Annotation In this book, Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects.

Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story

Data Center Virtualization Fundamentals For many IT organizations, today''s greatest challenge is to drive more value, efficiency, and utilization from data centers. Virtualization is the best way to meet this challenge. Data Center Virtualization Fundamentals brings together the comprehensive knowledge Cisco professionals need to apply virtualization throughout their data center environments. Leading data center expert Gustavo A. A. Santana thoroughly explores all components of an end-to-end data center virtualization solution, including networking, storage, servers, operating systems, application optimization, and security. Rather than focusing on a single product or technology, he explores product capabilities as interoperable design tools that can be combined and integrated with other solutions, including VMware vSphere. With the author''s guidance, you''ll learn how to define and implement highly-efficient architectures for new, expanded, or retrofit data center projects. By doing so, you can deliver agile application provisioning without purchasing unnecessary infrastructure, and establish a strong foundation for new cloud computing and IT-as-a-service initiatives. Throughout, Santana illuminates key theoretical concepts through realistic use cases, real-world designs, illustrative configuration examples, and verification outputs. Appendixes provide valuable reference information, including relevant Cisco data center products and CLI principles for IOS and NX-OS. With this approach, Data Center Virtualization Fundamentals will be an indispensable resource for anyone preparing for the CCNA Data Center, CCNP Data Center, or CCIE Data Center certification exams. Gustavo A. A. Santana, CCIE® No. 8806, is a Cisco Technical Solutions Architect working in enterprise and service provider data center projects that require deep integration across technology areas such as networking, application optimization, storage, and servers. He has more than 15 years of data center experience, and has led and coordinated a team of specialized Cisco engineers in Brazil. He holds two CCIE certifications (Routing & Switching and Storage Networking), and is a VMware Certified Professional (VCP) and SNIA Certified Storage Networking Expert (SCSN-E). A frequent speaker at Cisco and data center industry events, he blogs on data center virtualization at gustavoaasantana.net. Learn how virtualization can transform and improve traditional data center network topologies Understand the key characteristics and value of each data center virtualization technology Walk through key decisions, and transform choices into architecture Smoothly migrate existing data centers toward greater virtualization Burst silos that have traditionally made data centers inefficient Master foundational technologies such as VLANs, VRF, and virtual contexts Use virtual PortChannel and FabricPath to overcome the limits of STP Optimize cabling and network management with fabric extender (FEX) virtualized chassis Extend Layer 2 domains to distant data center sites using MPLS and Overlay Transport Virtualization (OTV) Use VSANs to overcome Fibre Channel fabric challenges Improve SAN data protection, environment isolation, and scalability Consolidate I/O through Data Center Bridging and FCoE Use virtualization to radically simplify server environments Create server profiles that streamline "bare metal" server provisioning "Transcend the rack" through virtualized networking based on Nexus 1000V and VM-FEX Leverage opportunities to deploy virtual network services more efficiently Evolve data center virtualization toward full-fledged private clouds -Reviews - "The variety of material that Gustavo covers in this work would appeal to anyone responsible for Data Centers today. His grasp of virtualization technologies and ability to relate it in both technical and non-technical terms makes for compelling reading. This is not your ordinary tech manual. Through use of relatable visual cues, Gustavo provides information that is easily recalled on the subject of virtualization, reaching across Subject Matter Expertise domains. Whether you consider yourself well-versed or a novice on the topic, working in large or small environments, this work will provide a clear understanding of the diverse subject of virtualization." -- Bill Dufresne, CCIE 4375, Distinguished Systems Engineer, Cisco (Americas) "..this book is an essential reference and will be valuable asset for potential candidates pursuing their Cisco Data Center certifications. I am confident that in reading this book, individuals will inevitably gain extensive knowledge and hands-on experience during their certification preparations. If you''re looking for a truly comprehensive guide to virtualization, this is the one!" -- Yusuf Bhaiji, Senior Manager, Expert Certifications (CCIE, CCDE, CCAr), Learning@Cisco "When one first looks at those classic Cisco Data Center blueprints, it is very common to become distracted with the overwhelming number of pieces and linkages. By creating a solid theoretical foundation and providing rich sets of companion examples to illustrate each concept, Gustavo''s book brings hope back to IT Professionals from different areas of expertise. Apparently complex topics are demystified and the insertion of products, mechanisms, protocols and technologies in the overall Data Center Architecture is clearly explained, thus enabling you to achieve robust designs and successful deployments. A must read... Definitely!" -- Alexandre M. S. P. Moraes, Consulting Systems Engineer -- Author of "Cisco Firewalls"

