"Mastering QlikView" is your advanced guide to unlocking the potential of business intelligence through QlikView. Dive deep into powerful data modeling, performance tuning, and visualization techniques, crafted to empower you in making data-driven decisions and optimizing your BI workflows. What this Book will help me do Understand and implement advanced QlikView data modeling techniques for efficient analysis. Master performance tuning methods to ensure your QlikView applications are fast and scalable. Apply industry best practices for ETL and data loading using QVDs and other QlikView features. Create advanced visualizations and dashboards that distill analytics into actionable insights. Leverage metadata management tools and governance techniques to maintain data integrity and consistency. Author(s) Stephen Redmond, an expert in business intelligence and data visualization, brings years of hands-on experience with QlikView and Qlik Sense. As a seasoned developer and thought leader, Stephen specializes in distilling complex BI methodologies into practical skills. His approachable style makes advanced topics accessible and engaging to readers. Who is it for? This book is tailored for business application developers and system analysts already familiar with QlikView. Ideal for professionals seeking to enhance their BI proficiency with advanced QlikView capabilities. If you're aiming to solve complex data challenges or refine your visualization skills, this book provides the expert guidance to take your knowledge further.

You have installed and performed the basic customization of IBM® Tivoli® Storage Productivity Center. You have collected performance data collection and generated reports. Now it’s time to learn the best ways to use the software to manage your storage infrastructure. This IBM Redbooks® publication shows the best way to set up the software, based on your storage environment, and then how to use it to manage your infrastructure. It includes experiences from IBM clients and staff and covers the following topics: Architectural design techniques (sizing your environment, single versus multiple installations, physical versus virtual servers, deployment in a large, existing storage infrastructure) Database and server considerations (database backup and restoration methods and scripts, using IBM Data Studio Client for database administration, database placement and relocation, repository sizing and tuning, moving and migrating the server) Alerting, monitoring and reporting (monitoring thresholds and alerts, performance management and analysis of reports, real-time performance monitoring for IBM SAN Volume Controller) Security considerations (Tivoli Storage Productivity Center internal user IDs, user authentication configuration methods, how and why to set up and change passwords, configuring, querying, and testing LDAP and Microsoft Active Directory) Heath checks (server heath and logs, health and recoverability of IBM DB2® databases, using the Database Maintenance tool) Data management techniques (how to spot unusual growth incidents, scripted actions for Tivoli Storage manager and hierarchical storage management) This book is for storage administrators who are responsible for the performance and growth of the IT storage infrastructure.

In "Learning HBase", you'll dive deep into the core functionalities of Apache HBase and understand its applications in handling Big Data environments. By exploring both theoretical concepts and practical scenarios, you'll acquire the skills to set up, manage, and optimize HBase clusters. What this Book will help me do Understand and explain the components of the HBase ecosystem. Install and configure HBase clusters for optimized performance. Develop and maintain applications using HBase's structured storage model. Troubleshoot and resolve common issues in HBase deployments. Leverage Hadoop tools and advanced techniques to enhance HBase capabilities. Author(s) None Shriparv is a skilled technologist with a robust background in Big Data tools and application development. With hands-on expertise in distributed storage systems and data analytics, they lend exceptional insights into managing HBase environments. Their approach combines clarity, practicality, and a focus on real-world applicability. Who is it for? This book is ideal for system administrators and developers who are starting their journey in Big Data technology. With clear explanations and hands-on scenarios, it suits those seeking foundational and intermediate knowledge of the HBase ecosystem. Suitably designed, it helps students, early-career professionals, and mid-level technologists enhance their expertise. If you work in Big Data and want to grow your skill set in distributed storage systems, this book is for you.

