Artificial Intelligence in Health
This book constitutes the refereed post-conference proceedings of the First International Workshop on Artificial Intelligence in Health, AIH 2018, in Stockholm, Sweden, in July 2018. This workshop consolidated the workshops CARE, KRH4C and AI4HC into a single event.The 18 revised full papers included in this volume were carefully selected from the 26 papers accepted for presentation out of 42 initial submissions. The papers present AI technologies with medical applications and are organized in three tracks: agents in healthcare; data science and decision systems in medicine; and knowledge management in healthcare.
Complex Enterprise Architecture
Implement successful and cost-effective enterprise architecture projects. This book provides a new approach to developing enterprise architecture based on the idea of emergent behaviors--where instead of micromanaging system implementation, the enterprise architecture effort establishes clear goals and leaves the details to the implementation teams. System development efforts are measured based on their contribution to achieving business goals instead of implementing specific (possibly outdated) requirements. Most enterprise architecture initiatives employ one of the existing system architecture frameworks such as Zachman or The Open Group Architecture Framework, but these are not well-suited for enterprise architecture in a modern, agile organization. The new approach presented in this book is based on the author's experience with large enterprise architecture efforts. The approach leverages research into complex adaptive systems and emergent behaviors, where afew simple rules result in complex and efficient enterprise behaviors. Simplifying the task of establishing and maintaining the enterprise architecture cuts the costs of building and maintaining the architecture and frees up those resources for more productive pursuits. System implementers are given the freedom to rapidly adapt to changing user needs without the blessing of the enterprise modeling priesthood, and the architecture is transformed from a static pile of obscure models and documents into an operational framework that can be actively used to manage an enterprise's resources to better achieve business goals. The enterprise architect is free to stop focusing on building and maintaining models and start focusing on achieving business goals. What You'll Learn Refocus enterprise architecture on business needs by eliminating most of the enterprise-level modelsDelegate tasks to the development teams who do system implementationDocument business goals, establish strategies for achieving those goals, and measure progress toward those goalsMeasure the results and gauge whether the enterprise architecture is achieving its goalsUtilize appropriate modeling techniques that can be effectively used in an enterprise architecture Who This Book Is ForArchitecture practitioners and architecture managers: Practitioners are experienced architects who have used existing frameworks such as Zachman, and have experience with formal architecture modeling and/or model-based system engineering; managers are responsible for managing an enterprise architecture project and either have experience with enterprise architecture projects that were ineffective or are looking for a different approach that will be more cost-effective and allow for more organizational agility. Government program managers looking for a differentapproach to make enterprise architecture more relevant and easier to implement will also find this book of value.
Advances in Computational Intelligence
The two-volume set LNAI 11288 and 11289 constitutes the proceedings of the 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, held in Guadalajara, Mexico, in October 2018. The total of 62 papers presented in these two volumes was carefully reviewed and selected from 149 submissions. The contributions are organized in topical as follows: Part I: evolutionary and nature-inspired intelligence; machine learning; fuzzy logic and uncertainty management. Part II: knowledge representation, reasoning, and optimization; natural language processing; and robotics and computer vision.
Advances in Soft Computing
The two-volume set LNAI 11288 and 11289 constitutes the proceedings of the 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, held in Guadalajara, Mexico, in October 2018. The total of 62 papers presented in these two volumes was carefully reviewed and selected from 149 submissions. The contributions are organized in topical as follows: Part I: evolutionary and nature-inspired intelligence; machine learning; fuzzy logic and uncertainty management.Part II: knowledge representation, reasoning, and optimization; natural language processing; and robotics and computer vision.
Pro Devops With Google Cloud Platform
Use DevOps principles with Google Cloud Platform (GCP) to develop applications and services. This book builds chapter by chapter to a complete real-life scenario, explaining how to build, monitor, and maintain a complete application using DevOps in practice.Starting with core DevOps concepts, continuous integration, and continuous delivery, you'll cover common tools including Jenkins, Docker, and Kubernetes in the context of a real microservices application to deploy in the cloud. You will also create a monitor for your cloud and see how to use its data to prevent errors and improve the stability of the system. By the end of Pro DevOps with Google Cloud Platform, you will be able to deploy, maintain, and monitor a real application with GCP. What You Will LearnBuild and deploy applications and services using DevOps on Google Cloud Platform Maintain a complete continuous integration (CI) and continuous delivery (CD) pipelineUse containerization with Docker and KubernetesCarry out CD with GCP and JenkinsCreate microservices with Jenkins, Docker, and KubernetesMonitor your newly deployed application and its deployment and performanceSet up security and manage your network with GCP Who This Book Is ForDevelopers and software architects who want to implement DevOps in practice. Some prior programming experience is recommended as well as a basic knowledge of a Linux command-line environment.
