Download or read book Modern Data Science with R written by Benjamin S. Baumer and published by CRC Press. This book was released on 2021-03-31 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

Download or read book Architecting Modern Data Platforms written by Jan Kunigk and published by "O'Reilly Media, Inc.". This book was released on 2018-12-05 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You’ll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into: Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability

Download or read book Modern Data Strategy written by Mike Fleckenstein and published by Springer. This book was released on 2018-02-12 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.

Download or read book Spring Data written by Mark Pollack and published by "O'Reilly Media, Inc.". This book was released on 2012-10-24 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring Data makes it relatively easy to build applications across a wide range of new data access technologies such as NoSQL and Hadoop. Through several sample projects, you’ll learn how Spring Data provides a consistent programming model that retains NoSQL-specific features and capabilities, and helps you develop Hadoop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow. You’ll also discover the features Spring Data adds to Spring’s existing JPA and JDBC support for writing RDBMS-based data access layers. Learn about Spring’s template helper classes to simplify the use of database-specific functionality Explore Spring Data’s repository abstraction and advanced query functionality Use Spring Data with Redis (key/value store), HBase (column-family), MongoDB (document database), and Neo4j (graph database) Discover the GemFire distributed data grid solution Export Spring Data JPA-managed entities to the Web as RESTful web services Simplify the development of HBase applications, using a lightweight object-mapping framework Build example big-data pipelines with Spring Batch and Spring Integration

Download or read book Modern Data Warehousing Mining and Visualization written by George M. Marakas and published by . This book was released on 2003 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: For undergraduate/graduate-level Data Mining or Data Warehousing courses in Information Systems or Operations Management Departments electives. Taking a multidisciplinary user/manager approach, this text looks at data warehousing technologies necessary to support the business processes of the twenty-first century. Using a balanced professional and conversational approach, it explores the basic concepts of data mining, warehousing, and visualization with an emphasis on both technical and managerial issues and the implication of these modern emerging technologies on those issues. Data mining and visualization exercises using an included fully-enabled, but time-limited version of Megaputer's PolyAnalyst and TextAnalyst data mining and visualization software give students hands-on experience with real-world applications.

Download or read book Modern Big Data Architectures written by Dominik Ryzko and published by John Wiley & Sons. This book was released on 2020-03-31 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.

Download or read book Modern Data Protection written by W. Curtis Preston and published by "O'Reilly Media, Inc.". This book was released on 2021-04-29 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Give your organization the data protection it deserves without the uncertainty and cost overruns experienced by your predecessors or other companies. System and network administrators have their work cut out for them to protect physical and virtual machines in the data center and the cloud; mobile devices including laptops and tablets; SaaS services like Microsoft 365, Google Workspace, and Salesforce; and persistent data created by Kubernetes and container workloads. To help you navigate the breadth and depth of this challenge, this book presents several solutions so you can determine which is right for your company. You'll learn the unique requirements that each workload presents, then explore various categories of commercial backup hardware, software, and services available to protect these data sources, including the advantages and disadvantages of each approach. Learn the workload types that your organization should be backing up Explore the hardware, software, and services you can use to back up your systems Understand what's wrong with your current data protection system Pair your backed-up workloads to the appropriate backup system Learn the adjustments that will make your backups better, without wasting money

