This IBM® Redbooks® publication presents an overview of the IBM Geographically Dispersed Parallel Sysplex™ (IBM GDPS®) offerings and the roles they play in delivering a business IT resilience solution. The book begins with general concepts of business IT resilience and disaster recovery, along with issues related to high application availability, data integrity, and performance. These topics are considered within the framework of government regulation, increasing application and infrastructure complexity, and the competitive and rapidly changing modern business environment. Next, it describes the GDPS family of offerings with specific reference to how they can help you achieve your defined goals for disaster recovery and high availability. Also covered are the features that simplify and enhance data replication activities, the prerequisites for implementing each offering, and tips for planning for the future and immediate business requirements. Tables provide easy-to-use summaries and comparisons of the offerings, and the additional planning and implementation services available from IBM are explained. Then, several practical client scenarios and requirements are described, along with the most suitable GDPS solution for each case. The introductory chapters of this publication are intended for a broad technical audience, including IT System Architects, Availability Managers, Technical IT Managers, Operations Managers, System Programmers, and Disaster Recovery Planners. The subsequent chapters provide more technical details about the GDPS offerings, and each can be read independently for those readers who are interested in specific topics. Therefore, if you do read all the chapters, be aware that some information is intentionally repeated.

Unlock the potential of big data analytics by mastering R programming with this comprehensive guide. This book takes you step-by-step through real-world scenarios where R's capabilities shine, providing you with practical skills to handle, process, and analyze large and complex datasets effectively. What this Book will help me do Understand the latest big data processing methods and how R can enhance their application. Set up and use big data platforms such as Hadoop and Spark in conjunction with R. Utilize R for practical big data problems, such as analyzing consumption and behavioral datasets. Integrate R with SQL and NoSQL databases to maximize its versatility in data management. Discover advanced machine learning implementations using R and Spark MLlib for predictive analytics. Author(s) None Walkowiak is an experienced data analyst and R programming expert with a passion for data engineering and machine learning. With a deep knowledge of big data platforms and extensive teaching experience, they bring a clear and approachable writing style to help learners excel. Who is it for? Ideal for data analysts, scientists, and engineers with fundamental data analysis knowledge looking to enhance their big data capabilities using R. If you aim to adapt R for large-scale data management and analysis workflows, this book is your ideal companion to bridge the gap.

Mastering Business Intelligence with MicroStrategy offers a thorough walkthrough of implementing enterprise business intelligence solutions using MicroStrategy 10. In this book, you'll learn how to design comprehensive dashboards, analyze data efficiently, and enhance user experiences with modern BI tools. What this Book will help me do Learn to utilize MicroStrategy's advanced BI capabilities, including dashboards and predictive analytics, to enhance business insights. Develop mobile-responsive analytics dashboards to deliver critical data effectively wherever needed. Explore integration techniques to connect MicroStrategy with other data sources like Hadoop and third-party mapping tools. Master visualization techniques such as charts and geospatial mapping to present data insights compellingly. Gain technical expertise in managing, administering, and troubleshooting MicroStrategy systems to maintain robust BI operations. Author(s) The authors Dmitry Anoshin, None Rana, None Ma, and Neil Mehta bring years of expertise in business intelligence and analytics. With backgrounds working in leading technology solutions and BI projects, they aim to share actionable, real-world insights based on their experiences. Who is it for? This book is perfect for BI developers, analytics managers, and business analysts who use MicroStrategy and wish to deepen their proficiency. It provides value for readers migrating from MicroStrategy 9 to 10 and for those seeking to leverage advanced BI functionalities. If you are keen on unlocking the full potential of BI tools for your organization, this book is for you.

The "R for Data Science Cookbook" is your comprehensive guide to tackling data problems using R. Focusing on practical applications, you will learn data manipulation, visualization, statistical inference, and machine learning with a hands-on approach using popular R packages. What this Book will help me do Master the use of R's functional programming features to streamline your analysis workflows. Extract, transform, and visualize data effectively using robust R packages like dplyr and ggplot2. Learn to create intuitive and professional visualizations and reports that communicate insights effectively. Implement key statistical modeling and machine learning techniques to solve real-world problems. Acquire expertise in data mining techniques, including clustering and association rule mining. Author(s) Yu-Wei Chiu, also known as David Chiu, is an experienced data scientist and educator. With a solid technical background in using R for data science, he combines theory with practical applications in his writing. David's approachable style and rich examples make complex topics accessible and engaging for learners. Who is it for? This book is perfect for individuals who already have a foundation in R and are looking to deepen their expertise in applying R to data science tasks. Ideal readers are analysts and statisticians eager to solve real-world problems using practical tools. If you're aspiring to work effectively with large data sets or want to learn versatile data analysis techniques, this book is designed for you. It bridges the gap between theoretical knowledge and actionable skills, making it invaluable for professionals and learners alike.