Dynamic Oracle Performance Analytics
Use an innovative approach that relies on big data and advanced analytical techniques to analyze and improve Oracle Database performance. The approach used in this book represents a step-change paradigm shift away from traditional methods. Instead of relying on a few hand-picked, favorite metrics, or wading through multiple specialized tables of information such as those found in an automatic workload repository (AWR) report, you will draw on all available data, applying big data methods and analytical techniques to help the performance tuner draw impactful, focused performance improvement conclusions. This book briefly reviews past and present practices, along with available tools, to help you recognize areas where improvements can be made. The book then guides you through a step-by-step method that can be used to take advantage of all available metrics to identify problem areas and work toward improving them. The method presented simplifies the tuning process and solves the problem of metric overload.You will learn how to: collect and normalize data, generate deltas that are useful in performing statistical analysis, create and use a taxonomy to enhance your understanding of problem performance areas in your database and its applications, and create a root cause analysis report that enables understanding of a specific performance problem and its likely solutions. What You'll LearnCollect and prepare metrics for analysis from a wide array of sourcesApply statistical techniques to select relevant metrics Create a taxonomy to provide additional insight into problem areasProvide a metrics-based root cause analysis regarding the performance issueGenerate an actionable tuning plan prioritized according to problem areasMonitor performance using database-specific normal ranges​Who This Book Is ForProfessional tuners: responsible for maintaining the efficient operation of large-scale databases who wish to focus on analysis, who want to expand their repertoire to include a big data methodology and use metrics without being overwhelmed, who desire to provide accurate root cause analysis and avoid the cyclical fix-test cycles that are inevitable when speculation is used
Migrating to Mariadb
Mitigate the risks involved in migrating away from a proprietary database platform toward MariaDB's open source database engine. This book will help you assess the risks and the work involved, and ensure a successful migration. Migrating to MariaDB describes the process and lessons learned during a migration from a proprietary database management engine to the MariaDB open source solution. The book discusses the drivers for making the decision and change, walking you through all aspects of the process from evaluating the licensing, navigating the pitfalls and hurdles of a migration, through to final implementation on the new platform. The book highlights the cost-effectiveness of MariaDB and how the licensing worries are simplified in comparison to running on a proprietary platform.You'll learn to do your own risk assessment, to identify database and application code that may need to be modified or re-implemented, and to identify MariaDB features to provide the security and failover protection needed by corporate customers. Let the author's experience in migrating a financial firm to MariaDB inform your own efforts, helping you to develop a road map for both technical and political success within your own organization as you migrate away from proprietary lock-in toward MariaDB's open source solution. What You'll LearnEvaluate and compare licensing costs between proprietary databases and MariaDBPerform a proper risk assessment to inform your planning and execution of the migrationBuild a migration road map from the book's example that is specific to your situationMake needed application changes and migrate data to the MariaDB open source database engineWho This Book Is For Technical professionals (including database administrators, programmers, and technical management) who are interested in migrating away from a proprietary database platform toward MariaDB's open source database engine and need to assess the risks and the work involved
Securing SQL Server
Protect your data from attack by using SQL Server technologies to implement a defense-in-depth strategy for your database enterprise. This new edition covers threat analysis, common attacks and countermeasures, and provides an introduction to compliance that is useful for meeting regulatory requirements such as the GDPR. The multi-layered approach in this book helps ensure that a single breach does not lead to loss or compromise of confidential, or business sensitive data.Database professionals in today's world deal increasingly with repeated data attacks against high-profile organizations and sensitive data. It is more important than ever to keep your company's data secure. Securing SQL Server demonstrates how developers, administrators and architects can all play their part in the protection of their company's SQL Server enterprise.This book not only provides a comprehensive guide to implementing the security model in SQLServer, including coverage of technologies such as Always Encrypted, Dynamic Data Masking, and Row Level Security, but also looks at common forms of attack against databases, such as SQL Injection and backup theft, with clear, concise examples of how to implement countermeasures against these specific scenarios. Most importantly, this book gives practical advice and engaging examples of how to defend your data, and ultimately your job, against attack and compromise.What You'll LearnPerform threat analysisImplement access level control and data encryptionAvoid non-reputability by implementing comprehensive auditingUse security metadata to ensure your security policies are enforcedMitigate the risk of credentials being stolenPut countermeasures in place against common forms of attackWho This Book Is ForDatabase administrators who need to understand and counteract the threat of attacks against their company's data, and useful for SQL developers and architects
Ethereum for Architects and Developers
Explore the Ethereum ecosystem step by step with extensive theory, labs, and live use cases. This book takes you through BlockChain concepts; decentralized applications; Ethereum's architecture; Solidity smart contract programming with examples; and testing, debugging, and deploying smart contracts on your local machine and on the cloud. You'll cover best practices for writing contracts with ample examples to allow you to write high-quality contracts with optimal usage of fuel. In later chapters, Ethereum for Architects and Developers covers use cases from different business areas, such as finance, travel, supply-chain, insurance, and land registry. Many of these sectors are explained with flowcharts, diagrams, and sample code that you can refer to and further enhance in live projects.By the end of the book, you will have enough information to use Ethereum to create value for your business processes and build foolproof data storage for smoother execution of business.What You Will Learn Discover key BlockChain conceptsMaster the architecture, building blocks, and ecosystem of EthereumDevelop smart contracts from scratch Debug, test, and deploy to test Take advantage of Ethereum in your business area Who This Book Is ForBlockChain developers and architects wanting to develop decentralized Ethereum applications or learn its architecture.
Data Professionals at Work
Enjoy reading interviews with more than two dozen data professionals to see a picture of what it's like to work in the industry managing and analyzing data, helping you to know what it takes to move from your current expertise into one of the fastest growing areas of technology today. Data is the hottest word of the century, and data professionals are in high demand. You may already be a data professional such as a database administrator or business intelligence analyst. Or you may be one of the many people who want to work as a data professional, and are curious how to get there. Either way, this collection helps you understand how data professionals work, what makes them successful, and what they do to keep up.You'll find interviews in this book with database administrators, database programmers, data architects, business intelligence professionals, and analytics professionals. Interviewees work across industry sectors ranging from healthcare and banking tofinance and transportation and beyond. Each chapter illuminates a successful professional at the top of their game, who shares what helped them get to the top, and what skills and attitudes combine to make them successful in their respective fields.Interviewees in the book include: Mindy Curnutt, Julie Smith, Kenneth Fisher, Andy Leonard, Jes Borland, Kevin Feasel, Ginger Grant, Vicky Harp, Kendra Little, Jason Brimhall, Tim Costello, Andy Mallon, Steph Locke, Jonathan Stewart, Joseph Sack, John Q. Martin, John Morehouse, Kathi Kellenberger, Argenis Fernandez, Kirsten Benzel, Tracy Boggiano, Dave Walden, Matt Gordon, Jimmy May, Drew Furgiuele, Marlon Ribunal, and Joseph Fleming. All of them have been successful in their careers, and share their perspectives on working and succeeding in the field as data and database professionals. What You'll LearnStand out as an outstanding professional in your area of data work by developing the right set of skills and attitudes that lead to successAvoid common mistakes and pitfalls, and recover from operational failures and bad technology decisionsUnderstand current trends and best practices, and stay out in front as the field evolvesBreak into working with data through database administration, business intelligence, or any of the other career paths represented in this bookManage stress and develop a healthy work-life balance no matter which career path you decide uponChoose a suitable path for yourself from among the different career paths in working with dataWho This Book Is ForDatabase administrators and developers, database and business intelligence architects, consultants, and analytic professionals, as well as those intent on moving into one of those career paths. Aspiring data professionals and those in related technical fields who want to make a move toward managing or analyzing data on a full-time basis will find the book useful. Existing data professionals who want to be outstanding and successful at what they do will also appreciate the book's advice and guidance.
