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| cloud data engineering for dummies: Cloud Computing For Dummies Judith S. Hurwitz, Robin Bloor, Marcia Kaufman, Fern Halper, 2010-01-19 The easy way to understand and implement cloud computing technology written by a team of experts Cloud computing can be difficult to understand at first, but the cost-saving possibilities are great and many companies are getting on board. If you've been put in charge of implementing cloud computing, this straightforward, plain-English guide clears up the confusion and helps you get your plan in place. You'll learn how cloud computing enables you to run a more green IT infrastructure, and access technology-enabled services from the Internet (in the cloud) without having to understand, manage, or invest in the technology infrastructure that supports them. You'll also find out what you need to consider when implementing a plan, how to handle security issues, and more. Cloud computing is a way for businesses to take advantage of storage and virtual services through the Internet, saving money on infrastructure and support This book provides a clear definition of cloud computing from the utility computing standpoint and also addresses security concerns Offers practical guidance on delivering and managing cloud computing services effectively and efficiently Presents a proactive and pragmatic approach to implementing cloud computing in any organization Helps IT managers and staff understand the benefits and challenges of cloud computing, how to select a service, and what's involved in getting it up and running Highly experienced author team consults and gives presentations on emerging technologies Cloud Computing For Dummies gets straight to the point, providing the practical information you need to know. |
| cloud data engineering for dummies: Data Warehousing For Dummies Thomas C. Hammergren, 2009-04-13 Data warehousing is one of the hottest business topics, and there’s more to understanding data warehousing technologies than you might think. Find out the basics of data warehousing and how it facilitates data mining and business intelligence with Data Warehousing For Dummies, 2nd Edition. Data is probably your company’s most important asset, so your data warehouse should serve your needs. The fully updated Second Edition of Data Warehousing For Dummies helps you understand, develop, implement, and use data warehouses, and offers a sneak peek into their future. You’ll learn to: Analyze top-down and bottom-up data warehouse designs Understand the structure and technologies of data warehouses, operational data stores, and data marts Choose your project team and apply best development practices to your data warehousing projects Implement a data warehouse, step by step, and involve end-users in the process Review and upgrade existing data storage to make it serve your needs Comprehend OLAP, column-wise databases, hardware assisted databases, and middleware Use data mining intelligently and find what you need Make informed choices about consultants and data warehousing products Data Warehousing For Dummies, 2nd Edition also shows you how to involve users in the testing process and gain valuable feedback, what it takes to successfully manage a data warehouse project, and how to tell if your project is on track. You’ll find it’s the most useful source of data on the topic! |
| cloud data engineering for dummies: Official Google Cloud Certified Professional Data Engineer Study Guide Dan Sullivan, 2020-06-10 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. |
| cloud data engineering for dummies: Data Engineering with Google Cloud Platform Adi Wijaya, 2022-03-31 Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book. |
| cloud data engineering for dummies: Big Data For Dummies Judith S. Hurwitz, Alan Nugent, Fern Halper, Marcia Kaufman, 2013-04-02 Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization. |
| cloud data engineering for dummies: Cloud Computing for Science and Engineering Ian Foster, Dennis B. Gannon, 2017-09-29 A guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. The book is accompanied by a website, Cloud4SciEng.org, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors. |
| cloud data engineering for dummies: Data Science For Dummies Lillian Pierson, 2021-08-20 Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today. |
| cloud data engineering for dummies: DevOps For Dummies Emily Freeman, 2019-08-20 Develop faster with DevOps DevOps embraces a culture of unifying the creation and distribution of technology in a way that allows for faster release cycles and more resource-efficient product updating. DevOps For Dummies provides a guidebook for those on the development or operations side in need of a primer on this way of working. Inside, DevOps evangelist Emily Freeman provides a roadmap for adopting the management and technology tools, as well as the culture changes, needed to dive head-first into DevOps. Identify your organization’s needs Create a DevOps framework Change your organizational structure Manage projects in the DevOps world DevOps For Dummies is essential reading for developers and operations professionals in the early stages of DevOps adoption. |
| cloud data engineering for dummies: Big Data, Cloud Computing, Data Science & Engineering Roger Lee, 2018-08-13 This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science. |
