Download or read book Cloud Data Science Harnessing Azure Machine Learning with Python written by Peter Jones and published by Walzone Press. This book was released on 2024-10-15 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the full potential of your data with "Cloud Data Science: Harnessing Azure Machine Learning with Python." This comprehensive guide equips you with the knowledge and skills to leverage the power of Azure Machine Learning and the versatility of Python to innovate and streamline your machine learning workflows. From setting up your Azure Machine Learning workspace to deploying sophisticated models, this book covers essential techniques and advanced methodologies in a clear, practical format. Dive into core topics such as data management, automated machine learning workflows, model optimization, and real-time monitoring to ensure your projects are scalable, efficient, and effective. Whether you're a data scientist, machine learning engineer, or a professional seeking to enhance your understanding of cloud-based machine learning, this book offers invaluable insights and hands-on examples to help you transform vast amounts of data into actionable insights. Explore real-world case studies across various industries, learn to overcome common challenges, and discover best practices for implementing machine learning projects successfully. "Cloud Data Science: Harnessing Azure Machine Learning with Python" is your gateway to mastering data science in the cloud and advancing your professional capabilities in the future of technology.
Download or read book Microsoft Azure Essentials Azure Machine Learning written by Jeff Barnes and published by Microsoft Press. This book was released on 2015-04-25 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.
Download or read book Harnessing the Internet of Everything IoE for Accelerated Innovation Opportunities written by Cardoso, Pedro J.S. and published by IGI Global. This book was released on 2019-02-15 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: As innovators continue to explore and create new developments within the fields of artificial intelligence and computer science, subfields such as machine learning and the internet of things (IoT) have emerged. Now, the internet of everything (IoE), foreseen as a cohesive and intelligent connection of people, processes, data, and things, is theorized to make internet connections more valuable by converting information into wise actions that create unprecedented capabilities, richer experiences, and economic opportunities to all players in the market. Harnessing the Internet of Everything (IoE) for Accelerated Innovation Opportunities discusses the theoretical, design, evaluation, implementation, and use of innovative technologies within the fields of IoE, machine learning, and IoT. Featuring research on topics such as low-power electronics, mobile technology, and artificial intelligence, this book is ideally designed for computer engineers, software developers, investigators, advanced-level students, professors, and professionals seeking coverage on the various contemporary theories, technologies, and tools in IoE engineering.
Download or read book Building Cloud Data Platforms Solutions written by Anouar BEN ZAHRA and published by Anouar BEN ZAHRA. This book was released on with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Building Cloud Data Platforms Solutions: An End-to-End Guide for Designing, Implementing, and Managing Robust Data Solutions in the Cloud" comprehensively covers a wide range of topics related to building data platforms in the cloud. This book provides a deep exploration of the essential concepts, strategies, and best practices involved in designing, implementing, and managing end-to-end data solutions. The book begins by introducing the fundamental principles and benefits of cloud computing, with a specific focus on its impact on data management and analytics. It covers various cloud services and architectures, enabling readers to understand the foundation upon which cloud data platforms are built. Next, the book dives into key considerations for building cloud data solutions, aligning business needs with cloud data strategies, and ensuring scalability, security, and compliance. It explores the process of data ingestion, discussing various techniques for acquiring and ingesting data from different sources into the cloud platform. The book then delves into data storage and management in the cloud. It covers different storage options, such as data lakes and data warehouses, and discusses strategies for organizing and optimizing data storage to facilitate efficient data processing and analytics. It also addresses data governance, data quality, and data integration techniques to ensure data integrity and consistency across the platform. A significant portion of the book is dedicated to data processing and analytics in the cloud. It explores modern data processing frameworks and technologies, such as Apache Spark and serverless computing, and provides practical guidance on implementing scalable and efficient data processing pipelines. The book also covers advanced analytics techniques, including machine learning and AI, and demonstrates how these can be integrated into the data platform to unlock valuable insights. Furthermore, the book addresses an aspects of data platform monitoring, security, and performance optimization. It explores techniques for monitoring data pipelines, ensuring data security, and optimizing performance to meet the demands of real-time data processing and analytics. Throughout the book, real-world examples, case studies, and best practices are provided to illustrate the concepts discussed. This helps readers apply the knowledge gained to their own data platform projects.
Download or read book Predictive Analytics with Microsoft Azure Machine Learning written by Valentine Fontama and published by Apress. This book was released on 2014-11-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter. The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.