Database Benchmarking and Stress Testing
Provide evidence-based answers that can be measured and relied upon by your business. Database administrators will be able to make sound architectural decisions in a fast-changing landscape of virtualized servers and container-based solutions based on the empirical method presented in this book for answering "what if" questions about database performance.Today's database administrators face numerous questions such as: What if we consolidate databases using multitenant features? What if we virtualize database servers as Docker containers? What if we deploy the latest in NVMe flash disks to speed up IO access?Do features such as compression, partitioning, and in-memory OLTP earn back their price? What if we move our databases to the cloud?As an administrator, do you know the answers or even how to test the assumptions?Database Benchmarking and Stress Testing introduces you to database benchmarking using industry-standard test suites such as the TCP series of benchmarks, which are the same benchmarks that vendors rely upon. You'll learn to run these industry-standard benchmarks and collect results to use in answering questions about the performance impact of architectural changes, technology changes, and even down to the brand of database software. You'll learn to measure performance and predict the specific impact of changes to your environment. You'll know the limitations of the benchmarks and the crucial difference between benchmarking and workload capture/reply. This book teaches you how to create empirical evidence in support of business and technology decisions. It's about not guessing when you should be measuring. Empirical testing is scientific testing that delivers measurable results. Begin with a hypothesis about the impact of a possible architecture or technology change. Then run the appropriate benchmarks to gather data and predict whether the change you're exploring will be beneficial, and by what order of magnitude. Stop guessing. Start measuring. Let Database Benchmarking and Stress Testing show the way. What You'll LearnUnderstand the industry-standard database benchmarks, and when each is best usedPrepare for a database benchmarking effort so reliable results can be achievedPerform database benchmarking for consolidation, virtualization, and cloud projectsRecognize and avoid common mistakes in benchmarking database performanceMeasure and interpret results in a rational, concise manner for reliable comparisonsChoose and provide advice on benchmarking tools based on their pros and consWho This Book Is ForDatabase administrators and professionals responsible for advising on architectural decisions such as whether to use cloud-based services, whether to consolidate and containerize, and who must make recommendations on storage or any other technology that impacts database performance
Expert SQL Server Transactions and Locking
Master SQL Server's Concurrency Model so you can implement high-throughput systems that deliver transactional consistency to your application customers. This book explains how to troubleshoot and address blocking problems and deadlocks, and write code and design database schemas to minimize concurrency issues in the systems you develop.SQL Server's Concurrency Model is one of the least understood parts of the SQL Server Database Engine. Almost every SQL Server system experiences hard-to-explain concurrency and blocking issues, and it can be extremely confusing to solve those issues without a base of knowledge in the internals of the Engine. While confusing from the outside, the SQL Server Concurrency Model is based on several well-defined principles that are covered in this book.Understanding the internals surrounding SQL Server's Concurrency Model helps you build high-throughput systems in multi-user environments. This book guides you through the Concurrency Model and elaborates how SQL Server supports transactional consistency in the databases. The book covers all versions of SQL Server, including Microsoft Azure SQL Database, and it includes coverage of new technologies such as In-Memory OLTP and Columnstore Indexes. What You'll LearnKnow how transaction isolation levels affect locking behavior and concurrencyTroubleshoot and address blocking issues and deadlocksProvide required data consistency while minimizing concurrency issuesDesign efficient transaction strategies that lead to scalable codeReduce concurrency problems through good schema designUnderstand concurrency models for In-Memory OLTP and Columnstore IndexesReduce blocking during index maintenance, batch data load, and similar tasksWho This Book Is ForSQL Server developers, database administrators, and application architects who are developing highly-concurrent applications. The book is for anyone interested in the technical aspects of creating and troubleshooting high-throughput systems that respond swiftly to user requests.
UX Optimization
Combine two typically separate sources of data--behavioral quantitative data and usability testing qualitative data--into a powerful single tool that helps improve your organization's website by increasing conversion and ROI. The combination of the what is happening data of website activity, coupled with the why it's happening data of usability testing, provides a complete 360-degree view into what is causing poor performance, where your website can be optimized, and how it can be improved. There are plenty of books focusing on big data and using data analytics to improve websites, or on utilizing usability testing and UX research methods for improvement. This is the first book that combines both subjects into a methodology you can use over and over again to improve any website.UX Optimization is ideal for anyone who wants to combine the power of quantitative data with the insights provided by qualitative data to improve website results. The book uses step-by-step instructions with photos, drawings, and supporting screenshots to show you how to: define personas, conduct behavioral UX data analysis, perform UX and usability testing evaluations, and combine behavioral UX and usability data to create a powerful set of optimization recommendations that can dramatically improve any website.What You'll Learn Understand personas: what they are and how to use them to analyze dataUse quantitative research tools and techniques for analysisKnow where to find UX behavioral data and when to use itUse qualitative research tools, techniques, and proceduresAnalyze qualitative data to find patterns of consistent task flow errorsCombine qualitative and quantitative data for a 360-degree viewMake recommendations for optimizations based on your findingsTest optimization recommendations to ensure improvements are achievedWho This Book Is For Big data analytics (quantitative) professionals who want to learn more about the qualitative side of analysis; UX researchers, usability testers, and UX designers (qualitative professionals) who want to know more about big data and behavioral UX analysis; and students of UX, UX designers, product managers, developers, and those at startups who want to understand how to use behavioral UX and usability testing data to optimize their websites and apps.
Sre in Practice
Organizations big and small have started to realize just how crucial system and application reliability is to their business. They璽 ve also learned just how difficult it is to maintain that reliability while iterating at the speed demanded by the marketplace. Site Reliability Engineering (SRE) is a proven approach to this challenge. SRE is a large and rich topic to discuss. Google led the way with Site Reliability Engineering, the wildly successful O璽 Reilly book that described Google璽 s creation of the discipline and the implementation that璽 s allowed them to operate at a planetary scale. Inspired by that earlier work, this book explores a very different part of the SRE space. The more than two dozen chapters in Seeking SRE bring you into some of the important conversations going on in the SRE world right now. Listen as engineers and other leaders in the field discuss: Different ways of implementing SRE and SRE principles in a wide variety of settings How SRE relates to other approaches such as DevOps Specialties on the cutting edge that will soon be commonplace in SRE Best practices and technologies that make practicing SRE easier The important but rarely explored human side of SRE David N. Blank-Edelman is the book璽 s curator and editor.