| cloud data engineering for dummies: 97 Things Every Cloud Engineer Should Know Emily Freeman, Nathen Harvey, 2020-12-04 If you create, manage, operate, or configure systems running in the cloud, you're a cloud engineer--even if you work as a system administrator, software developer, data scientist, or site reliability engineer. With this book, professionals from around the world provide valuable insight into today's cloud engineering role. These concise articles explore the entire cloud computing experience, including fundamentals, architecture, and migration. You'll delve into security and compliance, operations and reliability, and software development. And examine networking, organizational culture, and more. You're sure to find 1, 2, or 97 things that inspire you to dig deeper and expand your own career. Three Keys to Making the Right Multicloud Decisions, Brendan O'Leary Serverless Bad Practices, Manases Jesus Galindo Bello Failing a Cloud Migration, Lee Atchison Treat Your Cloud Environment as If It Were On Premises, Iyana Garry What Is Toil, and Why Are SREs Obsessed with It?, Zachary Nickens Lean QA: The QA Evolving in the DevOps World, Theresa Neate How Economies of Scale Work in the Cloud, Jon Moore The Cloud Is Not About the Cloud, Ken Corless Data Gravity: The Importance of Data Management in the Cloud, Geoff Hughes Even in the Cloud, the Network Is the Foundation, David Murray Cloud Engineering Is About Culture, Not Containers, Holly Cummins |
| cloud data engineering for dummies: Designing Cloud Data Platforms Danil Zburivsky, Lynda Partner, 2021-04-20 Centralized data warehouses, the long-time defacto standard for housing data for analytics, are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services. Designing Cloud Data Platforms is an hands-on guide to envisioning and designing a modern scalable data platform that takes full advantage of the flexibility of the cloud. As you read, you''ll learn the core components of a cloud data platform design, along with the role of key technologies like Spark and Kafka Streams. You''ll also explore setting up processes to manage cloud-based data, keep it secure, and using advanced analytic and BI tools to analyse it. about the technology Access to affordable, dependable, serverless cloud services has revolutionized the way organizations can approach data management, and companies both big and small are raring to migrate to the cloud. But without a properly designed data platform, data in the cloud can remain just as siloed and inaccessible as it is today for most organizations. Designing Cloud Data Platforms lays out the principles of a well-designed platform that uses the scalable resources of the public cloud to manage all of an organization''s data, and present it as useful business insights. about the book In Designing Cloud Data Platforms, you''ll learn how to integrate data from multiple sources into a single, cloud-based, modern data platform. Drawing on their real-world experiences designing cloud data platforms for dozens of organizations, cloud data experts Danil Zburivsky and Lynda Partner take you through a six-layer approach to creating cloud data platforms that maximizes flexibility and manageability and reduces costs. Starting with foundational principles, you''ll learn how to get data into your platform from different databases, files, and APIs, the essential practices for organizing and processing that raw data, and how to best take advantage of the services offered by major cloud vendors. As you progress past the basics you''ll take a deep dive into advanced topics to get the most out of your data platform, including real-time data management, machine learning analytics, schema management, and more. what''s inside The tools of different public cloud for implementing data platforms Best practices for managing structured and unstructured data sets Machine learning tools that can be used on top of the cloud Cost optimization techniques about the reader For data professionals familiar with the basics of cloud computing and distributed data processing systems like Hadoop and Spark. about the authors Danil Zburivsky has over 10 years experience designing and supporting large-scale data infrastructure for enterprises across the globe. Lynda Partner is the VP of Analytics-as-a-Service at Pythian, and has been on the business side of data for over 20 years. |
| cloud data engineering for dummies: Ahead in the Cloud Stephen Orban, 2018-03-27 Cloud computing is the most significant technology development of our lifetimes. It has made countless new businesses possible and presents a massive opportunity for large enterprises to innovate like startups and retire decades of technical debt. But making the most of the cloud requires much more from enterprises than just a technology change. Stephen Orban led Dow Jones's journey toward digital agility as their CIO and now leads AWS's Enterprise Strategy function, where he helps leaders from the largest companies in the world transform their businesses. As he demonstrates in this book, enterprises must re-train their people, evolve their processes, and transform their cultures as they move to the cloud. By bringing together his experiences and those of a number of business leaders, Orban shines a light on what works, what doesn't, and how enterprises can transform themselves using the cloud. |