Download or read book Mastering the Modern Data Stack written by Nick Jewell, PhD and published by TinyTechMedia LLC. This book was released on 2023-09-28 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of digital transformation, becoming overwhelmed by the sheer volume of potential data management, analytics, and AI solutions is common. Then it's all too easy to become distracted by glossy vendor marketing, and then chase the latest shiny tool, rather than focusing on building resilient, valuable platforms that will outperform the competition. This book aims to fix a glaring gap for data professionals: a comprehensive guide to the full Modern Data Stack that's rooted in real-world capabilities, not vendor hype. It is full of hard-earned advice on how to get maximum value from your investments through tangible insights, actionable strategies, and proven best practices. It comprehensively explains how the Modern Data Stack is truly utilized by today's data-driven companies. Mastering the Modern Data Stack: An Executive Guide to Unified Business Analytics is crafted for a diverse audience. It's for business and technology leaders who understand the importance and potential value of data, analytics, and AI—but don’t quite see how it all fits together in the big picture. It's for enterprise architects and technology professionals looking for a primer on the data analytics domain, including definitions of essential components and their usage patterns. It's also for individuals early in their data analytics careers who wish to have a practical and jargon-free understanding of how all the gears and pulleys move behind the scenes in a Modern Data Stack to turn data into actual business value. Whether you're starting your data journey with modest resources, or implementing digital transformation in the cloud, you'll find that this isn't just another textbook on data tools or a mere overview of outdated systems. It's a powerful guide to efficient, modern data management and analytics, with a firm focus on emerging technologies such as data science, machine learning, and AI. If you want to gain a competitive advantage in today’s fast-paced digital world, this TinyTechGuide™ is for you. Remember, it’s not the tech that’s tiny, just the book!™

Download or read book Data Strategy written by Bernard Marr and published by Kogan Page Publishers. This book was released on 2017-04-03 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: BRONZE RUNNER UP: Axiom Awards 2018 - Business Technology Category Less than 0.5 per cent of all data is currently analyzed and used. However, business leaders and managers cannot afford to be unconcerned or sceptical about data. Data is revolutionizing the way we work and it is the companies that view data as a strategic asset that will survive and thrive. Data Strategy is a must-have guide to creating a robust data strategy. Explaining how to identify your strategic data needs, what methods to use to collect the data and, most importantly, how to translate your data into organizational insights for improved business decision-making and performance, this is essential reading for anyone aiming to leverage the value of their business data and gain competitive advantage. Packed with case studies and real-world examples, advice on how to build data competencies in an organization and crucial coverage of how to ensure your data doesn't become a liability, Data Strategy will equip any organization with the tools and strategies it needs to profit from Big Data, analytics and the Internet of Things (IoT).

Download or read book Small Wars Big Data written by Eli Berman and published by Princeton University Press. This book was released on 2018-06-12 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: How a new understanding of warfare can help the military fight today’s conflicts more effectively The way wars are fought has changed starkly over the past sixty years. International military campaigns used to play out between large armies at central fronts. Today's conflicts find major powers facing rebel insurgencies that deploy elusive methods, from improvised explosives to terrorist attacks. Small Wars, Big Data presents a transformative understanding of these contemporary confrontations and how they should be fought. The authors show that a revolution in the study of conflict--enabled by vast data, rich qualitative evidence, and modern methods—yields new insights into terrorism, civil wars, and foreign interventions. Modern warfare is not about struggles over territory but over people; civilians—and the information they might choose to provide—can turn the tide at critical junctures. The authors draw practical lessons from the past two decades of conflict in locations ranging from Latin America and the Middle East to Central and Southeast Asia. Building an information-centric understanding of insurgencies, the authors examine the relationships between rebels, the government, and civilians. This approach serves as a springboard for exploring other aspects of modern conflict, including the suppression of rebel activity, the role of mobile communications networks, the links between aid and violence, and why conventional military methods might provide short-term success but undermine lasting peace. Ultimately the authors show how the stronger side can almost always win the villages, but why that does not guarantee winning the war. Small Wars, Big Data provides groundbreaking perspectives for how small wars can be better strategized and favorably won to the benefit of the local population.

Download or read book Python and R for the Modern Data Scientist written by Rick J. Scavetta and published by "O'Reilly Media, Inc.". This book was released on 2021-06-22 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a case study that demonstrates ways to use these languages together

