the steps from general good clinical practice in healthcare research to the process and management of research. This handbook includes clear instructions on the legislative and practical requirements of commissioning, conducting, analysing, and reporting research for those in clinical or healthcare practice, education, or training. Written with Good Clinical Practice (GCP) education in mind, it includes valuable information needed for the accredited certificates and diploma-level benchmark exams now commonly required by employers. This is a definitive text for all clinical and healthcare research students, as well as graduates with an interest in clinical and healthcare research. |
| gcp master data management: Multi-Cloud Architecture and Governance Jeroen Mulder, 2020-12-11 A comprehensive guide to architecting, managing, implementing, and controlling multi-cloud environments Key Features Deliver robust multi-cloud environments and improve your business productivity Stay in control of the cost, governance, development, security, and continuous improvement of your multi-cloud solution Integrate different solutions, principles, and practices into one multi-cloud foundation Book DescriptionMulti-cloud has emerged as one of the top cloud computing trends, with businesses wanting to reduce their reliance on only one vendor. But when organizations shift to multiple cloud services without a clear strategy, they may face certain difficulties, in terms of how to stay in control, how to keep all the different components secure, and how to execute the cross-cloud development of applications. This book combines best practices from different cloud adoption frameworks to help you find solutions to these problems. With step-by-step explanations of essential concepts and practical examples, you’ll begin by planning the foundation, creating the architecture, designing the governance model, and implementing tools, processes, and technologies to manage multi-cloud environments. You’ll then discover how to design workload environments using different cloud propositions, understand how to optimize the use of these cloud technologies, and automate and monitor the environments. As you advance, you’ll delve into multi-cloud governance, defining clear demarcation models and management processes. Finally, you’ll learn about managing identities in multi-cloud: who’s doing what, why, when, and where. By the end of this book, you’ll be able to create, implement, and manage multi-cloud architectures with confidenceWhat you will learn Get to grips with the core functions of multiple cloud platforms Deploy, automate, and secure different cloud solutions Design network strategy and get to grips with identity and access management for multi-cloud Design a landing zone spanning multiple cloud platforms Use automation, monitoring, and management tools for multi-cloud Understand multi-cloud management with the principles of BaseOps, FinOps, SecOps, and DevOps Define multi-cloud security policies and use cloud security tools Test, integrate, deploy, and release using multi-cloud CI/CD pipelines Who this book is for This book is for architects and lead engineers involved in architecting multi-cloud environments, with a focus on getting governance right to stay in control of developments in multi-cloud. Basic knowledge of different cloud platforms (Azure, AWS, GCP, VMWare, and OpenStack) and understanding of IT governance is necessary. |
| gcp master data management: Business Intelligence Career Master Plan Eduardo Chavez, Danny Moncada, 2023-08-31 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. |
| gcp master data management: Official Google Cloud Certified Associate Cloud Engineer Study Guide Dan Sullivan, 2019-04-01 The Only Official Google Cloud Study Guide The Official Google Cloud Certified Associate Cloud Engineer Study Guide, provides everything you need to prepare for this important exam and master the skills necessary to land that coveted Google Cloud Engineering 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, Official Google Cloud Certified Associate Cloud Engineer Study Guide is your ace in the hole for deploying and managing Google Cloud Services. Select the right Google service from the various choices based on the application to be built Compute with Cloud VMs and managing VMs Plan and deploying storage Network and configure access and security Google Cloud Platform is a leading public cloud that provides its users to many of the same software, hardware, and networking infrastructure used to power Google services. Businesses, organizations, and individuals can launch servers in minutes, store petabytes of data, and implement global virtual clouds with the Google Cloud Platform. Certified Associate Cloud Engineers have demonstrated the knowledge and skills needed to deploy and operate infrastructure, services, and networks in the Google Cloud. This exam guide is designed to help you understand the Google Cloud Platform in depth so that you can meet the needs of those operating resources in the Google Cloud. |
| gcp master data management: Machine Learning in Production Suhas Pote, 2023-04-29 Deploy, manage, and scale Machine Learning models with MLOps effortlessly KEY FEATURES ● Explore several ways to build and deploy ML models in production using an automated CI/CD pipeline. ● Develop and convert ML apps into Android and Windows apps. ● Learn how to implement ML model deployment on popular cloud platforms, including Azure, GCP, and AWS. DESCRIPTION ‘Machine Learning in Production’ is an attempt to decipher the path to a remarkable career in the field of MLOps. It is a comprehensive guide to managing the machine learning lifecycle from development to deployment, outlining ways in which you can deploy ML models in production. It starts off with fundamental concepts, an introduction to the ML lifecycle and MLOps, followed by comprehensive step-by-step instructions on how to develop a package for ML code from scratch that can be installed