| cloud data engineering for dummies: CCSP For Dummies with Online Practice Arthur J. Deane, 2020-09-29 Secure your CSSP certification CCSP is the world’s leading Cloud Security certification. It covers the advanced technical skills and knowledge to design, manage, and secure data, applications, and infrastructure in the cloud using best practices, policies, and procedures. If you’re a cloud security professional seeking your CSSP certification, this book is a perfect way to prepare for the exam. Covering in detail all six domains, the expert advice in this book gives you key information you'll need to pass the exam. In addition to the information covered on the exam, you'll get tips on setting up a study plan, tips for exam day, and access to an online test bank of questions. Key information for all six exam domains Test -taking and exam day tips and tricks Free online practice questions and flashcards Coverage of the core concepts From getting familiar with the core concepts to establishing a study plan, this book is all you need to hang your hat on that certification! |
| cloud data engineering for dummies: Sailing For Dummies J. J. Isler, Peter Isler, 2011-03-03 Interested in learning to sail but feel like you’re navigating in murky waters? Sailing for Dummies, Second Edition introduces the basics of sailing, looks at the different types of sailboats and their basic parts, and teaches you everything you need to know before you leave the dock. In Sailing for Dummies, Second Edition, two U.S. sailing champions show you how to: Find and choose a sailing school Use life jackets correctly Tie ten nautical knots Handle sailing emergencies (such as capsizing and rescuing a man overboard) Launch your boat from a trailer, ramp, or beach Get your boat from point A to point B (and back again) Predict and respond to water and wind conditions Read charts, plot your course, use a compass, and find your position at sea Sailing for Dummies shows you that getting out on the water is easier than you think. The authors keep the sailor-speak to a minimum where possible, but give you a grasp of the terminology you need to safely and effectively communicate with your crew. A textbook, user’s manual, and reference all in one, this book takes the intimidation out of sailing and gives you the skills and confidence you need to get your feet wet and become the sailing pro you’ve always wanted to be. Anchors away! |
| cloud data engineering for dummies: 97 Things Every Data Engineer Should Know Tobias Macey, 2021-06-11 Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail |
| cloud data engineering for dummies: Cloud Computing Thomas Erl, Ricardo Puttini, Zaigham Mahmood, 2013-05-02 Clouds are distributed technology platforms that leverage sophisticated technology innovations to provide highly scalable and resilient environments that can be remotely utilized by organizations in a multitude of powerful ways. To successfully build upon, integrate with, or even create a cloud environment requires an understanding of its common inner mechanics, architectural layers, and models, as well as an understanding of the business and economic factors that result from the adoption and real-world use of cloud-based services. In Cloud Computing: Concepts, Technology & Architecture, Thomas Erl, one of the world’s top-selling IT authors, teams up with cloud computing experts and researchers to break down proven and mature cloud computing technologies and practices into a series of well-defined concepts, models, technology mechanisms, and technology architectures, all from an industry-centric and vendor-neutral point of view. In doing so, the book establishes concrete, academic coverage with a focus on structure, clarity, and well-defined building blocks for mainstream cloud computing platforms and solutions. Subsequent to technology-centric coverage, the book proceeds to establish business-centric models and metrics that allow for the financial assessment of cloud-based IT resources and their comparison to those hosted on traditional IT enterprise premises. Also provided are templates and formulas for calculating SLA-related quality-of-service values and numerous explorations of the SaaS, PaaS, and IaaS delivery models. With more than 260 figures, 29 architectural models, and 20 mechanisms, this indispensable guide provides a comprehensive education of cloud computing essentials that will never leave your side. |
| cloud data engineering for dummies: Guide to Cloud Computing Richard Hill, Laurie Hirsch, Peter Lake, Siavash Moshiri, 2012-11-28 This book describes the landscape of cloud computing from first principles, leading the reader step-by-step through the process of building and configuring a cloud environment. The book not only considers the technologies for designing and creating cloud computing platforms, but also the business models and frameworks in real-world implementation of cloud platforms. Emphasis is placed on “learning by doing,” and readers are encouraged to experiment with a range of different tools and approaches. Topics and features: includes review questions, hands-on exercises, study activities and discussion topics throughout the text; demonstrates the approaches used to build cloud computing infrastructures; reviews the social, economic, and political aspects of the on-going growth in cloud computing use; discusses legal and security concerns in cloud computing; examines techniques for the appraisal of financial investment into cloud computing; identifies areas for further research within this rapidly-moving field. |
| cloud data engineering for dummies: Data Engineering on Azure Vlad Riscutia, 2021-08-17 Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure. Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data |