Introducing Innodb Cluster
Set up, manage, and configure the new InnoDB Cluster feature in MySQL from Oracle. If you are growing your MySQL installation and want to explore making your servers highly available, this book provides what you need to know about high availability and the new tools that are available in MySQL 8.0.11 and later. Introducing InnoDB Cluster teaches you about the building blocks that make up InnoDB Cluster such as MySQL Group Replication for storing data redundantly, MySQL Router for the routing of inbound connections, and MySQL Shell for simplified setup and configuration, status reporting, and even automatic failover. You will understand how it all works together to ensure that your data are available even when your primary database server goes down. Features described in this book are available in the Community Edition of MySQL, beginning with the version 8.0.11 GA release, making this book relevant for any MySQL users in need of redundancy against failure. Tutorials in the book show how to configure a test environment and plan a production deployment. Examples are provided in the form of a walk-through of a typical MySQL high-availability setup.What You'll LearnDiscover the newest high-availability features in MySQLSet up and use InnoDB Cluster as an HA solutionMigrate your existing servers to MySQL 8Employ best practices for using InnoDB ClusterConfigure servers for optimal automatic failover to ensure that applications continue when a server failsConfigure MySQL Router to load-balance inbound connections to the clusterWho This Book Is For Systems engineers, developers, and database professionals wanting to learn about the powerful high availability (HA) features, beginning with MySQL 8.0.11: MySQL Shell, MySQL Router, and MySQL Group Replication. The book is useful for those designing high-availability systems backed by a database, and for those interested in open source HA solutions.
SQL Server Advanced Data Types
Microsoft has been steadily adding support for advanced data types into their database engine, and many developers and database administrators are not fully aware of what these new types can provide in the way of optimization and speeding development time. This book introduces readers to the growing amount of support within SQL Server for operations and data transformations that until now required third-party software and all the associated licensing and development costs. Readers benefit through a better understanding of what can be done inside the database engine with no additional costs or development time invested in outside software.
Applied Analytics Through Case Studies Using SAS & R
Practical and hands-on approach in building the predictive model and machine learning technique using SAS & R Covers real world business case studies from 6 industrial domains Application of analytical approach to industrial business problems
Mysql Connector/Python Revealed
Move data back and forth between database and application. The must-have knowledge in this book helps programmers learn how to use the official driver, MySQL Connector/Python, by which Python programs communicate with the MySQL database. This book takes you from the initial installation of the connector through basic query execution, then through more advanced topics, error handing, and troubleshooting. The book covers both the traditional API as well as the new X DevAPI. The X DevAPI is part of MySQL 8.0 and is an API that can be used with connectors for several programming languages and is used from the command-line interface known as MySQL Shell. You will learn to use the connector by working through code examples and following a discussion of how the API calls work. By the end of the book, you will be able to use MySQL as the back-end storage for your Python programs, and you'll even have the option of choosing between SQLand NoSQL interfaces. What You'll LearnInstall MySQL Connector/PythonConnect to MySQL and configure database accessExecute SQL and NoSQL queries from your Python programTrap errors and troubleshoot problemsStore data from different languages using MySQL's character set supportWork in the X DevAPI that underlies all of MySQL's language connectorsWho This Book Is ForDevelopers familiar with Python who are looking at using MySQL as the back-end database. No prior knowledge of Connector/Python is assumed, but readers should be familiar with databases and the Python programming language.
Microservices Architecture Handbook
Are you a non-coder looking for insight into Microservices Architecture? You may be a consultant, Advisor, Project Manager or a novice into IT industry; after going through this guide you would be able to appreciate Microservices and other related concepts like SOA, Monolith Architecture, DevOps, Docker, Kubernetes etc.You would also get to know about the leaders in Microservices adoption and impact it had on the overall agility and hyper-growth of the adopters. This book covers the complete lifecycle for your understanding like Integrating, Testing, Deploying Microservices and the Security concerns while deploying. I am confident that after going through the book you would be able to navigate the discussion with any stakeholder and take your agenda ahead as per your role. Additionally, if you are new to the industry, and looking for an application development job, this book will help you to prepare with all the relevant information and understanding of the topic. "One of the best Microservices books of all time" - BookAuthority
Advances in Data Mining. Applications and Theoretical Aspects
This volume constitutes the proceedings of the 18th Industrial Conference on Adances in Data Mining, ICDM 2018, held in New York, NY, USA, in July 2018.The 24 regular papers presented in this book were carefully reviewed and selected from 146 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine and agriculture, and in process control, industry, and society.
Beginning Blockchain
Understand the nuts and bolts of Blockchain, its different flavors with simple use cases, and cryptographic fundamentals. You will also learn some design considerations that can help you build custom solutions.Beginning Blockchain is a beginner's guide to understanding the core concepts of Blockchain from a technical perspective. By learning the design constructs of different types of Blockchain, you will get a better understanding of building the best solution for specific use cases. The book covers the technical aspects of Blockchain technologies, cryptography, cryptocurrencies, and distributed consensus mechanisms. You will learn how these systems work and how to engineer them to design next-gen business solutions.What You'll LearnGet a detailed look at how cryptocurrencies workUnderstand the core technical components of BlockchainBuild a secured Blockchain solution from cryptographic primitivesDiscover how to use different Blockchain platforms and their suitable use casesKnow the current development status, scope, limitations, and future of BlockchainWho This Book Is For Software developers and architects, computer science graduates, entrepreneurs, and anyone wishing to dive deeper into blockchain fundamentals. A basic understanding of computer science, data structure, and algorithms is helpful.