Data virtualization can help you accomplish your goals with more flexibility and agility. Learn what it is and how and why it should be used with Data Virtualization for Business Intelligence Systems. In this book, expert author Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. You'll learn the difference is between this new form of data integration and older forms, such as ETL and replication, and gain a clear understanding of how data virtualization really works. Data Virtualization for Business Intelligence Systems outlines the advantages and disadvantages of data virtualization and illustrates how data virtualization should be applied in data warehouse environments. You'll come away with a comprehensive understanding of how data virtualization will make data warehouse environments more flexible and how it make developing operational BI applications easier. Van der Lans also describes the relationship between data virtualization and related topics, such as master data management, governance, and information management, so you come away with a big-picture understanding as well as all the practical know-how you need to virtualize your data. - First independent book on data virtualization that explains in a product-independent way how data virtualization technology works. - Illustrates concepts using examples developed with commercially available products. - Shows you how to solve common data integration challenges such as data quality, system interference, and overall performance by following practical guidelines on using data virtualization. - Apply data virtualization right away with three chapters full of practical implementation guidance. - Understand the big picture of data virtualization and its relationship with data governance and information management.

This IBM® RedpaperTM publication introduces a new data virtualization capability that enables IBM z/OS® data to be combined with other enterprise data sources in real-time, which allows applications to access any live enterprise data anytime and use the power and efficiencies of the IBM Z® platform. Modern businesses need actionable and timely insight from current data. They cannot afford the time that is necessary to copy and transform data. They also cannot afford to secure and protect each copy of personally identifiable information and corporate intellectual property. Data virtualization enables direct connections to be established between multiple data sources and the applications that process the data. Transformations can be applied, in line, to enable real-time access to data, which opens up many new ways to gain business insight with less IT infrastructure necessary to achieve those goals. Data virtualization can become the backbone for advanced analytics and modern applications. The IBM Data Virtualization Manager for z/OS (DVM) can be used as a stand-alone product or as a utility that is used by other products. Its goal is to enable access to live mainframe transaction data and make it usable by any application. This enables customers to use the strengths of mainframe processing with new agile applications. Additionally, its modern development environment and code-generating capabilities enable any developer to update, access, and combine mainframe data easily by using modern APIs and languages. If data is the foundation for building new insights, IBM DVM is a key tool for providing easy, cost-efficient access to that foundation.

Run queries and analysis on big data clusters across relational and non relational databases Ê KEY FEATURESÊÊ _ Connect to Hadoop, Azure, Spark, Oracle, Teradata, Cassandra, MongoDB, CosmosDB, MySQL, PostgreSQL, MariaDB, and SAP HANA. _ Numerous techniques on how to query data and troubleshoot Polybase for better data analytics. _ Exclusive coverage on Azure Synapse Analytics and building Big Data clusters. DESCRIPTIONÊ This book brings exciting coverage on establishing and managing data virtualization using polybase. This book teaches how to configure polybase on almost all relational and nonrelational databases. You will learn to set up the test environment for any tool or software instantly without hassle. You will practice how to design and build some of the high performing data warehousing solutions and that too in a few minutes of time. You will almost become an expert in connecting to all databases including hadoop, cassandra, MySQL, PostgreSQL, MariaDB and Oracle database. This book also brings exclusive coverage on how to build data clusters on Azure and using Azure Synapse Analytics. By the end of this book, you just don't administer the polybase for managing big data clusters but rather you learn to optimize and boost the performance for enabling data analytics and ease of data accessibility. WHAT YOU WILL LEARN _ Learn to configure Polybase and process Transact SQL queries with ease. _ Create a Docker container with SQL Server 2019 on Windows and Polybase. _ Establish SQL Server instance with any other software or tool using Polybase _ Connect with Cassandra, MongoDB, MySQL, PostgreSQL, MariaDB, and IBM DB2. WHO THIS BOOK IS FORÊÊ This book is for database developers and administrators familiar with the SQL language and command prompt. Managers and decision-makers will also find this book useful. No prior knowledge of any other technology or language is required. TABLE OF CONTENTS 1. What is Data Virtualization (Polybase) 2. History of Polybase 3. Polybase current state 4. Differences with other technologies 5. Usage 6. Future 7. SQL Server 8. Hadoop Cloudera and Hortonworks 9. Windows Azure Storage Blob 10. Spark 11. From Azure Synapse Analytics 12. From Big Data Clusters 13. Oracle 14. Teradata 15. Cassandra 16. MongoDB 17. CosmosDB 18. MySQL 19. PostgreSQL 20. MariaDB 21. SAP HANA 22. IBM DB2 23. Excel