| cloud data engineering for dummies: 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. |
| cloud data engineering for dummies: Security Engineering for Cloud Computing: Approaches and Tools Rosado, David G., 2012-09-30 This book provides a theoretical and academic description of Cloud security issues, methods, tools and trends for developing secure software for Cloud services and applications--Provided by publisher. |
| cloud data engineering for dummies: Azure Data Engineering Cookbook Ahmad Osama, 2021-04-05 Over 90 recipes to help you orchestrate modern ETL/ELT workflows and perform analytics using Azure services more easily Key FeaturesBuild highly efficient ETL pipelines using the Microsoft Azure Data servicesCreate and execute real-time processing solutions using Azure Databricks, Azure Stream Analytics, and Azure Data ExplorerDesign and execute batch processing solutions using Azure Data FactoryBook Description Data engineering is one of the faster growing job areas as Data Engineers are the ones who ensure that the data is extracted, provisioned and the data is of the highest quality for data analysis. This book uses various Azure services to implement and maintain infrastructure to extract data from multiple sources, and then transform and load it for data analysis. It takes you through different techniques for performing big data engineering using Microsoft Azure Data services. It begins by showing you how Azure Blob storage can be used for storing large amounts of unstructured data and how to use it for orchestrating a data workflow. You'll then work with different Cosmos DB APIs and Azure SQL Database. Moving on, you'll discover how to provision an Azure Synapse database and find out how to ingest and analyze data in Azure Synapse. As you advance, you'll cover the design and implementation of batch processing solutions using Azure Data Factory, and understand how to manage, maintain, and secure Azure Data Factory pipelines. You'll also design and implement batch processing solutions using Azure Databricks and then manage and secure Azure Databricks clusters and jobs. In the concluding chapters, you'll learn how to process streaming data using Azure Stream Analytics and Data Explorer. By the end of this Azure book, you'll have gained the knowledge you need to be able to orchestrate batch and real-time ETL workflows in Microsoft Azure. What you will learnUse Azure Blob storage for storing large amounts of unstructured dataPerform CRUD operations on the Cosmos Table APIImplement elastic pools and business continuity with Azure SQL DatabaseIngest and analyze data using Azure Synapse AnalyticsDevelop Data Factory data flows to extract data from multiple sourcesManage, maintain, and secure Azure Data Factory pipelinesProcess streaming data using Azure Stream Analytics and Data ExplorerWho this book is for This book is for Data Engineers, Database administrators, Database developers, and extract, load, transform (ETL) developers looking to build expertise in Azure Data engineering using a recipe-based approach. Technical architects and database architects with experience in designing data or ETL applications either on-premise or on any other cloud vendor who wants to learn Azure Data engineering concepts will also find this book useful. Prior knowledge of Azure fundamentals and data engineering concepts is needed. |
| cloud data engineering for dummies: Smart Grid Technology Sudip Misra, Samaresh Bera, 2018-07-12 Discusses concepts of smart grid technologies, from the perspective of integration with cloud computing and data management approaches. |
| cloud data engineering for dummies: Data Science on the Google Cloud Platform Valliappa Lakshmanan, 2017-12-12 Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you’ll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You’ll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines |
| cloud data engineering for dummies: Software Engineering in IoT, Big Data, Cloud and Mobile Computing Haengkon Kim, Roger Lee, 2020-12-26 This edited book presents scientific results of the International Semi-Virtual Workshop on Software Engineering in IoT, Big data, Cloud and Mobile Computing (SE-ICBM 2020) which was held on October 15, 2020, at Soongsil University, Seoul, Korea. The aim of this workshop was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The workshop organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 17 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science. |
| cloud data engineering for dummies: Machining For Dummies Kip Hanson, 2017-11-06 Start a successful career in machining Metalworking is an exciting field that's currently experiencing a shortage of qualified machinists—and there's no time like the present to capitalize on the recent surge in manufacturing and production opportunities. Covering everything from lathe operation to actual CNC programming, Machining For Dummies provides you with everything it takes to make a career for yourself as a skilled machinist. Written by an expert offering real-world advice based on experience in the industry, this hands-on guide begins with basic topics like tools, work holding, and ancillary equipment, then goes into drilling, milling, turning, and other necessary metalworking processes. You'll also learn about robotics and new developments in machining technology that are driving the future of manufacturing and the machining market. Be profitable in today's competitive manufacturing environment Set up and operate a variety of computer-controlled and mechanically controlled machines Produce precision metal parts, instruments, and tools Become a part of an industry that's experiencing steady growth Manufacturing is the backbone of America, and this no-nonsense guide will provide you with valuable information to help you get a foot in the door as a machinist. |