using pip. It then covers MLflow for ML life cycle management, CI/CD pipelines, and shows how to deploy ML applications on Azure, GCP, and AWS. Furthermore, it provides guidance on how to convert Python applications into Android and Windows apps, as well as how to develop ML web apps. Finally, it covers monitoring, the critical topic of machine learning attacks, and A/B testing. With this book, you can easily build and deploy machine learning solutions in production. WHAT YOU WILL LEARN ● Master the Machine Learning lifecycle with MLOps. ● Learn best practices for managing ML models at scale. ● Streamline your ML workflow with MLFlow. ● Implement monitoring solutions using whylogs, WhyLabs, Grafana, and Prometheus. ● Use Docker and Kubernetes for ML deployment. WHO THIS BOOK IS FOR Whether you are a Data scientist, ML engineer, DevOps professional, Software engineer, or Cloud architect, this book will help you get your machine learning models into production quickly and efficiently. TABLE OF CONTENTS 1. Python 101 2. Git and GitHub Fundamentals 3. Challenges in ML Model Deployment 4. Packaging ML Models 5. MLflow-Platform to Manage the ML Life Cycle 6. Docker for ML 7. Build ML Web Apps Using API 8. Build Native ML Apps 9. CI/CD for ML 10. Deploying ML Models on Heroku 11. Deploying ML Models on Microsoft Azure 12. Deploying ML Models on Google Cloud Platform 13. Deploying ML Models on Amazon Web Services 14. Monitoring and Debugging 15. Post-Productionizing ML Models |
| gcp master data management: Data Analytics for Internet of Things Infrastructure Rohit Sharma, Gwanggil Jeon, Yan Zhang, 2023-09-19 This book provides techniques for the deployment of semantic technologies in data analysis along with the latest applications across the field such as Internet of Things (IoT). The authors focus on the use of the IoT and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. They discuss how the generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends the adoption of data analytics to strengthen solutions. The book addresses the challenges in designing the web based IoT system, provides a comparative analysis of different advanced approaches in industries, and contains an analysis of databases to provide expert systems. The book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of IoT and big data analytics. |
| gcp master data management: Cloud Computing For Dummies Judith S. Hurwitz, Daniel Kirsch, 2020-07-07 Get your head—and your business—into the Cloud Cloud computing is no longer just a clever new toy in the world of IT infrastructure. Despite the nebulous name, it’s become a real and important part of our information architecture—and tech professionals who ignore it or try to skim their way through risk falling behind rapidly. The new edition of Cloud Computing For Dummies gets you up to speed fast, clarifying your Cloud options, showing you where can save you time and money, giving you ways to frame your decisions, and helping you avoid weeks of research. In a friendly, easy-to-follow style, Cloud Computing For Dummies, 2nd Edition demystifies the Cloud’s virtual landscape, breaking up a complex and multi-layered topic into simple explanations that will make the various benefits clear and ultimately guide you toward making the most appropriate choices for your organization. Know the business case for the Cloud Understand hybrid and multi-cloud options Develop your Cloud strategy Get tips on best practices The Cloud is everywhere, and it can deliver amazing benefits to our lives and businesses. Get a much clearer vision of exactly how with Cloud Computing For Dummies—and you’ll begin to see that the sky really is the limit! |
| gcp master data management: Fraud and Misconduct in Biomedical Research, 4th edition Frank Wells, Michael Farthing, 2019-03-14 Now in its fourth edition, Fraud and Misconduct in Biomedical Research boasts an impressive list of contributors from around the globe and introduces a new focus for the book, transforming it from a series of monographs into a publication that will quickly become an essential textbook on all areas of research fraud and misconduct.Key features inclu |
| gcp master data management: Professional Cloud Architect Google Cloud Certification Guide Konrad Clapa, Brian Gerrard, Yujun Liang, 2021-12-23 Become a Professional Cloud Architect by exploring the essential concepts, tools, and services in GCP and working through practice tests designed to help you take the exam confidently Key FeaturesPlan and design a GCP cloud solution architectureEnsure the security and reliability of your cloud solutions and operationsAssess your knowledge by taking mock tests with up-to-date exam questionsBook Description Google Cloud Platform (GCP) is one of the industry leaders thanks to its array of services that can be leveraged by organizations to bring the best out of their infrastructure. This book is a comprehensive guide for learning methods to effectively utilize GCP services and help you become acquainted with the topics required to pass Google's Professional Cloud Architect certification exam. Following the Professional Cloud Architect's official exam syllabus, you'll first be introduced to the GCP. The book then covers the core services that GCP offers, such as computing and storage, and takes you through effective methods of scaling and automating your cloud infrastructure. As you progress through the chapters, you'll get to grips with containers and services and discover best practices related to the design and process. This revised second edition features new topics such as Cloud Run, Anthos, Data Fusion, Composer, and Data Catalog. By the end of this book, you'll have gained the knowledge required to take and pass the Google Cloud Certification – Professional Cloud Architect exam and become an expert in GCP services. What you will learnUnderstand the benefits of being a Google Certified Professional Cloud ArchitectFind out how to enroll for the Professional Cloud Architect examMaster the compute options in GCPExplore security and networking options in GCPGet to grips with managing and monitoring your workloads in GCPUnderstand storage, big data, and machine learning servicesBecome familiar with exam scenarios and passing strategiesWho this book is for If you are a cloud architect, cloud engineer, administrator, or any IT professional looking to learn how to implement Google Cloud services in your organization and become a GCP Certified Professional Cloud Architect, this book is for you. Basic knowledge of server infrastructure, including Linux and Windows Servers, is assumed. A solid understanding of network and storage will help you to make the most out of this book. |