Harness the power of PolyBase data virtualization software to make data from a variety of sources easily accessible through SQL queries while using the T-SQL skills you already know and have mastered. PolyBase Revealed shows you how to use the PolyBase feature of SQL Server 2019 to integrate SQL Server with Azure Blob Storage, Apache Hadoop, other SQL Server instances, Oracle, Cosmos DB, Apache Spark, and more. You will learn how PolyBase can help you reduce storage and other costs by avoiding the need for ETL processes that duplicate data in order to make it accessible from one source. PolyBase makes SQL Server into that one source, and T-SQL is your golden ticket. The book also covers PolyBase scale-out clusters, allowing you to distribute PolyBase queries among several SQL Server instances, thus improving performance. With great flexibility comes great complexity, and this book shows you where to look when queries fail, complete with coverage of internals, troubleshooting techniques, and where to find more information on obscure cross-platform errors. Data virtualization is a key target for Microsoft with SQL Server 2019. This book will help you keep your skills current, remain relevant, and build new business and career opportunities around Microsoft’s product direction. What You Will LearnInstall and configure PolyBase as a stand-alone service, or unlock its capabilities with a scale-out cluster Understand how PolyBase interacts with outside data sources while presenting their data as regular SQL Server tables Write queries combining data from SQL Server, Apache Hadoop, Oracle, Cosmos DB, Apache Spark, and more Troubleshoot PolyBase queries using SQL Server Dynamic Management Views Tune PolyBase queries using statistics and execution plans Solve common business problems, including "cold storage" of infrequently accessed data and simplifying ETL jobs Who This Book Is For SQL Server developers working in multi-platform environments who want one easy way of communicating with, and collecting data from, all of these sources

Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulate and transform point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fit and interpret spatial and spatio-temporal models with the Integrated Nested Laplace Approximations (INLA) and the Stochastic Partial Differential Equation (SPDE) approaches, Create interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policy makers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modeling and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.

Presenting practical guidelines and examples, Advanced Server Virtualization emphasizes design, implementation, and management from both a technical and consultative point of view. It features step-by-step guidelines for planning, deployment, installing, configuring, and creating virtual servers. Covering Microsoft Virtual Server and VMware, it addresses platform-specific virtualization features such as virtual machines, hard drives, networking, and resource management. It offers best practices that allow users to avoid common pitfalls and achieve success faster during server virtualization implementations. It also discusses software licensing issues and the cost-benefits of deploying virtual servers.

Build your own enterprise applications and integration flows with JBoss and its products About This Book Build fast, smart, and flexible applications using JBoss Couple one or more JBoss products to effectively solve various business problems Explore the JBoss product ecosystem for improving the performance of your projects Who This Book Is For If you are a Java developer who wants to have a complete view of the JBoss ecosystem or quickly explore a specific JBoss Product, then this is the book you want. Integrators and consultants, familiar with JBoss, who want integrate several JBoss products within their ongoing project will also find this book useful. What You Will Learn Create new applications or integrate existing systems with JBoss products Setup and manage a JBoss domain Setup and manage a JBoss Fuse cluster with Fabric and Apache Karaf Create and deploy OSGi applications on JBoss Fuse containersv Manage enterprise data with JBoss Datagrid Aggregate various data sources with JBoss Data virtualization to offer data as a service Optimize your business and workflows with both JBoss Business RulesManagement System and JBoss Business Process Management platforms. In Detail Have you often wondered what is the best JBoss product to solve a specific problem? Do you want to get started with a specific JBoss product and know how to integrate different JBoss products in your IT Systems? Then this is the book for you. Through hands-on examples from the business world, this guide presents details on the major products and how you can build your own Enterprise services around the JBoss ecosystem. Starting with an introduction to the JBoss ecosystem, you will gradually move on to developing and deploying clustered application on JBoss Application Server, and setting up high availability using undertow or HA proxy loadbalancers. As you are moving to a micro service archicture, you will be taught how to package existing Java EE applications as micro service using Swarm or create your new micro services from scratch by coupling most popular Java EE frameworks like JPA, CDI with Undertow handlers. Next, you will install and configure JBoss Data grid in development and production environments, develop cache based applications and aggregate various data source in JBoss data virtualization. You will learn to build, deploy, and monitor integration scenarios using JBoss Fuse and run both producers/consumers applications relying on JBoss AMQ. Finally, you will learn to develop and run business workflows and make better decisions in your applications using Drools and Jboss BPM Suite Platform. Style and Approach The book works through the major JBoss products, with examples and instructions to help you understand each product and how they work together.