| cloud data engineering for dummies: Cloud Computing Dan C. Marinescu, 2013-05-30 Cloud Computing: Theory and Practice provides students and IT professionals with an in-depth analysis of the cloud from the ground up. Beginning with a discussion of parallel computing and architectures and distributed systems, the book turns to contemporary cloud infrastructures, how they are being deployed at leading companies such as Amazon, Google and Apple, and how they can be applied in fields such as healthcare, banking and science. The volume also examines how to successfully deploy a cloud application across the enterprise using virtualization, resource management and the right amount of networking support, including content delivery networks and storage area networks. Developers will find a complete introduction to application development provided on a variety of platforms. - Learn about recent trends in cloud computing in critical areas such as: resource management, security, energy consumption, ethics, and complex systems - Get a detailed hands-on set of practical recipes that help simplify the deployment of a cloud based system for practical use of computing clouds along with an in-depth discussion of several projects - Understand the evolution of cloud computing and why the cloud computing paradigm has a better chance to succeed than previous efforts in large-scale distributed computing |
| cloud data engineering for dummies: Cloud Computing Christian Baun, Marcel Kunze, Jens Nimis, Stefan Tai, 2011-07-14 Cloud computing is a buzz-word in today’s information technology (IT) that nobody can escape. But what is really behind it? There are many interpretations of this term, but no standardized or even uniform definition. Instead, as a result of the multi-faceted viewpoints and the diverse interests expressed by the various stakeholders, cloud computing is perceived as a rather fuzzy concept. With this book, the authors deliver an overview of cloud computing architecture, services, and applications. Their aim is to bring readers up to date on this technology and thus to provide a common basis for discussion, new research, and novel application scenarios. They first introduce the foundation of cloud computing with its basic technologies, such as virtualization and Web services. After that they discuss the cloud architecture and its service modules. The following chapters then cover selected commercial cloud offerings (including Amazon Web Services and Google App Engine) and management tools, and present current related open-source developments (including Hadoop, Eucalyptus, and Open CirrusTM). Next, economic considerations (cost and business models) are discussed, and an evaluation of the cloud market situation is given. Finally, the appendix contains some practical examples of how to use cloud resources or cloud applications, and a glossary provides concise definitions of key terms. The authors’ presentation does not require in-depth technical knowledge. It is equally intended as an introduction for students in software engineering, web technologies, or business development, for professional software developers or system architects, and for future-oriented decision-makers like top executives and managers. |
| cloud data engineering for dummies: Jumpstart Snowflake Dmitry Anoshin, Dmitry Shirokov, Donna Strok, 2019-12-20 Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud. With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use. Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses. What You Will Learn Know the key functionalities of Snowflake Set up security and access with cluster Bulk load data into Snowflake using the COPY command Migrate from a legacy data warehouse to Snowflake integrate the Snowflake data platform with modern business intelligence (BI) and data integration tools Who This Book Is For Those working with data warehouse and business intelligence (BI) technologies, and existing and potential Snowflake users |
| cloud data engineering for dummies: Cloud Computing For Dummies Judith S. Hurwitz, Robin Bloor, Marcia Kaufman, Fern Halper, 2009-11-16 The easy way to understand and implement cloud computing technology written by a team of experts Cloud computing can be difficult to understand at first, but the cost-saving possibilities are great and many companies are getting on board. If you've been put in charge of implementing cloud computing, this straightforward, plain-English guide clears up the confusion and helps you get your plan in place. You'll learn how cloud computing enables you to run a more green IT infrastructure, and access technology-enabled services from the Internet (in the cloud) without having to understand, manage, or invest in the technology infrastructure that supports them. You'll also find out what you need to consider when implementing a plan, how to handle security issues, and more. Cloud computing is a way for businesses to take advantage of storage and virtual services through the Internet, saving money on infrastructure and support This book provides a clear definition of cloud computing from the utility computing standpoint and also addresses security concerns Offers practical guidance on delivering and managing cloud computing services effectively and efficiently Presents a proactive and pragmatic approach to implementing cloud computing in any organization Helps IT managers and staff understand the benefits and challenges of cloud computing, how to select a service, and what's involved in getting it up and running Highly experienced author team consults and gives presentations on emerging technologies Cloud Computing For Dummies gets straight to the point, providing the practical information you need to know. |