| gcp master data management: Global Clinical Trials Playbook Menghis Bairu, Richard Chin, 2012-04-20 Pharmaceuticals companies, biotech companies, and CROs, regardless of size, all face the same challenge of managing costs and operational execution associated with bringing a valuable drugs and devices to market. Because of timeline pressures and cost as well as the growing interest in neglected diseases and diseases affecting the emerging nations, clinical trials are increasingly conducted in emerging markets and developing countries where infrastructure, leadership, skilled personnel and a governance are at a premium. Working with academics, regulatory professionals, safety officers, experts from the pharma industry and CROs, the editors have put together this up-to-date, step-by-step guide book to building and enhancing global clinical trial capacity in emerging markets and developing countries. This book covers the design, conduct, and tools to build and/or enhance human capacity to execute such trials, appealing to individuals in health ministries, pharmaceutical companies, world health organizations, academia, industry, and non-governmental organizations (NGOs) who are managing global clinical trials. Gives medical professionals the business tools needed to effectively execute clinical trials throughout the world Provides real world international examples which illustrate the practical translation of principles Includes forms, templates, and additional references for standardization in a number of global scenarios |
| gcp master data management: The Definitive Guide to Data Integration Pierre-Yves BONNEFOY, Emeric CHAIZE, Raphaël MANSUY, Mehdi TAZI, 2024-03-29 Learn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stack Key Features Learn how to leverage modern data stack tools and technologies for effective data integration Design and implement data integration solutions with practical advice and best practices Focus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologies Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.What you will learn Discover the evolving architecture and technologies shaping data integration Process large data volumes efficiently with data warehousing Tackle the complexities of integrating large datasets from diverse sources Harness the power of data warehousing for efficient data storage and processing Design and optimize effective data integration solutions Explore data governance principles and compliance requirements Who this book is for This book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you’re a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape. |
| gcp master data management: Thesis Writing for Master's and Ph.D. Program Subhash Chandra Parija, Vikram Kate, 2018-11-03 This book on Thesis Writing for Master’s and Ph.D. program focuses on the difficulties students encounter with regard to choosing a guide; selecting an appropriate research title considering the available resources; conducting research; and ways to overcome the hardships they face while researching, writing and preparing their dissertation for submission. Thesis writing is an essential skill that medical and other postgraduates are expected to learn during their academic career as a mandatory partial requirement in order to receive the Master’s degree. However, at the majority of medical schools, writing a thesis is largely based on self-learning, which adds to the burden on students due to the tremendous amount of time spent learning the writing skills in addition to their exhausting clinical and academic work. Due to the difficulties faced during the early grooming years and lack of adequate guidance, acquiring writing skills continues to be a daunting task for most students. This book addresses these difficulties and deficiencies and provides comprehensive guidance, from selecting the research title to publishing in a scientific journal. |
| gcp master data management: Guide for Investigator Initiated Trials Gerhard Fortwengel, 2011 An essential manual for beginners and senior researchers alike For academic medical faculty unfamiliar with national and international regulations, the prospect of initiating and managing a clinical trial can be intimidating. The development of protocols and case report forms, compliance with regulatory requirements, the monitoring of clinical trials as well as the responsibilities of documentation are just some of the tasks the sponsor-investigator is faced with. This book covers the entire spectrum of a clinical trial, reviewing the different stages step by step: financial planning, crucial aspects of trial design, the authorization process and, finally, documentation. Moreover, it contains helpful tips, a practical glossary, instructions and a large number of resources related to the relevant regulations and forms conforming to the International Conference on Harmonization and Good Clinical Practice'. This makes the publication at hand an essential cookbook' for both academic faculty new to clinical trials as well as seasoned sponsors-investigators. |