Database Management for Business Leaders
Information is a key to making better decisions. Author Larry Ruddell provides a holistic approach to database management for small business owners, nonprofit executives, and educators who want to answer the following questions. - How to apply database management best practices to my organization? - How to use database management to create a competitive advantage? - How to use Microsoft Access? - What does a database administrator do? - How to become a database administrator? - And more Leveraging more than ten years of experience in database management, Dr. Ruddell has created a modern database management book written in a conversational style. It will help students consider a database administrator career while at the same time providing practical principles to help small business owners communicate more effectively with IT professionals. Dr. Ruddell shows us all that database management doesn't have to be daunting. In his book, you'll learn database design principles that will help you create a plan for using information technology even when you don't have a database administrator on staff. Small business owners and nonprofit executives with limited resources will learn to take control of data and make better decisions to grow your organization. In addition, you'll feel more informed and confident talking to IT professionals while improving your database management skills to boost productivity and create a competitive advantage. Professors and teachers will get a guide that provides learners insights into database management best practices and database design principles with practical advice to help put their students on a path to a career in database administration. Dr. Ruddell is an Associate Professor in Business at Belhaven University and former Dean of Faculty at Belhaven University, Houston campus. He has honed his database management skills and principles through practical experience with four computer startups and as the founder and president of Integrated Systems and Services. He knows what it's like to work at a small company with limited resources and desires to help small business owners and nonprofit executives improve performance and create efficiencies through effective database management. He has more than ten years of experience working as a computer consultant in several capacities, including training, process analysis, database design and development, systems management, project management, and business development. He has worked for Nomos Systems, Inc. (as a founding partner), Quad S Consultants, Enron (with TCHD and OSI), and on a NASA contract with Booz, Allen & Hamilton. He is a Microsoft Certified Microsoft Access Trainer and has developed over 15 database applications, including the global training tracking system for Miami International Seminary.
Database Management for Business Leaders
Information is a key to making better decisions. Author Larry Ruddell provides a holistic approach to database management for small business owners, nonprofit executives, and educators who want to answer the following questions. - How to apply database management best practices to my organization? - How to use database management to create a competitive advantage? - How to use Microsoft Access? - What does a database administrator do? - How to become a database administrator? - And more Leveraging more than ten years of experience in database management, Dr. Ruddell has created a modern database management book written in a conversational style. It will help students consider a database administrator career while at the same time providing practical principles to help small business owners communicate more effectively with IT professionals. Dr. Ruddell shows us all that database management doesn't have to be daunting. In his book, you'll learn database design principles that will help you create a plan for using information technology even when you don't have a database administrator on staff. Small business owners and nonprofit executives with limited resources will learn to take control of data and make better decisions to grow your organization. In addition, you'll feel more informed and confident talking to IT professionals while improving your database management skills to boost productivity and create a competitive advantage. Professors and teachers will get a guide that provides learners insights into database management best practices and database design principles with practical advice to help put their students on a path to a career in database administration. Dr. Ruddell is an Associate Professor in Business at Belhaven University and former Dean of Faculty at Belhaven University, Houston campus. He has honed his database management skills and principles through practical experience with four computer startups and as the founder and president of Integrated Systems and Services. He knows what it's like to work at a small company with limited resources and desires to help small business owners and nonprofit executives improve performance and create efficiencies through effective database management. He has more than ten years of experience working as a computer consultant in several capacities, including training, process analysis, database design and development, systems management, project management, and business development. He has worked for Nomos Systems, Inc. (as a founding partner), Quad S Consultants, Enron (with TCHD and OSI), and on a NASA contract with Booz, Allen & Hamilton. He is a Microsoft Certified Microsoft Access Trainer and has developed over 15 database applications, including the global training tracking system for Miami International Seminary.
Beginning Backup and Restore for SQL Server
Beginning Backup and Restore for SQL Server is the essential guide to discovering the power of data protection and loss mitigation in a SQL Server environment. A company that does not protect its data will not be a company for very long. This book will guide all levels of database administrator through the steps of creating an automated database backup and restore scenario. Too many database administrators rely on a generic maintenance plan to backup data. Catastrophic events can occur, and when they do, the seasoned DBA needs to have more than a generic backup available. This book will prepare any level DBA for these eventualities, bringing into focus such topics as backup rotation and retention periods, differing backup strategies, point-in-time restoration of data, and file/page restores.Recovering from a catastrophic failure used to be next to impossible. With the enhanced techniques and methods you will learn in this book, those failures can be reduced, if not eliminated. SQL Server provides a wealth of tools for backing up and restoring data; this book will help you to wield those tools successfully.
Next-Generation Big Data
Details how to integrate popular third-party applications and platforms such as StreamSets, ZoomData, Talend, Pentaho, Cask, Oracle, and SQL Server. with next-generation big data technologies such as Spark, Kudu, Impala, etc First book covering Apache Kudu--a game-changer relational data store from Cloudera that will disrupt the traditional data warehouse market Features big data use cases and case studies from some of the most successful deployments--GoPro, Mastercard, British Telecom, Navistar, oPower, Cerner, Shopzilla and Caesars Entertainment
New Frontiers in Mining Complex Patterns
This book features a collection of revised and significantly extended versions of the papers accepted for presentation at the 6th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2017, held in conjunction with ECML-PKDD 2017 in Skopje, Macedonia, in September 2017. The book is composed of five parts: feature selection and induction; classification prediction; clustering; pattern discovery; applications.The workshop was aimed at discussing and introducing new algorithmic foundations and representation formalisms in complex pattern discovery. Finally, it encouraged the integration of recent results from existing fields, such as Statistics, Machine Learning and Big Data Analytics.