Mastering GeoServer is your complete guide to deploying GeoServer for enterprise geospatial data hosting. You'll gain advanced skills in data integration, security, and analysis to create efficient and secure mapping systems. What this Book will help me do Learn to install and configure GeoServer for secure and scalable enterprise use. Optimize data handling for complex datasets, including vectors and rasters. Enhance GeoServer's security with corporate integration and secure connections. Gain expertise in styling and deploying production-ready maps. Monitor and optimize GeoServer's performance for large-scale operations. Author(s) None Henderson is a seasoned GIS specialist with years of experience in geospatial systems and geospatial data hosting solutions. Known for their practical insights and clear explanations, Henderson brings practical expertise to every chapter. They aim to provide readers with actionable, real-world solutions to hosting and managing geospatial data effectively. Who is it for? This book is ideal for GIS professionals, system administrators, and developers managing enterprise-scale geospatial data. Whether you're new to GeoServer or aiming to enhance an existing deployment, you'll find tailored guidance for your needs. Readers should have basic GIS knowledge but need not have previous GeoServer experience. This book targets those looking to optimize geospatial servers for enterprise environments.

Corporations and governmental agencies of all sizes are embracing a new generation of enterprise-scale business intelligence (BI) and data warehousing (DW), and very often appoint a single senior-level individual to serve as the Enterprise BI/DW Program Manager. This book is the essential guide to the incremental and iterative build-out of a successful enterprise-scale BI/DW program comprised of multiple underlying projects, and what the Enterprise Program Manager must successfully accomplish to orchestrate the many moving parts in the quest for true enterprise-scale business intelligence and data warehousing. Author Alan Simon has served as an enterprise business intelligence and data warehousing program management advisor to many of his clients, and spent an entire year with a single client as the adjunct consulting director for a $10 million enterprise data warehousing (EDW) initiative. He brings a wealth of knowledge about best practices, risk management, organizational culture alignment, and other Critical Success Factors (CSFs) to the discipline of enterprise-scale business intelligence and data warehousing.

RDF Database Systems is a cutting-edge guide that distills everything you need to know to effectively use or design an RDF database. This book starts with the basics of linked open data and covers the most recent research, practice, and technologies to help you leverage semantic technology. With an approach that combines technical detail with theoretical background, this book shows how to design and develop semantic web applications, data models, indexing and query processing solutions. Understand the Semantic Web, RDF, RDFS, SPARQL, and OWL within the context of relational database management and NoSQL systems Learn about the prevailing RDF triples solutions for both relational and non-relational databases, including column family, document, graph, and NoSQL Implement systems using RDF data with helpful guidelines and various storage solutions for RDF Process SPARQL queries with detailed explanations of query optimization, query plans, caching, and more Evaluate which approaches and systems to use when developing Semantic Web applications with a helpful description of commercial and open-source systems

"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006) A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. Includes numerous worked examples and exercises within each chapter.

Get the expert perspective and practical advice on big data The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits makes the case that big data is for real, and more than just big hype. The book uses real-life examples—from Nate Silver to Copernicus, and Apple to Blackberry—to demonstrate how the winners of the future will use big data to seek the truth. Written by a marketing journalist and the CEO of a multi-million-dollar B2B marketing platform that reaches more than 90% of the U.S. business population, this book is a comprehensive and accessible guide on how to win customers, beat competitors, and boost the bottom line with big data. The marketplace has entered an era where the customer holds all the cards. With unprecedented choice in both the consumer world and the B2B world, it's imperative that businesses gain a greater understanding of their customers and prospects. Big data is the key to this insight, because it provides a comprehensive view of a company's customers—who they are, and who they may be tomorrow. The Big Data-Driven Business is a complete guide to the future of business as seen through the lens of big data, with expert advice on real-world applications. Learn what big data is, and how it will transform the enterprise Explore why major corporations are betting their companies on marketing technology Read case studies of big data winners and losers Discover how to change privacy and security, and remodel marketing Better information allows for better decisions, better targeting, and better reach. Big data has become an indispensable tool for the most effective marketers in the business, and it's becoming less of a competitive advantage and more like an industry standard. Remaining relevant as the marketplace evolves requires a full understanding and application of big data, and The Big Data-Driven Business provides the practical guidance businesses need.

Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media.

However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS.

This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries.

Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis.

This book is part of the SAS Press program.