Download or read book Deep Learning with Azure written by Mathew Salvaris and published by Apress. This book was released on 2018-08-24 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.
Download or read book Harnessing the Power of Analytics written by Leila Halawi and published by Springer Nature. This book was released on 2022-01-31 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead. The book combines the conceptual perspective and a hands-on approach to predictive analytics using SAS VIYA, an analytic and data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline and business environment, and compare several different modeling techniques. They decipher complex algorithms to demonstrate how they can be applied and explained within improving decisions.
Download or read book AI Unleashed Harnessing Artificial Intelligence to Start and Grow Your Business written by Cassandra Fenyk and published by Fenyk Enterprises LLC. This book was released on 2023-05-15 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI Unleashed: Harnessing Artificial Intelligence to Start and Grow Your Business is a comprehensive guide that takes entrepreneurs on a transformative journey into the world of AI. From understanding the potential of AI to implementing it strategically in various aspects of business, this book provides invaluable insights and practical strategies for leveraging AI to achieve success. In this nine-chapter book, readers will explore the fascinating intersection of AI and entrepreneurship. Beginning with an introduction to AI in business, the book dispels common misconceptions and showcases real-world examples of organizations that have harnessed AI to revolutionize their operations. Readers will learn how to identify opportunities for AI integration within their business models and conduct market research to stay ahead of emerging trends. Practical guidance is provided for setting up the necessary infrastructure and acquiring the hardware and software resources to embark on the AI journey. The book delves into the intricacies of building and training AI models, offering readers a solid foundation in understanding different AI models and their applications. Step-by-step instructions are provided for collecting and preparing data for training, and popular AI frameworks and platforms are explored. This book may contain affiliate links. Using these links does not impact the amount that you are charged, but it does allow me to continue to create and offer amazing content and programs. Thank you for your support. With a focus on practical implementation, the book guides entrepreneurs through the process of integrating AI solutions into existing business processes. It covers topics such as enhancing customer experience through AI-powered chatbots and personalization, optimizing operations through automation and predictive analytics, and leveraging AI in marketing and sales for customer segmentation, pricing optimization, and more. As AI continues to evolve, ethical considerations are paramount. The book addresses these concerns, emphasizing the importance of transparency, accountability, and ethical decision-making in AI applications. It also highlights emerging trends and future possibilities, encouraging entrepreneurs to stay informed and adaptable. AI Unleashed is a must-read for business owners, managers, and aspiring entrepreneurs who are eager to leverage AI's transformative power. With its practical approach, real-world examples, and expert guidance, this book equips readers with the knowledge and tools to unlock the potential of AI and drive sustainable growth in their businesses. Embrace the AI revolution and propel your business forward with AI Unleashe
Download or read book Ultimate Big Data Analytics with Apache Hadoop written by Simhadri Govindappa and published by Orange Education Pvt Ltd. This book was released on 2024-09-09 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Cloud Computing Impact on the World written by Vijay Kumar Yadav and published by Vijay Kumar Yadav . This book was released on with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: **Cloud Computing Impact on the World** is an essential guide to understanding how cloud computing has become a transformative force in today's digital age. This book offers a deep dive into the origins and evolution of cloud computing, examining the key innovations and technologies that have driven its rapid adoption. Readers will explore the major players in the industry, such as AWS, Google Cloud, and Microsoft Azure, and learn how cloud computing went from a niche concept to a global powerhouse. The book highlights cloud computing's role in driving business transformation across various industries, including retail, healthcare, finance, and manufacturing. It also delves into its economic impact, illustrating how it has enabled globalization, fostered innovation in startups, and contributed to the growth of developing economies. Beyond business and economics, the book explores the broader societal implications, from reshaping education and employment to promoting social good and sustainability. With an emphasis on security, artificial intelligence, and big data, the book provides a comprehensive overview of how cloud computing is shaping the future. **Cloud Computing Impact on the World** offers a forward-looking perspective on emerging technologies like edge computing and quantum computing, making it a must-read for anyone interested in the ongoing evolution of cloud services and their global impact.