Automate your workload and manage more databases and instances with greater ease and efficiency by combining metadata-driven automation with powerful tools like PowerShell and SQL Server Agent. Automate your new instance-builds and use monitoring to drive ongoing automation, with the help of an inventory database and a management data warehouse. The market has seen a trend towards there being a much smaller ratio of DBAs to SQL Server instances. Automation is the key to responding to this challenge and continuing to run a reliable database platform service. guides you through the process of automating the maintenance of your SQL Server enterprise. Expert Scripting and Automation for SQL Server DBAs shows how to automate the SQL Server build processes, monitor multiple instances from a single location, and automate routine maintenance tasks throughout your environment. You will also learn how to create automated responses to common or time consuming break/fix scenarios. The book helps you become faster and better at what you do for a living, and thus more valuable in the job market. Expert Scripting and Automation for SQL Server DBAs Extensive coverage of automation using PowerShell and T-SQL Detailed discussion and examples on metadata-driven automation Comprehensive coverage of automated responses to break/fix scenarios What You Will Learn Automate the SQL Server build process Create intelligent, metadata-drive routines Automate common maintenance tasks Create automated responses to common break/fix scenarios Monitor multiple instance from a central location Utilize T-SQL and PowerShell for administrative purposes Who This Book Is For is a book for SQL Server database administrators responsible for managing increasingly large numbers of databases across their business enterprise. The book is also useful for any database administrator looking to ease their workload through automation. The book addresses the needs of these audiences by showing how to get more done through less effort by implementing an intelligent, automated-processes service model using tools such as T-SQL, PowerShell, Server Agent, and the Management Data Warehouse. Expert Scripting and Automation for SQL Server DBAs

"Monitoring Elasticsearch" focuses on teaching readers how to manage and monitor the health and performance of Elasticsearch clusters. Through practical steps and real-world examples, this book ensures that users can diagnose, resolve, and prevent common issues to optimize system reliability and performance. What this Book will help me do Obtain a clear understanding of Elasticsearch monitoring tools and their features. Learn how to diagnose and troubleshoot common Elasticsearch performance issues. Master the use of Elasticsearch APIs for monitoring and analysis. Explore the best practices for effectively maintaining cluster reliability. Understand the features of tools like Kibana, Marvel, and BigDesk for Elasticsearch monitoring. Author(s) The authors of "Monitoring Elasticsearch" are experts in distributed systems and database management, with extensive experience in Elasticsearch deployment and monitoring. They bring their practical knowledge, teaching readers clear and actionable techniques. Their approachable style makes complex systems accessible, helping professionals and aficionados alike. Who is it for? This book is ideal for developers and system administrators who work with Elasticsearch, regardless of their industry. Whether you're new to Elasticsearch or aiming to deepen your expertise, you will find practical solutions and helpful tools. The content suits a range of experiences, from beginners curious about cluster monitoring to experts needing solutions for specific issues. If you use Elasticsearch or plan to, this book is for you.

IBM® Netcool® Operations Insight integrates infrastructure and operations management into a single coherent structure across business applications, virtualized servers, network devices and protocols, internet protocols, and security and storage devices. This IBM Redbooks® publication will help you install, tailor, and configure Netcool Operations Insight Version 1.4. Netcool Operations Insight consists of several products and components that can be installed on many servers in many combinations. You must make many decisions, both critical and personal preference. The purpose of this document is to accelerate the initial deployment of Netcool Operations Insight by making preferred practice choices. The target audience of this book is Netcool Operations Insight deployment specialists.

This IBM® Redbooks® publication demonstrates and documents that IBM Power Systems™ high-performance computing and technical computing solutions deliver faster time to value with powerful solutions. Configurable into highly scalable Linux clusters, Power Systems offer extreme performance for demanding workloads such as genomics, finance, computational chemistry, oil and gas exploration, and high-performance data analytics. This book delivers a high-performance computing solution implemented on the IBM Power System S822LC. The solution delivers high application performance and throughput based on its built-for-big-data architecture that incorporates IBM POWER8® processors, tightly coupled Field Programmable Gate Arrays (FPGAs) and accelerators, and faster I/O by using Coherent Accelerator Processor Interface (CAPI). This solution is ideal for clients that need more processing power while simultaneously increasing workload density and reducing datacenter floor space requirements. The Power S822LC offers a modular design to scale from a single rack to hundreds, simplicity of ordering, and a strong innovation roadmap for graphics processing units (GPUs). This publication is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) responsible for delivering cost effective high-performance computing (HPC) solutions that help uncover insights from their data so they can optimize business results, product development, and scientific discoveries