Business Case Analysis With R
This tutorial teaches you how to use the statistical programming language R to develop a business case simulation and analysis. It presents a methodology for conducting business case analysis that minimizes decision delay by focusing stakeholders on what matters most and suggests pathways for minimizing the risk in strategic and capital allocation decisions. Business case analysis, often conducted in spreadsheets, exposes decision makers to additional risks that arise just from the use of the spreadsheet environment. R has become one of the most widely used tools for reproducible quantitative analysis, and analysts fluent in this language are in high demand. The R language, traditionally used for statistical analysis, provides a more explicit, flexible, and extensible environment than spreadsheets for conducting business case analysis. The main tutorial follows the case in which a chemical manufacturing company considers constructing a chemical reactor and production facility to bring a new compound to market. There are numerous uncertainties and risks involved, including the possibility that a competitor brings a similar product online. The company must determine the value of making the decision to move forward and where they might prioritize their attention to make a more informed and robust decision. While the example used is a chemical company, the analysis structure it presents can be applied to just about any business decision, from IT projects to new product development to commercial real estate. The supporting tutorials include the perspective of the founder of a professional service firm who wants to grow his business and a member of a strategic planning group in a biomedical device company who wants to know how much to budget in order to refine the quality of information about critical uncertainties that might affect the value of a chosen product development pathway. What You'll LearnSet upa business case abstraction in an influence diagram to communicate the essence of the problem to other stakeholdersModel the inherent uncertainties in the problem with Monte Carlo simulation using the R languageCommunicate the results graphicallyDraw appropriate insights from the resultsDevelop creative decision strategies for thorough opportunity cost analysisCalculate the value of information on critical uncertainties between competing decision strategies to set the budget for deeper data analysisConstruct appropriate information to satisfy the parameters for the Monte Carlo simulation when little or no empirical data are available Who This Book Is For Financial analysts, data practitioners, and risk/business professionals; also appropriate for graduate level finance, business, or data science students
The Tech Professional's Guide to Communicating in a Global Workplace
Globalization and outsourcing are but two of the trends driving I.T. professionals toward environments in which they must communicate across cultural boundaries. Working effectively in multi-cultural situations is a path toward personal growth and better career choices, and ultimately toward better pay and greater influence in one's organization. Smart I.T. professionals will read and absorb the lessons in this book in order to address gaps their communication skill set. Readers will learn to better communicate across cultural boundaries of all types, ensuring that what they mean to say is what their colleagues actually perceive them to say.
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 10534 - 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track.
Oracle Weblogic Server 12c Administration I Exam Iz0-133
Use this comprehensive guide to study for the Oracle WebLogic Server 12c Administration I Exam 1Z0-133. This book is a unique introductory resource to the WebLogic Server certification for new Oracle Fusion Middleware administrators and a valuable resource for veteran WebLogic Server administrators seeking to update their skills for the 12c certification topics. It is common sense that passing a certification exam requires a good command of the subject matter, understanding the intricacies surrounding its practice, and having sufficient experience working with the concepts. This book aims to accelerate the process by providing an accurate review of all exam topics, suggesting hands-on practices to gain or reinforce experience working with WebLogic Server, and introducing questions to help candidates become familiar with the format and style of questions found on the actual certification exam. Oracle WebLogic Server 12c Administration I Exam 1Z0-133 covers the associate level certification with Oracle. Although not dedicated to exam 1Z0-599, the guide is also a valuable foundational resource for those preparing for WebLogic Server 12c implementation specialist level certification. This book: Inspects the certification topics in the order that you would likely follow in an on-the-job middleware infrastructure projectIs a great resource for candidates preparing for the certification, who are unable to start with live or personally-assisted trainingIs a great starting point for those pursuing advanced Oracle WebLogic Server certifications What You'll Learn Cover all topics on the certification exam 1Z0-133Become familiar with the types and format of questions on the certification examUnderstand and properly describe Oracle WebLogic Server domains and clustersInstall, configure, maintain, and monitor Oracle WebLogic ServerDeploy and manage applications on Oracle WebLogic ServerDiscover how to use new administration features of Oracle WebLogic Server 12c Who This Book Is For Certified Oracle WebLogic administrators seeking to update their Oracle WebLogic Server credentials, as well as experienced WebLogic Server administrators seeking to earn certification for the first time. Non-Oracle administrators seeking to earn a WebLogic Server certification will also find this book useful.
Deep Learning
Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning璽 especially deep neural networks璽 make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you璽 ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J璽 s workflow tool Learn how to use DL4J natively on Spark and Hadoop
Moving Hadoop to the Cloud
Until recently, Hadoop deployments existed on hardware owned and run by organizations. Now, of course, you can acquire the computing resources and network connectivity to run Hadoop clusters in the cloud. But there's a lot more to deploying Hadoop to the public cloud than simply renting machines. This hands-on guide shows developers and systems administrators familiar with Hadoop how to install, use, and manage cloud-born clusters efficiently. You'll learn how to architect clusters that work with cloud-provider features--not just to avoid pitfalls, but also to take full advantage of these services. You'll also compare the Amazon, Google, and Microsoft clouds, and learn how to set up clusters in each of them. Learn how Hadoop clusters run in the cloud, the problems they can help you solve, and their potential drawbacks Examine the common concepts of cloud providers, including compute capabilities, networking and security, and storage Build a functional Hadoop cluster on cloud infrastructure, and learn what the major providers require Explore use cases for high availability, relational data with Hive, and complex analytics with Spark Get patterns and practices for running cloud clusters, from designing for price and security to dealing with maintenance
Analytics
Learn how big data and other sources of information can be transformed into valuable knowledge - knowledge that can create incredible competitive advantage to propel a business toward market leadership. Learn through examples and experience exactly how to pick projects and build analytics teams that deliver results. Know the ethical and privacy issues, and apply the three-part litmus test of context, permission, and accuracy.Without a doubt, data and analytics are the new source of competitive advantage, but how do executives go from hype to action? That's the objective of this book - to assist executives in making the right investments in the right place and at the right time in order to reap the full benefits of data analytics.