Download or read book Automated Machine Learning with Microsoft Azure written by Dennis Michael Sawyers and published by Packt Publishing Ltd. This book was released on 2021-04-23 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical, step-by-step guide to using Microsoft's AutoML technology on the Azure Machine Learning service for developers and data scientists working with the Python programming language Key FeaturesCreate, deploy, productionalize, and scale automated machine learning solutions on Microsoft AzureImprove the accuracy of your ML models through automatic data featurization and model trainingIncrease productivity in your organization by using artificial intelligence to solve common problemsBook Description Automated Machine Learning with Microsoft Azure will teach you how to build high-performing, accurate machine learning models in record time. It will equip you with the knowledge and skills to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. Guided user interfaces (GUIs) enable both novices and seasoned data scientists to easily train and deploy machine learning solutions to production. Using a careful, step-by-step approach, this book will teach you how to use Azure AutoML with a GUI as well as the AzureML Python software development kit (SDK). First, you'll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. You'll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train regression, classification, and forecasting models but also use them to solve a wide variety of business problems. By the end of this Azure book, you'll be able to show your business partners exactly how your ML models are making predictions through automatically generated charts and graphs, earning their trust and respect. What you will learnUnderstand how to train classification, regression, and forecasting ML algorithms with Azure AutoMLPrepare data for Azure AutoML to ensure smooth model training and deploymentAdjust AutoML configuration settings to make your models as accurate as possibleDetermine when to use a batch-scoring solution versus a real-time scoring solutionProductionalize your AutoML and discover how to quickly deliver valueCreate real-time scoring solutions with AutoML and Azure Kubernetes ServiceTrain a large number of AutoML models at once using the AzureML Python SDKWho this book is for Data scientists, aspiring data scientists, machine learning engineers, or anyone interested in applying artificial intelligence or machine learning in their business will find this machine learning book useful. You need to have beginner-level knowledge of artificial intelligence and a technical background in computer science, statistics, or information technology before getting started. Familiarity with Python will help you implement the more advanced features found in the chapters, but even data analysts and SQL experts will be able to train ML models after finishing this book.
Download or read book Data Analytics for Business Leveraging Data for Strategic Insights written by Michael Roberts and published by Richards Education. This book was released on with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the modern business landscape, data is more valuable than ever. "Data Analytics for Business: Leveraging Data for Strategic Insights" is a comprehensive guide designed to help businesses harness the power of data analytics to drive decision-making, improve operations, and gain competitive advantage. This book covers the entire spectrum of data analytics, from foundational concepts to advanced techniques, with practical examples and real-world case studies. Whether you are a business leader, data professional, or aspiring analyst, this handbook equips you with the knowledge and skills to transform raw data into actionable insights that propel your organization forward. Embrace the future of business intelligence and unlock the full potential of data analytics.
Download or read book AI in Practice written by Robert Johnson and published by HiTeX Press. This book was released on 2024-10-28 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: "AI in Practice: Core Concepts and Innovative Applications" provides a comprehensive and accessible exploration of artificial intelligence, designed to equip both novices and enthusiasts with the foundational understanding necessary to navigate this transformative field. Delving into the intricate world of AI, this book meticulously outlines essential principles, from the evolution and types of AI to advanced concepts like neural networks, deep learning, and natural language processing. Each chapter stands as a testament to the profound ways in which AI impacts various sectors, including healthcare, robotics, and beyond, highlighting the technological advances that shape our future. In addition to exploring practical applications, the book addresses critical ethical considerations, ensuring readers gain insights into the responsible deployment of AI technologies. With a focus on the latest tools, frameworks, and emerging trends, "AI in Practice" not only offers a window into the current state of AI but also prepares readers for its future possibilities. Whether for academic study, professional development, or personal interest, this book serves as an essential resource for understanding the complexities and potentials of artificial intelligence in today's world.
Download or read book Advanced Data Science and Analytics with Python written by Jesus Rogel-Salazar and published by CRC Press. This book was released on 2020-05-05 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. Features: Targets readers with a background in programming, who are interested in the tools used in data analytics and data science Uses Python throughout Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs Focuses on the practical use of the tools rather than on lengthy explanations Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences – in this case, literally to the users’ fingertips in the form of an iPhone app. About the Author Dr. Jesús Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.