SAP is a market leader in enterprise business application software. SAP solutions provide a rich set of composable application modules, and configurable functional capabilities that are expected from a comprehensive enterprise business application software suite. In most cases, companies that adopt SAP software remain heterogeneous enterprises running both SAP and non-SAP systems to support their business processes. Regardless of the specific scenario, in heterogeneous enterprises most SAP implementations must be integrated with a variety of non-SAP enterprise systems: Portals Messaging infrastructure Business process management (BPM) tools Enterprise Content Management (ECM) methods and tools Business analytics (BA) and business intelligence (BI) technologies Security Systems of record Systems of engagement When SAP software is used in a large, heterogeneous enterprise environment, SAP clients face the dilemma of selecting the correct set of tools and platforms to implement SAP functionality, and to integrate the SAP solutions with non-SAP systems. This IBM® Redbooks® publication explains the value of integrating IBM software with SAP solutions. It describes how to enhance and extend pre-built capabilities in SAP software with best-in-class IBM enterprise software, enabling clients to maximize return on investment (ROI) in their SAP investment and achieve a balanced enterprise architecture approach. This book describes IBM Reference Architecture for SAP, a prescriptive blueprint for using IBM software in SAP solutions. The reference architecture is focused on defining the use of IBM software with SAP, and is not intended to address the internal aspects of SAP components. The chapters of this book provide a specific reference architecture for many of the architectural domains that are each important for a large enterprise to establish common strategy, efficiency, and balance. The majority of the most important architectural domain topics, such as integration, process optimization, master data management, mobile access, Enterprise Content Management, business intelligence, DevOps, security, systems monitoring, and so on, are covered in the book. However, there are several other architectural domains which are not included in the book. This is not to imply that these other architectural domains are not important or are less important, or that IBM does not offer a solution to address them. It is only reflective of time constraints, available resources, and the complexity of assembling a book on an extremely broad topic. Although more content could have been added, the authors feel confident that the scope of architectural material that has been included should provide organizations with a fantastic head start in defining their own enterprise reference architecture for many of the important architectural domains, and it is hoped that this book provides great value to those reading it. This IBM Redbooks publication is targeted to the following audiences: Client decision makers and solution architects leading enterprise transformation projects and wanting to gain further insight so that they can benefit from the integration of IBM software in large-scale SAP projects. IT architects and consultants integrating IBM technology with SAP solutions.

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of the methodology, this book brings together the theoretical and methodological aspects of MFA. It also covers principal component analysis, multiple correspondence analysis, factor analysis for mixed data, hierarchical MFA, and more. The book also includes examples of applications and details on how to implement MFA using an R package, with the data and R scripts available online.

The ability to create and understand financial models that assess the valuation of a company, the projects it undertakes, and its future earnings/profit projections is one of the most valued skills in corporate finance. However, while many business professionals are familiar with financial statements and accounting reports, few are truly proficient at building an accurate and effective financial model from the ground up. In his short book, The Basics of Financial Modeling—an abridgement of his Handbook of Financial Modeling—Jack Avon equips financial professionals with a quick overview of the tools they need to monitor a company's assets and project its future performance and prospects for specific initiatives. Based on the author's extensive experience building models in business and finance—and teaching others to do the same— The Basics of Financial Modeling takes readers step by step in a quick-read format through the financial modeling process, starting with a general overview of the history and evolution of financial modeling. It then moves on to more technical topics, such as the principles of financial modeling and the proper way to approach a financial modeling assignment, before covering key application areas for modeling in Microsoft Excel. Designed for beginning to intermediate modelers who wish to expand and enhance their knowledge of using Excel to build financial models, The Basics of Financial Modeling covers: The accounting and finance concepts that underpin working financial models How to approach financial issues and solutions from a modeler's perspective The importance of thinking about end users when developing a financial model How to plan, design, and build a financial model A nuts-to-bolts guide to solving common financial problems with spreadsheets, The Basics of Financial Modeling is a one-stop resource for anyone who needs to build or analyze financial models.