Agile Data Science
Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they're to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You'll learn an iterative approach that lets you quickly change the kind of analysis you're doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization. Build value from your data in a series of agile sprints, using the data-value pyramid Extract features for statistical models from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future via classification and regression Translate predictions into actions Get feedback from users after each sprint to keep your project on track
Mastering Azure Analytics
Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution. You'll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs. Understand the fundamental patterns of the data lake and lambda architecture Recognize the canonical steps in the analytics data pipeline and learn how to use Azure Data Factory to orchestrate them Implement data lakes and lambda architectures, using Azure Data Lake Store, Data Lake Analytics, HDInsight (including Spark), Stream Analytics, SQL Data Warehouse, and Event Hubs Understand where Azure Machine Learning fits into your analytics pipeline Gain experience using these services on real-world data that has real-world problems, with scenarios ranging from aviation to Internet of Things (IoT)
Oracle Database 12c Release 2 Performance Tuning Tips and Techniques
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Proven Database Optimization Solutions―Fully Updated for Oracle Database 12c Release 2Systematically identify and eliminate database performance problems with help from Oracle Certified Master Richard Niemiec. Filled with real-world case studies and best practices, Oracle Database 12c Release 2 Performance Tuning Tips and Techniques details the latest monitoring, troubleshooting, and optimization methods. Find out how to identify and fix bottlenecks on premises and in the cloud, configure storage devices, execute effective queries, and develop bug-free SQL and PL/SQL code. Testing, reporting, and security enhancements are also covered in this Oracle Press guide.- Properly index and partition Oracle Database 12c Release 2- Work effectively with Oracle Cloud, Oracle Exadata, and Oracle Enterprise Manager- Efficiently manage disk drives, ASM, RAID arrays, and memory- Tune queries with Oracle SQL hints and the Trace utility- Troubleshoot databases using V$ views and X$ tables- Create your first cloud database service and prepare for hybrid cloud- Generate reports using Oracle's Statspack and Automatic Workload Repository tools- Use sar, vmstat, and iostat to monitor operating system statistics
Efficient R Programming
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively--until now. This hands-on book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics--from optimizing the set-up of RStudio to leveraging C++--that make this book a useful addition to any R user's bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming. Get advice for setting up an R programming environment Explore general programming concepts and R coding techniques Understand the ingredients of an efficient R workflow Learn how to efficiently read and write data in R Dive into data carpentry--the vital skill for cleaning raw data Optimize your code with profiling, standard tricks, and other methods Determine your hardware capabilities for handling R computation Maximize the benefits of collaborative R programming Accelerate your transition from R hacker to R programmer
Oracle Database 12c Release 2 Multitenant
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Master the Powerful Multitenant Features of Oracle Database 12cGovern a scalable, extensible, and highly available enterprise database environment using the practical information contained in this Oracle Press guide. Written by a team of Oracle Masters, Oracle Database 12c Release 2 Multitenant shows, step-by-step, how to deploy and manage multitenant configurations across IT frameworks of all types and sizes. Find out how to create databases, work with PDBs and CDBs, administer Oracle Net Services, and automate administrative tasks. Backup and recovery, security, and advanced multitenant options are covered in complete detail.Learn how to: - Build high-performance multitenant Oracle databases- Create single-tenant, multitenant, and application containers- Establish network connections and manage services- Handle security using authentication, authorization, and encryption- Back up and restore your mission-critical data- Work with point-in-time recovery and Oracle Flashback- Move data and replicate and clone databases- Work with Oracle's Resource Manager and Data Guard
Practical Machine Learning With H2o
Machine learning has finally come of age. With H2O software, you can perform machine learning and data analysis using a simple open source framework that's easy to use, has a wide range of OS and language support, and scales for big data. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. If you're familiar with R or Python, know a bit of statistics, and have some experience manipulating data, author Darren Cook will take you through H2O basics and help you conduct machine-learning experiments on different sample data sets. You'll explore several modern machine-learning techniques such as deep learning, random forests, unsupervised learning, and ensemble learning. Learn how to import, manipulate, and export data with H2O Explore key machine-learning concepts, such as cross-validation and validation data sets Work with three diverse data sets, including a regression, a multinomial classification, and a binomial classification Use H2O to analyze each sample data set with four supervised machine-learning algorithms Understand how cluster analysis and other unsupervised machine-learning algorithms work
Programming Pig
For many organizations, Hadoop is the first step for dealing with massive amounts of data. The next step? Processing and analyzing datasets with the Apache Pig scripting platform. With Pig, you can batch-process data without having to create a full-fledged application, making it easy to experiment with new datasets. Updated with use cases and programming examples, this second edition is the ideal learning tool for new and experienced users alike. You'll find comprehensive coverage on key features such as the Pig Latin scripting language and the Grunt shell. When you need to analyze terabytes of data, this book shows you how to do it efficiently with Pig. Delve into Pig's data model, including scalar and complex data types Write Pig Latin scripts to sort, group, join, project, and filter your data Use Grunt to work with the Hadoop Distributed File System (HDFS) Build complex data processing pipelines with Pig's macros and modularity features Embed Pig Latin in Python for iterative processing and other advanced tasks Use Pig with Apache Tez to build high-performance batch and interactive data processing applications Create your own load and store functions to handle data formats and storage mechanisms
Introduction to Apache Flink
There's growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensors, and many others. But analyzing data streams at scale has been difficult to do well--until now. This practical book delivers a deep introduction to Apache Flink, a highly innovative open source stream processor with a surprising range of capabilities. Authors Ellen Friedman and Kostas Tzoumas show technical and nontechnical readers alike how Flink is engineered to overcome significant tradeoffs that have limited the effectiveness of other approaches to stream processing. You'll also learn how Flink has the ability to handle both stream and batch data processing with one technology. Learn the consequences of not doing streaming well--in retail and marketing, IoT, telecom, and banking and finance Explore how to design data architecture to gain the best advantage from stream processing Get an overview of Flink's capabilities and features, along with examples of how companies use Flink, including in production Take a technical dive into Flink, and learn how it handles time and stateful computation Examine how Flink processes both streaming (unbounded) and batch (bounded) data without sacrificing performance
Delivering Business Intelligence With Microsoft SQL Server 2016
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Distribute Actionable, Timely BI with Microsoft(R) SQL Server(R) 2016 and Power BIDrive better, faster, more informed decision making across your organization using the expert tips and best practices featured in this hands-on guide. Delivering Business Intelligence with Microsoft SQL Server 2016, Fourth Edition, shows, step-by-step, how to distribute high-performance, custom analytics to users enterprise-wide. Discover how to build BI Semantic Models, create data marts and OLAP cubes, write MDX and DAX scripts, and share insights using Microsoft client tools. The book includes coverage of self-service business intelligence with Power BI.- Understand the goals and components of successful BI- Build data marts, OLAP cubes, and Tabular models- Load and cleanse data with SQL Server Integration Services- Manipulate and analyze data using MDX and DAX scripts and queries- Work with SQL Server Analysis Services and the BI Semantic Model- Author interactive reports using SQL Server Data Tools- Create KPIs and digital dashboards - Implement time-based analytics- Embed data model content in custom applications using ADOMD.NET- Use Power BI to gather, model, and visualize data in a self-service environment
Date on Database
C. J. Date is one of the founding fathers of the relational database field. Of all the early leaders, Date is by far the most prolific, and is arguably the most authoritative (Even today "Date says" carries a lot of weight). Many of today's more seasoned database professionals "grew up" on Date's writings. Those same professionals, along with other serious database students and practitioners, form the core audience for Date's ongoing writing efforts. Date on Database: Writings 2000-2006 is a compilation of Date's most significant articles and papers over the past seven years. It gives readers a one-stop place in which to find Date's latest thinking on relational technology. Many papers are not easily found outside this book. Readers who want the material will gladly pay the price for the book.