Download or read book The Modern Data Warehouse in Azure written by Matt How and published by Apress. This book was released on 2020-06-15 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a modern data warehouse on Microsoft's Azure Platform that is flexible, adaptable, and fast—fast to snap together, reconfigure, and fast at delivering results to drive good decision making in your business. Gone are the days when data warehousing projects were lumbering dinosaur-style projects that took forever, drained budgets, and produced business intelligence (BI) just in time to tell you what to do 10 years ago. This book will show you how to assemble a data warehouse solution like a jigsaw puzzle by connecting specific Azure technologies that address your own needs and bring value to your business. You will see how to implement a range of architectural patterns using batches, events, and streams for both data lake technology and SQL databases. You will discover how to manage metadata and automation to accelerate the development of your warehouse while establishing resilience at every level. And you will know how to feed downstream analytic solutions such as Power BI and Azure Analysis Services to empower data-driven decision making that drives your business forward toward a pattern of success. This book teaches you how to employ the Azure platform in a strategy to dramatically improve implementation speed and flexibility of data warehousing systems. You will know how to make correct decisions in design, architecture, and infrastructure such as choosing which type of SQL engine (from at least three options) best meets the needs of your organization. You also will learn about ETL/ELT structure and the vast number of accelerators and patterns that can be used to aid implementation and ensure resilience. Data warehouse developers and architects will find this book a tremendous resource for moving their skills into the future through cloud-based implementations. What You Will LearnChoose the appropriate Azure SQL engine for implementing a given data warehouse Develop smart, reusable ETL/ELT processes that are resilient and easily maintained Automate mundane development tasks through tools such as PowerShell Ensure consistency of data by creating and enforcing data contracts Explore streaming and event-driven architectures for data ingestionCreate advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse Who This Book Is For Data warehouse or ETL/ELT developers who wish to implement a data warehouse project in the Azure cloud, and developers currently working in on-premise environments who want to move to the cloud, and for developers with Azure experience looking to tighten up their implementation and consolidate their knowledge

Download or read book The Informed Company written by Dave Fowler and published by John Wiley & Sons. This book was released on 2021-10-26 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to manage a modern data stack and get the most out of data in your organization! Thanks to the emergence of new technologies and the explosion of data in recent years, we need new practices for managing and getting value out of data. In the modern, data driven competitive landscape the "best guess" approach—reading blog posts here and there and patching together data practices without any real visibility—is no longer going to hack it. The Informed Company provides definitive direction on how best to leverage the modern data stack, including cloud computing, columnar storage, cloud ETL tools, and cloud BI tools. You'll learn how to work with Agile methods and set up processes that's right for your company to use your data as a key weapon for your success . . . You'll discover best practices for every stage, from querying production databases at a small startup all the way to setting up data marts for different business lines of an enterprise. In their work at Chartio, authors Fowler and David have learned that most businesspeople are almost completely self-taught when it comes to data. If they are using resources, those resources are outdated, so they're missing out on the latest cloud technologies and advances in data analytics. This book will firm up your understanding of data and bring you into the present with knowledge around what works and what doesn't. Discover the data stack strategies that are working for today's successful small, medium, and enterprise companies Learn the different Agile stages of data organization, and the right one for your team Learn how to maintain Data Lakes and Data Warehouses for effective, accessible data storage Gain the knowledge you need to architect Data Warehouses and Data Marts Understand your business's level of data sophistication and the steps you can take to get to "level up" your data The Informed Company is the definitive data book for anyone who wants to work faster and more nimbly, armed with actionable decision-making data.

Download or read book Mastering Azure Synapse Analytics guide to modern data integration written by Sultan Yerbulatov and published by Litres. This book was released on 2024-06-26 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing from my extensive hands-on experience as a data engineer, this book presents a deep exploration of Azure Synapse Analytics through detailed explanations, practical examples, and expert insights. Readers will learn to navigate the complexities of modern data analytics, from data ingestion and transformation to dynamic data masking and compliance reporting.