| cloud data engineering for dummies: Software Architecture for Big Data and the Cloud Ivan Mistrik, Rami Bahsoon, Nour Ali, Maritta Heisel, Bruce Maxim, 2017-06-12 Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. - Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques - Presents case studies involving enterprise, business, and government service deployment of big data applications - Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data |
| cloud data engineering for dummies: Snowflake Cookbook Hamid Mahmood Qureshi, Hammad Sharif, 2021-02-25 Develop modern solutions with Snowflake's unique architecture and integration capabilities; process bulk and real-time data into a data lake; and leverage time travel, cloning, and data-sharing features to optimize data operations Key Features Build and scale modern data solutions using the all-in-one Snowflake platform Perform advanced cloud analytics for implementing big data and data science solutions Make quicker and better-informed business decisions by uncovering key insights from your data Book Description Snowflake is a unique cloud-based data warehousing platform built from scratch to perform data management on the cloud. This book introduces you to Snowflake's unique architecture, which places it at the forefront of cloud data warehouses. You'll explore the compute model available with Snowflake, and find out how Snowflake allows extensive scaling through the virtual warehouses. You will then learn how to configure a virtual warehouse for optimizing cost and performance. Moving on, you'll get to grips with the data ecosystem and discover how Snowflake integrates with other technologies for staging and loading data. As you progress through the chapters, you will leverage Snowflake's capabilities to process a series of SQL statements using tasks to build data pipelines and find out how you can create modern data solutions and pipelines designed to provide high performance and scalability. You will also get to grips with creating role hierarchies, adding custom roles, and setting default roles for users before covering advanced topics such as data sharing, cloning, and performance optimization. By the end of this Snowflake book, you will be well-versed in Snowflake's architecture for building modern analytical solutions and understand best practices for solving commonly faced problems using practical recipes. What you will learn Get to grips with data warehousing techniques aligned with Snowflake's cloud architecture Broaden your skills as a data warehouse designer to cover the Snowflake ecosystem Transfer skills from on-premise data warehousing to the Snowflake cloud analytics platform Optimize performance and costs associated with a Snowflake solution Stage data on object stores and load it into Snowflake Secure data and share it efficiently for access Manage transactions and extend Snowflake using stored procedures Extend cloud data applications using Spark Connector Who this book is for This book is for data warehouse developers, data analysts, database administrators, and anyone involved in designing, implementing, and optimizing a Snowflake data warehouse. Knowledge of data warehousing and database and cloud concepts will be useful. Basic familiarity with Snowflake is beneficial, but not necessary. |
| cloud data engineering for dummies: Microsoft Azure For Dummies Timothy L. Warner, 2020-03-24 Your roadmap to Microsoft Azure Azure is Microsoft’s flagship cloud computing platform. With over 600 services available to over 44 geographic regions, it would take a library of books to cover the entire Azure ecosystem. Microsoft Azure For Dummies offers a shortcut to getting familiar with Azure’s core product offerings used by the majority of its subscribers. It’s a perfect choice for those looking to gain a quick, basic understanding of this ever-evolving public cloud platform. Written by a Microsoft MVP and Microsoft Certified Azure Solutions Architect, Microsoft Azure For Dummies covers building virtual networks, configuring cloud-based virtual machines, launching and scaling web applications, migrating on-premises services to Azure, and keeping your Azure resources secure and compliant. Migrate your applications and services to Azure with confidence Manage virtual machines smarter than you've done on premises Deploy web applications that scale dynamically to save you money and effort Apply Microsoft's latest security technologies to ensure compliance to maintain data privacy With more and more businesses making the leap to run their applications and services on Microsoft Azure, basic understanding of the technology is becoming essential. Microsoft Azure For Dummies offers a fast and easy first step into the Microsoft public cloud. |