Learn all of Excel's statistical tools Test your hypotheses and draw conclusions Use Excel to give meaning to your data Use Excel to interpret stats Statistical analysis with Excel is incredibly useful—and this book shows you that it can be easy, too! You'll discover how to use Excel's perfectly designed tools to analyze and understand data, predict trends, make decisions, and more. Tackle the technical aspects of Excel and start using them to interpret your data! Inside... Covers Excel 2016 for Windows® & Mac® users Check out new Excel stuff Make sense of worksheets Create shortcuts Tool around with analysis Use Quick Statistics Graph your data Work with probability Handle random variables

The Language of SQL, Second Edition Many SQL texts attempt to serve as an encyclopedic reference on SQL syntax -- an approach that is often counterproductive, because that information is readily available in online references published by the major database vendors. For SQL beginners, it’s more important for a book to focus on general concepts and to offer clear explanations and examples of what various SQL statements can accomplish. This is that book. A number of features make The Language of SQL unique among introductory SQL books. First, you will not be required to download software or sit with a computer as you read the text. The intent of this book is to provide examples of SQL usage that can be understood simply by reading. Second, topics are organized in an intuitive and logical sequence. SQL keywords are introduced one at a time, allowing you to grow your understanding as you encounter new terms and concepts. Finally, this book covers the syntax of three widely used databases: Microsoft SQL Server, MySQL, and Oracle. Special “Database Differences” sidebars clearly show you any differences in syntax among these three databases, and instructions are included on how to obtain and install free versions of the databases. This is the only book you need to gain a quick working knowledge of SQL and relational databases. Learn How To... Use SQL to retrieve data from relational databases Apply functions and calculations to data Group and summarize data in a variety of useful ways Use complex logic to retrieve only the data you need Update data and create new tables Design relational databases so that data retrieval is easy and intuitive Use spreadsheets to transform your data into meaningful displays Retrieve data from multiple tables via joins, subqueries, views, and set logic Create, modify, and execute stored procedures Install Microsoft SQL Server, MySQL, or Oracle Contents at a Glance 1 Relational Databases and SQL 2 Basic Data Retrieval 3 Calculated Fields and Aliases 4 Using Functions 5 Sorting Data 6 Selection Criteria 7 Boolean Logic 8 Conditional Logic 9 Summarizing Data 10 Subtotals and Crosstabs 11 Inner Joins 12 Outer Joins 13 Self Joins and Views 14 Subqueries 15 Set Logic 16 Stored Procedures and Parameters 17 Modifying Data 18 Maintaining Tables 19 Principles of Database Design 20 Strategies for Displaying Data A Getting Started with Microsoft SQL Server B Getting Started with MySQL C Getting Started with Oracle

IBM® Netcool® Operations Insight empowers your IT operations to use real-time and historical analytics to identify, isolate, and resolve problems before they affect your business. Powered by IBM Tivoli® Netcool/OMNIbus and the transformative capabilities of cognitive analytics, Netcool Operations Insight consolidates millions of alerts from across local, cloud, and hybrid environments into a few actionable problems. This IBM Redbooks® publication gives a broad understanding of Netcool Operations Insight and describes several scenarios that show the capabilities of this solution in a real-life environment. Each scenario features a different capability of Netcool Operations Insight. The scenarios are documented by using step-by-step figures with explanations to make them easier to implement in your own environment. The scenarios in this book are broken into the following categories: - Network Management-related scenarios - Network Event and cognitive-related scenarios - Network Event-related scenarios The target audience of this book is network specialists, network administrators, and network operators.

Which companies have adopted technologies such as Hadoop and Spark, as well as data science in general? And which industries are lagging behind? This O’Reilly report provides the results of a unique, data-driven analysis of the market for big data products and technologies. Using eye-catching charts and visualizations, Spiderbook cofounder Aman Naimat highlights some surprising results from the analysis, such as: The relatively small number of companies using big data in production Industries that have embraced big data the most—and the least The amount of money spent on various big data use cases How many companies actually use “fast data” The results also reveal the geographical locations where companies have been quick to adopt big data, as well as the types of teams that use big data technology. In addition, Naimat takes you through the analysis process with Spiderbook’s graph-based machine-learning model. The company analyzed billions of publicly available documents, canvassed more than 500,000 companies, and searched the entire business internet to compile the most comprehensive results possible.