A comprehensive overview of the internationalisation of correspondence analysis Correspondence Analysis: Theory, Practice and New Strategies examines the key issues of correspondence analysis, and discusses the new advances that have been made over the last 20 years. The main focus of this book is to provide a comprehensive discussion of some of the key technical and practical aspects of correspondence analysis, and to demonstrate how they may be put to use. Particular attention is given to the history and mathematical links of the developments made. These links include not just those major contributions made by researchers in Europe (which is where much of the attention surrounding correspondence analysis has focused) but also the important contributions made by researchers in other parts of the world. Key features include: A comprehensive international perspective on the key developments of correspondence analysis. Discussion of correspondence analysis for nominal and ordinal categorical data. Discussion of correspondence analysis of contingency tables with varying association structures (symmetric and non-symmetric relationship between two or more categorical variables). Extensive treatment of many of the members of the correspondence analysis family for two-way, three-way and multiple contingency tables. Correspondence Analysis offers a comprehensive and detailed overview of this topic which will be of value to academics, postgraduate students and researchers wanting a better understanding of correspondence analysis. Readers interested in the historical development, internationalisation and diverse applicability of correspondence analysis will also find much to enjoy in this book.

Mixed modelling is very useful, and easier than you think! Mixed modelling is now well established as a powerful approach to statistical data analysis. It is based on the recognition of random-effect terms in statistical models, leading to inferences and estimates that have much wider applicability and are more realistic than those otherwise obtained. Introduction to Mixed Modelling leads the reader into mixed modelling as a natural extension of two more familiar methods, regression analysis and analysis of variance. It provides practical guidance combined with a clear explanation of the underlying concepts. Like the first edition, this new edition shows diverse applications of mixed models, provides guidance on the identification of random-effect terms, and explains how to obtain and interpret best linear unbiased predictors (BLUPs). It also introduces several important new topics, including the following: Use of the software SAS, in addition to GenStat and R. Meta-analysis and the multiple testing problem. The Bayesian interpretation of mixed models. Including numerous practical exercises with solutions, this book provides an ideal introduction to mixed modelling for final year undergraduate students, postgraduate students and professional researchers. It will appeal to readers from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, archaeology and geography. Praise for the first edition: "One of the main strengths of the text is the bridge it provides between traditional analysis of variance and regression models and the more recently developed class of mixed models...Each chapter is well-motivated by at least one carefully chosen example...demonstrating the broad applicability of mixed models in many different disciplines...most readers will likely learn something new, and those previously unfamiliar with mixed models will obtain a solid foundation on this topic."— Kerrie Nelson University of South Carolina, in American Statistician, 2007

The IBM XIV® Storage System has a rich set of copy functions suited for various data protection scenarios that enable you to enhance your business continuance, disaster recovery, data migration, and online backup solutions. These functions allow point-in-time copies, known as snapshots and full volume copies, and also include remote copy capabilities in either synchronous or asynchronous mode. A three-site mirroring function is now available to further improve availability and disaster recovery capabilities. These functions are included in the XIV software and all their features are available at no extra charge. The various copy functions are reviewed in separate chapters, which include detailed information about usage and practical illustrations. The book also illustrates the use of IBM® Tivoli® Storage Productivity Center for Replication to manage XIV Copy Services. This IBM Redbooks® publication is intended for anyone who needs a detailed and practical understanding of the XIV copy functions.

Hbase Essentials provides a hands-on introduction to HBase, a distributed database built on top of the Hadoop ecosystem. Through practical examples and clear explanations, you will learn how to set up, use, and administer HBase to manage high-volume, high-velocity data efficiently. What this Book will help me do Understand the importance and use cases of HBase for managing Big Data. Successfully set up and configure an HBase cluster in your environment. Develop data models in HBase and perform CRUD operations effectively. Learn advanced HBase features like counters, coprocessors, and integration with MapReduce. Master cluster management and performance tuning for optimal HBase operations. Author(s) None Garg is a seasoned Big Data engineer with extensive experience in distributed databases and the Hadoop ecosystem. Having worked on complex data systems, None brings practical insights to understanding and implementing HBase. Known for a clear and approachable writing style, None aims to make learning technical subjects accessible. Who is it for? Hbase Essentials is ideal for developers and Big Data engineers keen to build expertise in distributed databases. If you have a basic understanding of HDFS or MapReduce or have experience with NoSQL databases, this book will accelerate your knowledge of HBase. It's tailored for those seeking to leverage HBase for scalable and reliable data solutions. Whether you're starting with HBase or expanding your Big Data skillset, this guide provides the tools to succeed.