Download or read book IoT Data Analytics using Python written by M S Hariharan and published by BPB Publications. This book was released on 2023-10-23 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of Python to analyze your IoT data KEY FEATURES ● Learn how to build an IoT Data Analytics infrastructure. ● Explore advanced techniques for IoT Data Analysis with Python. ● Gain hands-on experience applying IoT Data Analytics to real-world situations. DESCRIPTION Python is a popular programming language for data analytics, and it is also well-suited for IoT Data Analytics. By leveraging Python's versatility and its rich ecosystem of libraries and tools, Data Analytics for IoT can unlock valuable insights, enable predictive capabilities, and optimize decision-making in various IoT applications and domains. The book begins with a foundation in IoT fundamentals, its role in digital transformation, and why Python is the preferred language for IoT Data Analytics. It then covers essential data analytics concepts, how to establish an IoT Data Analytics environment, and how to design and manage real-time IoT data flows. Next, the book discusses how to implement Descriptive Analytics with Pandas, Time Series Forecasting with Python libraries, and Monitoring, Preventive Maintenance, Optimization, Text Mining, and Automation strategies. It also introduces Edge Computing and Analytics, discusses Continuous and Adaptive Learning concepts, and explores data flow and use cases for Edge Analytics. Finally, the book concludes with a chapter on IoT Data Analytics for self-driving cars, using the CRISP-DM framework for data collection, modeling, and deployment. By the end of the book, you will be equipped with the skills and knowledge needed to extract valuable insights from IoT data and build real-world applications. WHAT YOU WILL LEARN ● Explore the essentials of IoT Data Analytics and the Industry 4.0 revolution. ● Learn how to set up the IoT Data Analytics environment. ● Equip Python developers with data analysis foundations. ● Learn to build data lakes for real-time IoT data streaming. ● Learn to deploy machine learning models on edge devices. ● Understand Edge Computing with MicroPython for efficient IoT Data Analytics. WHO THIS BOOK IS FOR If you are an experienced Python developer who wants to master IoT Data Analytics, or a newcomer who wants to learn Python and its applications in IoT, this book will give you a thorough understanding of IoT Data Analytics and practical skills for real-world use cases. TABLE OF CONTENTS 1. Necessity of Analytics Across IoT 2. Up and Running with Data Analytics Fundamentals 3. Setting Up IoT Analytics Environment 4. Managing Data Pipeline and Cleaning 5. Designing Data Lake and Executing Data Transformation 6. Implementing Descriptive Analytics Using Pandas 7. Time Series Forecasting and Predictions 8. Monitoring and Preventive Maintenance 9. Model Deployment on Edge Devices 10. Understanding Edge Computing with MicroPython 11. IoT Analytics for Self-driving Vehicles
Download or read book Cloud Migration Mastery written by Rob Botwright and published by Rob Botwright. This book was released on 101-01-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: 🌟 Introducing "Cloud Migration Mastery" 🌟 Are you ready to master the art of seamless cloud integration? Look no further! 🚀 With our comprehensive book bundle, you'll gain the knowledge and expertise needed to navigate the complexities of cloud migration across leading platforms such as AWS, Microsoft Azure, VMware, and NaviSite. 💡 Here's what you'll find inside: 📘 Book 1: Cloud Migration Essentials: A Beginner's Guide to AWS Perfect for beginners, this book provides a step-by-step roadmap for understanding key AWS concepts and executing successful cloud migration projects. Whether you're new to the cloud or looking to refresh your skills, this guide has got you covered. 🌈 📘 Book 2: Mastering Microsoft Azure: Advanced Strategies for Cloud Migration Take your Azure skills to the next level with advanced strategies and insights tailored specifically for Microsoft Azure. From identity management to AI and machine learning services, this book equips you with the knowledge needed to maximize the benefits of Azure for your organization. 🚀 📘 Book 3: VMware Virtualization: Optimizing Cloud Migration for Enterprises Explore the role of VMware virtualization technology in optimizing cloud migration for enterprise environments. With a focus on vSphere architecture, performance monitoring, and best practices, this book provides invaluable guidance for enterprises seeking to leverage VMware for their cloud migration initiatives. 💼 📘 Book 4: Navigating NaviSite: Expert Tactics for Seamless Cloud Integration Unlock the full potential of NaviSite's cloud services with expert tactics and strategies for seamless integration. From industry solutions to security frameworks, this book empowers you to navigate the complexities of NaviSite and achieve seamless cloud integration for your organization. 🛠️ Ready to become a cloud migration master? Get your hands on the "Cloud Migration Mastery" book bundle today and embark on your journey to cloud excellence! 🌟
Download or read book Analytics Engineering with SQL and dbt written by Rui Pedro Machado and published by "O'Reilly Media, Inc.". This book was released on 2023-12-08 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. dbt (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL. Authors Rui Machado from Monstarlab and Hélder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence. With this book, you'll learn: What dbt is and how a dbt project is structured How dbt fits into the data engineering and analytics worlds How to collaborate on building data models The main tools and architectures for building useful, functional data models How to fit dbt into data warehousing and laking architecture How to build tests for data transformations