| cloud data engineering for dummies: Cloud Data Center Network Architectures and Technologies Lei Zhang, Le Chen, 2021-04-21 Cloud Data Center Network Architectures and Technologies has been written with the support of Huawei's vast technical knowledge and experience in the data center network (DCN) field, as well as its understanding of customer service requirements. This book describes in detail the architecture design, technical implementation, planning and design, and deployment suggestions for cloud DCNs based on the service challenges DCNs encounter. It starts by describing the overall architecture and technical evolution of DCNs, with the aim of helping readers understand the development of DCNs. It then proceeds to explain the design and implementation of cloud DCNs, including the service model of a single data center (DC), construction of physical and logical networks of DCs, construction of multiple DCNs, and security solutions of DCs. Next, this book dives deep into practices of cloud DCN deployment based on real-world cases to help readers better understand how to build cloud DCNs. Finally, this book introduces DCN openness and some of the hottest forward-looking technologies. In summary, you can use this book as a reference to help you to build secure, reliable, efficient, and open cloud DCNs. It is intended for technical professionals of enterprises, research institutes, information departments, and DCs, as well as teachers and students of computer network-related majors in colleges and universities. Authors Lei Zhang Mr. Zhang is the Chief Architect of Huawei's DCN solution. He has more than 20 years' experience in network product and solution design, as well as a wealth of expertise in product design and development, network planning and design, and network engineering project implementation. He has led the design and deployment of more than 10 large-scale DCNs for Fortune Global 500 companies worldwide. Le Chen Mr. Chen is a Huawei DCN Solution Documentation Engineer with eight years' experience in developing documents related to DCN products and solutions. He has participated in the design and delivery of multiple large-scale enterprise DCNs. Mr. Chen has written many popular technical document series, such as DCN Handbook and BGP Topic. |
| cloud data engineering for dummies: Cybersecurity For Dummies Joseph Steinberg, 2019-10-15 Protect your business and family against cyber attacks Cybersecurity is the protection against the unauthorized or criminal use of electronic data and the practice of ensuring the integrity, confidentiality, and availability of information. Being cyber-secure means that a person or organization has both protected itself against attacks by cyber criminals and other online scoundrels, and ensured that it has the ability to recover if it is attacked. If keeping your business or your family safe from cybersecurity threats is on your to-do list, Cybersecurity For Dummies will introduce you to the basics of becoming cyber-secure! You’ll learn what threats exist, and how to identify, protect against, detect, and respond to these threats, as well as how to recover if you have been breached! The who and why of cybersecurity threats Basic cybersecurity concepts What to do to be cyber-secure Cybersecurity careers What to think about to stay cybersecure in the future Now is the time to identify vulnerabilities that may make you a victim of cyber-crime — and to defend yourself before it is too late. |
| cloud data engineering for dummies: Machine Learning Approach for Cloud Data Analytics in IoT Sachi Nandan Mohanty, Jyotir Moy Chatterjee, Monika Mangla, Suneeta Satpathy, Sirisha Potluri, 2021-07-27 Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book. |
| cloud data engineering for dummies: Handbook of Cloud Computing Nayyar Dr. Anand, 2019-09-20 Great POSSIBILITIES and high future prospects to become ten times folds in the near FUTUREKey features Comprehensively gives clear picture of current state-of-the-art aspect of cloud computing by elaborating terminologies, models and other related terms. Enlightens all major players in Cloud Computing industry providing services in terms of SaaS, PaaS and IaaS. Highlights Cloud Computing Simulators, Security Aspect and Resource Allocation. In-depth presentation with well-illustrated diagrams and simple to understand technical concepts of cloud. Description The book e;Handbook of Cloud Computinge; provides the latest and in-depth information of this relatively new and another platform for scientific computing which has great possibilities and high future prospects to become ten folds in near future. The book covers in comprehensive manner all aspects and terminologies associated with cloud computing like SaaS, PaaS and IaaS and also elaborates almost every cloud computing service model.The book highlights several other aspects of cloud computing like Security, Resource allocation, Simulation Platforms and futuristic trend i.e. Mobile cloud computing. The book will benefit all the readers with all in-depth technical information which is required to understand current and futuristic concepts of cloud computing. No prior knowledge of cloud computing or any of its related technology is required in reading this book. What will you learn Cloud Computing, Virtualisation Software as a Service, Platform as a Service, Infrastructure as a Service Data in Cloud and its Security Cloud Computing - Simulation, Mobile Cloud Computing Specific Cloud Service Models Resource Allocation in Cloud Computing Who this book is for Students of Polytechnic Diploma Classes- Computer Science/ Information Technology Graduate Students- Computer Science/ CSE / IT/ Computer Applications Master Class Students-Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S. Researcher's-Ph.D Research Scholars doing work in Virtualization, Cloud