Growing Business Intelligence
Learn how to make business intelligence (BI) successful in your organization.How do we enable our organizations to enjoy the often significant benefits of BI and analytics, while at the same time minimizing the cost and risk of failure? In this book, I am not going to try to be prescriptive; I won't tell you exactly how to build your BI environment. Instead, I am going to focus on a few core principles that will enable you to navigate the rocky shoals of BI architecture and arrive at a destination best suited for your particular organization. Some of these core principles include: Have an overarching strategy, plan, and roadmap Recognize and leverage your existing technology investments Support both data discovery and data reuse Keep data in motion, not at rest Separate information delivery from data storage Emphasize data transparency over data quality Take an agile approach to BI development. This book will show you how to successfully navigate both the jungle of BI technology and the minefield of human nature. It will show you how to create a BI architecture and strategy that addresses the needs of all organizational stakeholders. It will show you how to maximize the value of your BI investments. It will show you how to manage the risk of disruptive technology. And it will show you how to use agile methodologies to deliver on the promise of BI and analytics quickly, succinctly, and iteratively. This book is about many things. But principally, it's about success. The goal of any enterprise initiative is to succeed and to derive benefit--benefit that all stakeholders can share in. I want you to be successful. I want your organization to be successful. This book will show you how. This book is for anyone who is currently or will someday be working on a BI, analytics, or Big Data project, and for organizations that want to get the maximum amount of value from both their data and their BI technology investment. This includes all stakeholders in the BI effort--not just the data people or the IT people, but also the business stakeholders who have the responsibility for the definition and use of data. There are six sections to this book: In Section I, What Kind of Garden Do You Want?, we will examine the benefits and risks of Business Intelligence, making the central point that BI is a business (not IT) process designed to manage data assets in pursuit of enterprise goals. We will show how data, when properly managed and used, can be a key enabler of several types of core business processes. The purpose of this section is to help you define the particular benefit(s) you want from BI. In Section II, Building the Bones, we will talk about how to design and build out the "hardscape" (infrastructure) of your BI environment. This stage of the process involves leveraging existing technology investments and iteratively moving toward your desired target state BI architecture. In Section III, From the Ground Up, we explore the more detailed aspects of implementing your BI operational environment. In Section IV, Weeds, Pests and Critters, we talk about the myriad of things that can go wrong on a BI project, and discuss ways of mitigating these risks. In Section V, The Sustainable Garden, we talk about how to create a BI infrastructure that is easy and inexpensive to maintain. Finally, Section VI presents a case study illustrating the principles of this book, as applied to a fictional manufacturing company (the Blue Moon Guitar Company).
Mastering Cloudforms Automation
Learn how to work with the Automate feature of CloudForms, the powerful Red Hat cloud management platform that lets you administer your virtual infrastructure, including hybrid public and private clouds. This practical hands-on introduction shows you how to increase your operational efficiency by automating day-to-day tasks that now require manual input. Throughout the book, author Peter McGowan provides a combination of theoretical information and practical coding examples to help you learn the Automate object model. With this CloudForms feature, you can create auto-scalable cloud applications, eliminate manual decisions and operations when provisioning virtual machines and cloud instances, and manage your complete virtual machine lifecycle. In six parts, this book helps you: Learn the objects and concepts for developing automation scripts with CloudForms Automate Customize the steps and workflows involved in provisioning virtual machines Create and use service catalogs, items, dialogs, objects, bundles, and hierarchies Use CloudForm's updated workflow to retire and delete virtual machines and services Orchestrate and coordinate with external services as part of a workflow Explore distributed automation processing as well as argument passing and handling
Julia for Data Science
After covering the importance of Julia to the data science community and several essential data science principles, we start with the basics including how to install Julia and its powerful libraries. Many examples are provided as we illustrate how to leverage each Julia command, dataset, and function.Specialized script packages are introduced and described. Hands-on problems representative of those commonly encountered throughout the data science pipeline are provided, and we guide you in the use of Julia in solving them using published datasets. Many of these scenarios make use of existing packages and built-in functions, as we cover: An overview of the data science pipeline along with an example illustrating the key points, implemented in Julia Options for Julia IDEs Programming structures and functions Engineering tasks, such as importing, cleaning, formatting and storing data, as well as performing data preprocessing Data visualization and some simple yet powerful statistics for data exploration purposes Dimensionality reduction and feature evaluation Machine learning methods, ranging from unsupervised (different types of clustering) to supervised ones (decision trees, random forests, basic neural networks, regression trees, and Extreme Learning Machines) Graph analysis including pinpointing the connections among the various entities and how they can be mined for useful insights. Each chapter concludes with a series of questions and exercises to reinforce what you learned. The last chapter of the book will guide you in creating a data science application from scratch using Julia.
Architecting Hbase Applications
HBase is a remarkable tool for indexing mass volumes of data, but getting started with this distributed database and its ecosystem can be daunting. With this hands-on guide, you'll learn how to architect, design, and deploy your own HBase applications by examining real-world solutions. Along with HBase principles and cluster deployment guidelines, this book includes in-depth case studies that demonstrate how large companies solved specific use cases with HBase. Authors Jean-Marc Spaggiari and Kevin O'Dell also provide draft solutions and code examples to help you implement your own versions of those use cases, from master data management (MDM) and document storage to near real-time event processing. You'll also learn troubleshooting techniques to help you avoid common deployment mistakes. Learn exactly what HBase does, what its ecosystem includes, and how to set up your environment Explore how real-world HBase instances were deployed and put into production Examine documented use cases for tracking healthcare claims, digital advertising, data management, and product quality Understand how HBase works with tools and techniques such as Spark, Kafka, MapReduce, and the Java API Learn how to identify the causes and understand the consequences of the most common HBase issues
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