Download or read book Modern Data Structures and Algorithms in Rust written by and published by RantAI. This book was released on 2024-09-30 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the Power of Data with Rust! 📊🦀 Introducing Modern Data Structures and Algorithms in Rust (DSAR)—your definitive guide to mastering data structures and algorithms using the cutting-edge Rust programming language! 🚀 Whether you're a student diving into computer science or a professional aiming to enhance your software engineering skills, DSAR is crafted to elevate your understanding and application of fundamental and advanced concepts. ✨ Dive deep into: 🔍 Fundamental (F): Grasp the essential building blocks of data structures and algorithms. 💡 Conceptual (C): Explore the theories that drive efficient problem-solving. 🛠️ Practical (P): Implement robust and high-performance solutions with Rust’s unique features. With over 500+ hands-on examples 🤖 and interactive exercises, DSAR empowers you to build memory-safe, concurrent, and lightning-fast applications. 💻 Each chapter seamlessly integrates Rust’s powerful capabilities with time-tested algorithmic strategies, ensuring you not only learn but also apply your knowledge effectively. 🧩 Why Choose DSAR? ✅ Memory Safety: Leverage Rust’s ownership model to write secure code without sacrificing performance. ✅ Concurrency: Master concurrent programming to build scalable and efficient applications. ✅ Performance: Optimize your algorithms to run at peak speed with Rust’s low-level control. Embrace a modern approach to learning and software development—transform your coding prowess with DSAR’s innovative and comprehensive content! 📚 Perfect for learners at every stage, Modern Data Structures and Algorithms in Rust will deepen your technical expertise and prepare you for the challenges of today’s dynamic tech landscape. 🌟 Start your journey towards becoming a Rustacean data maestro today! 🏆

Download or read book Modern Data Science with R written by Benjamin S. Baumer and published by CRC Press. This book was released on 2021-04-13 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

Download or read book The Modern Data Center A Comprehensive Guide written by Charles Nehme and published by Charles Nehme. This book was released on with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Purpose of the Book In today's digital age, data centers are the backbone of virtually every industry, from finance and healthcare to entertainment and retail. This book, "The Modern Data Center: A Comprehensive Guide," aims to provide a thorough understanding of the complexities and innovations that define contemporary data centers. Whether you are an IT professional, a data center manager, or a technology enthusiast, this guide is designed to equip you with the knowledge necessary to navigate and excel in the ever-evolving landscape of data centers. The Evolution and Significance of Modern Data Centers Data centers have come a long way since the early days of computing. What began as simple server rooms has evolved into sophisticated, multi-layered environments that support a wide range of applications and services critical to modern business operations. The significance of data centers cannot be overstated—they are integral to the functioning of the internet, cloud services, and the digital infrastructure that supports our daily lives. Target Audience This book is tailored for a diverse audience: IT Professionals: Gain in-depth knowledge of the latest technologies and best practices in data center design, management, and operations. Data Center Managers: Discover strategies for optimizing performance, enhancing security, and ensuring compliance. Technology Enthusiasts: Understand the foundational concepts and future trends shaping the data center industry. Structure of the Book "The Modern Data Center: A Comprehensive Guide" is divided into five parts, each focusing on a different aspect of data centers: Foundations of Data Centers: Covers the historical evolution, core components, and architectural frameworks. Design and Planning: Discusses site selection, design principles, and capacity planning. Technologies and Trends: Explores virtualization, cloud computing, automation, and networking innovations. Operations and Management: Details day-to-day operations, monitoring, security, and compliance. Future Directions: Looks at emerging technologies, sustainability, and future trends in data center development. Key Topics Covered Historical Context: Learn about the origins and development of data centers. Core Components: Understand the essential elements that make up a data center. Modern Architectures: Explore traditional and cutting-edge data center architectures. Design and Efficiency: Discover best practices for designing scalable and sustainable data centers. Operational Excellence: Gain insights into effective data center management and operations. Technological Innovations: Stay updated on the latest trends and technologies transforming data centers. Future Insights: Prepare for the future with predictions and expert insights into the next generation of data centers. Our Journey Together As we embark on this journey through the world of modern data centers, you will gain a comprehensive understanding of how these critical infrastructures operate, evolve, and shape the future of technology. Each chapter builds on the last, providing a layered approach to learning that ensures you have a well-rounded grasp of both the theoretical and practical aspects of data centers. Thank you for choosing "The Modern Data Center: A Comprehensive Guide." Let’s dive into the intricate and fascinating world of data centers, where technology, innovation, and strategic planning converge to power the digital age.