Computing and Cloud Security Industry Professionals- Preparing for Certifications, Implementing Cloud Computing and even working on Cloud Security Table of contents1. Introduction to Cloud Computing2. Virtualisation3. Software as a Service4. Platform as a Service5. Infrastructure as a Service6. Data in Cloud7. Cloud Security 8. Cloud Computing - Simulation9. Specific Cloud Service Models10. Resource Allocation in Cloud Computing11. Mobile Cloud Computing About the authorDr. Anand Nayyar received Ph.D (Computer Science) in Wireless Sensor Networks and Swarm Intelligence. Presently he is working in Graduate School, Duy Tan University, Da Nang, Vietnam. He has total of fourteen Years of Teaching, Research and Consultancy experience with more than 250 Research Papers in various International Conferences and highly reputed journals. He is certified Professional with more than 75 certificates and member of 50 Professional Organizations. He is acting as e;ACM DISTINGUISHED SPEAKERe; |
| cloud data engineering for dummies: IT Architecture For Dummies Kalani Kirk Hausman, Susan L. Cook, 2010-11-01 A solid introduction to the practices, plans, and skills required for developing a smart system architecture Information architecture combines IT skills with business skills in order to align the IT structure of an organization with the mission, goals, and objectives of its business. This friendly introduction to IT architecture walks you through the myriad issues and complex decisions that many organizations face when setting up IT systems to work in sync with business procedures. Veteran IT professional and author Kirk Hausman explains the business value behind IT architecture and provides you with an action plan for implementing IT architecture procedures in an organization. You'll explore the many challenges that organizations face as they attempt to use technology to enhance their business's productivity so that you can gain a solid understanding of the elements that are required to plan and create an architecture that meets specific business goals. Defines IT architecture as a blend of IT skills and business skills that focuses on business optimization, business architecture, performance management, and organizational structure Uncovers and examines every topic within IT architecture including network, system, data, services, application, and more Addresses the challenges that organizations face when attempting to use information technology to enable profitability and business continuity While companies look to technology more than ever to enhance productivity, you should look to IT Architecture For Dummies for guidance in this field. |
| cloud data engineering for dummies: Cloud and Serverless Computing for Scientists Juan A. Añel, Diego P. Montes, Javier Rodeiro Iglesias, 2020-05-12 This book offers an introduction to cloud computing and serverless computing for students, researchers and R&D organizations through several practical examples. Rather than focusing exclusively on the computational issues related to cloud computing, the authors focus on addressing the multidisciplinary applications of cloud computing for daily research work in public institutions and private companies in fields such as archaeology, geosciences, computer sciences, medicine and physics. The book also discusses the emergence of serverless computing over the last three years as a means to make computational infrastructures more apparent to users, avoiding the need to concern one's self with the type of server or computing machine needed to perform a computing task. These topics are presented from the perspective of users, researchers and decision-makers, and are approached based on the authors' collective experience on the use and adoption of cloud computing. |
| cloud data engineering for dummies: Computer Engineering for Babies Chase Roberts, 2021-10-20 An introduction to computer engineering for babies. Learn basic logic gates with hands on examples of buttons and an output LED. |
| cloud data engineering for dummies: Rise of the Data Cloud Frank Slootman, Steve Hamm, 2020-12-18 The rise of the Data Cloud is ushering in a new era of computing. The world’s digital data is mass migrating to the cloud, where it can be more effectively integrated, managed, and mobilized. The data cloud eliminates data siloes and enables data sharing with business partners, capitalizing on data network effects. It democratizes data analytics, making the most sophisticated data science tools accessible to organizations of all sizes. Data exchanges enable businesses to discover, explore, and easily purchase or sell data—opening up new revenue streams. Business leaders have long dreamed of data driving their organizations. Now, thanks to the Data Cloud, nothing stands in their way. |
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Meet your business challenges head on with cloud computing services from Google, including data management, hybrid & multi-cloud, and AI & ML.
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Google Cloud Platform lets you build, deploy, and scale applications, websites, and services on the same infrastructure as Google.
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Meistern Sie geschäftliche Herausforderungen mit Cloud-Computing-Diensten von Google wie Datenverwaltung, Hybrid- und Multi-Cloud sowie KI und ML.
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借助 Google 的云计算服务，包括数据管理、混合云、多云以及 AI 和机器学习方面的服务，着力应对业务挑战。
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