| gcp master data management: Official Google Cloud Certified Professional Cloud Security Engineer Exam Guide Ankush Chowdhary, Prashant Kulkarni, 2023-08-30 Master the art of designing, developing, and operating secure infrastructures on Google Cloud Key Features Prepare for the certification exam with clear explanations, real-world examples, and self-assessment questions Review Google Cloud security best practices for building a secure and compliant cloud environment Explore advanced concepts like Security Command Center, BeyondCorp Zero Trust, and container security Book DescriptionGoogle Cloud security offers powerful controls to assist organizations in establishing secure and compliant cloud environments. With this book, you’ll gain in-depth knowledge of the Professional Cloud Security Engineer certification exam objectives, including Google Cloud security best practices, identity and access management (IAM), network security, data security, and security operations. The chapters go beyond the exam essentials, helping you explore advanced topics such as Google Cloud Security Command Center, the BeyondCorp Zero Trust architecture, and container security. With step-by-step explanations, practical examples, and practice exams to help you improve your skills for the exam, you'll be able to efficiently review and apply key concepts of the shared security responsibility model. Finally, you’ll get to grips with securing access, organizing cloud resources, network and data security, and logging and monitoring. By the end of this book, you'll be proficient in designing, developing, and operating security controls on Google Cloud and gain insights into emerging concepts for future exams.What you will learn Understand how Google secures infrastructure with shared responsibility Use resource hierarchy for access segregation and implementing policies Utilize Google Cloud Identity for authentication and authorizations Build secure networks with advanced network features Encrypt/decrypt data using Cloud KMS and secure sensitive data Gain visibility and extend security with Google's logging and monitoring capabilities Who this book is forThis book is for IT professionals, cybersecurity specialists, system administrators, and tech enthusiasts aspiring to strengthen their understanding of Google Cloud security and elevate their career trajectory. Earning this certification not only validates your expertise but also makes you part of an elite group of GCP security engineers, opening doors to opportunities that can significantly advance your career. Prior knowledge of the foundational concepts of Google Cloud or GCP Associate Engineer Certification is strongly recommended. |
| gcp master data management: Guide to EU and UK Pharmaceutical Regulatory Law Sally Shorthose, 2023-01-10 In the European Union (EU), its Member States and the United Kingdom (UK) post-Brexit, as elsewhere, the marketing of pharmaceuticals is subject to an ever more complex web of legislation and regulation, resulting from the intense scrutiny necessary to ensure such essential products are not only efficacious but also safe. This useful volume lays out this system with extraordinary clarity and logic. Adopting a Europe-wide perspective on the law governing pharmaceuticals, expert authors from the law firm Bird & Bird LLP map the life cycle of a medicinal product or medical device from development to clinical trials to product launch and ongoing pharmacovigilance, offering comprehensive and unambiguous guidance at every stage. Following a brief overview of how the exit from the EU by the UK currently affects the regulatory regime, as well as an introductory overview focusing on the regulatory framework for pharmaceuticals in Europe – from its underlying rationales to the relevant committees and agencies – each of the following twenty-one incisive chapters examines a particular process or subject. Among the many topics and issues covered from both an EU and UK perspective are the following: clinical trials; stages and standards for creating a product dossier; obtaining a marketing authorisation; how and when an abridged marketing authorisation procedure can be used; criteria for conditional marketing authorisations; generic products and ‘essential similarity’; paediatric use and the requisite additional trials; orphan medicinal products; biologicals and ‘biosimilars’; homeopathic, herbal and similar medicines; medical devices; pandemics, epidemics and vaccines; pharmacovigilance; parallel trade; advertising; and relevant competition law, intellectual property rights and data protection regulation. In addition, sample forms and URLs for the most important reference materials are included. Pharmaceutical lawyers and regulatory advisers, both in-house and in private practice, will welcome this unique book. It offers immeasurable value for all who need to understand the process of bringing a medicinal product or medical device to market and the continuing rights and obligations. |
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Spend smart, procure faster and retire committed Google Cloud spend with Google Cloud Marketplace. Browse the catalog of over 2000 SaaS, VMs, development stacks, and …
GCP Marketplace - Google Cloud Platform
A new version of the Google Cloud Marketplace Terms of Service is available. If the page does not automatically redirect, please click here https://cloud.google.com ...
Google Cloud Platform
Google Cloud Platform lets you build, deploy, and scale applications, websites, and services on the same infrastructure as Google.
Google Cloud Platform
Google Cloud Platform enables you to build, deploy, and scale applications using Google's infrastructure.
Google Cloud console
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Google Cloud console
Google Cloud コンソールで、クラウドアプリケーションを構築および管理できます。
Google Cloud console
Spend smart, procure faster and retire committed Google Cloud spend with Google Cloud Marketplace. Browse the catalog of over 2000 SaaS, VMs, development stacks, and …
GCP Marketplace - Google Cloud Platform
A new version of the Google Cloud Marketplace Terms of Service is available. If the page does not automatically redirect, please click here https://cloud.google.com ...