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

Data-driven techniques have improved decision-making processes for people in industries such as finance and real estate. Yet, despite promising solutions that data analytics and artificial intelligence/machine learning (ML) tools can bring to healthcare, the industry remains largely unconvinced. In this O’Reilly report, you’ll explore the potential of—and impediments to—widespread adoption of AI and ML in the medical field. You’ll also learn how extensive government regulation and resistance from the medical community have so far stymied full-scale acceptance of sophisticated data analytics in healthcare. Through interviews with several professionals working at the intersection of medicine and data science, author Mike Barlow examines five areas where the application of AI/ML strategies can spur a beneficial revolution in healthcare: Identifying risks and interventions for healthcare management of entire populations Closing gaps in care by designing plans for individual patients Supporting customized self-care treatment plans and monitoring patient health in real time Optimizing healthcare processes through data analysis to improve care and reduce costs Helping doctors and patients choose proper medications, dosages, and promising surgical options

To satisfy end users who want easily accessible answers, many software vendors are looking to add analytics and reporting capabilities to their applications. Embedding analytics into applications can lead to wider adoption and product use, improved user experience, and differentiated products, but embedding analytics can also come with challenges and complexities. In this report, author Courtney Webster reviews several approaches and methods for embedding analytics capabilities into your applications. Should you implement a separate reporting portal, an in-application reporting tab, or go all in with a fully embedded in-page analytics solution? And do you build your own or buy a solution out of the box? To help you choose the right embedded analytics tool, Webster examines seven challenges—from customization, usability, and capabilities to scalability, performance, and data structure support—and presents best practice solutions for each.

The IBM® System Storage® Solutions Handbook helps you solve your current and future data storage business requirements. It helps you achieve enhanced storage efficiency by design to allow managed cost, capacity of growth, greater mobility, and stronger control over storage performance and management. It describes the most current IBM storage products, including the IBM Spectrum™ family, IBM FlashSystem®, disk, and tape, as well as virtualized solutions such IBM Storage Cloud. This IBM Redbooks® publication provides overviews and information about the most current IBM System Storage products. It shows how IBM delivers the right mix of products for nearly every aspect of business continuance and business efficiency. IBM storage products can help you store, safeguard, retrieve, and share your data. This book is intended as a reference for basic and comprehensive information about the IBM Storage products portfolio. It provides a starting point for establishing your own enterprise storage environment. This book describes the IBM Storage products as of March, 2016.

Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community’s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains

What is text mining, and how can it be used? What relevance do these methods have to everyday work in information science and the digital humanities? How does one develop competences in text mining? Working with Text provides a series of cross-disciplinary perspectives on text mining and its applications. As text mining raises legal and ethical issues, the legal background of text mining and the responsibilities of the engineer are discussed in this book. Chapters provide an introduction to the use of the popular GATE text mining package with data drawn from social media, the use of text mining to support semantic search, the development of an authority system to support content tagging, and recent techniques in automatic language evaluation. Focused studies describe text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature. Interviews are included that offer a glimpse into the real-life experience of working within commercial and academic text mining. Introduces text analysis and text mining tools Provides a comprehensive overview of costs and benefits Introduces the topic, making it accessible to a general audience in a variety of fields, including examples from biology, chemistry, sociology, and criminology

This IBM® Redbooks® publication helps administrators and technical professionals understand Internet Small Computer System Interface (iSCSI) and how to implement it for use with IBM Storwize® storage systems. iSCSI can be used alone or with other technologies. This publication provides an overview of the iSCSI protocol and helps you understand how it is similar to and different from Fibre Channel (FC) technology. It helps you plan and design your network topology. It explains how to configure your IBM Storwize storage systems and hosts (including IBM AIX®, Linux, VMware, and Microsoft Windows hosts) to interact with it. It also provides an overview of using IBM Storwize storage systems with OpenStack. This book describes iSCSI configuring for IBM Storwize and SAN Volume Controller storage systems at Version 7.6 or later. In addition to configuration, this publication provides information about performance and troubleshooting.

The Book of R is a comprehensive, beginner-friendly guide to R, the world's most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you'll find everything you need to begin using R effectively for statistical analysis. You'll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You'll even learn how to create impressive data visualizations with R's basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R How to access R's thousands of functions, libraries, and data sets How to draw valid and useful conclusions from your data How to create publication-quality graphics of your resultsCombining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R's functionality. Make The Book of R your doorway into the growing world of data analysis.