Take Your PL/SQL Programming Skills to the Next Level Build robust database-centric PL/SQL applications quickly and effectively. Oracle Database 12c PL/SQL Advanced Programming Techniques shows you how to write and deploy Java libraries inside Oracle Database 12c, use the utl_file and DBMS_SCHEDULER packages, and create external tables and external procedures. Application security, performance tuning, and Oracle Database In-Memory are also covered in this Oracle Press guide. Configure, deploy, and troubleshoot Java libraries for Oracle object types Use the utl_file package to manage unstructured and structured data Develop and deploy Java I/O libraries and wrap them with PL/SQL Create and use external tables Implement high-speed data transfer Harden database systems and develop secure applications Manage complex schedules and jobs with the DBMS_SCHEDULER package Optimize PL/SQL for use in performance tuning Create and deploy external procedures Implement the Oracle Database In-Memory column store feature

The Snowden intelligence leak and the recent Navy Yard shooting have cast a bright light on what employers and background companies do to vet their employees. This edition includes new information providing the latest tactics and guidelines for proper use of Internet vetting, investigations, and open-source intelligence on the Internet. It outlines new tools and tactics to legally comb the Internet for information on individuals when screening current and prospective employees, and includes outcomes of recent legal cases relating to discoverable information on social media.

With a growing number of scientists and engineers using JMP software for design of experiments, there is a need for an example-driven book that supports the most widely used textbook on the subject, Design and Analysis of Experiments by Douglas C. Montgomery. Design and Analysis of Experiments by Douglas Montgomery: A Supplement for Using JMP meets this need and demonstrates all of the examples from the Montgomery text using JMP. In addition to scientists and engineers, undergraduate and graduate students will benefit greatly from this book.
While users need to learn the theory, they also need to learn how to implement this theory efficiently on their academic projects and industry problems. In this first book of its kind using JMP software, Rushing, Karl and Wisnowski demonstrate how to design and analyze experiments for improving the quality, efficiency, and performance of working systems using JMP. Topics include JMP software, two-sample t-test, ANOVA, regression, design of experiments, blocking, factorial designs, fractional-factorial designs, central composite designs, Box-Behnken designs, split-plot designs, optimal designs, mixture designs, and 2 k factorial designs. JMP platforms used include Custom Design, Screening Design, Response Surface Design, Mixture Design, Distribution, Fit Y by X, Matched Pairs, Fit Model, and Profiler.
With JMP software, Montgomery’s textbook, and Design and Analysis of Experiments by Douglas Montgomery: A Supplement for Using JMP, users will be able to fit the design to the problem, instead of fitting the problem to the design. This book is part of the SAS Press program.

" Now in its third edition, this best-selling book continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications that perform well and deliver correct results. Tom Kyte and Darl Kuhn share a simple philosophy: "you can treat Oracle as a black box and just stick data into it, or you can understand how it works and exploit it as a powerful computing environment." If you choose the latter, then you’ll find that there are few information management problems that you cannot solve quickly and elegantly. This fully revised third edition covers the developments up to Oracle Database 12 c. Significant new content is included surrounding Oracle's new cloud feature set, and especially the use of pluggable databases. Each feature is taught in a proof-by-example manner, not only discussing what it is, but also how it works, how to implement software using it, and the common pitfalls associated with it. Don’t treat Oracle Database as a black-box. Get this book. Get under the hood. Turbo-charge your career. Revised to cover Oracle Database 12 c Proof-by-example approach: Let the evidence be your guide Dives deeply into Oracle Database’s most powerful features"