“This book is a splendid and valuable addition to this subject. The whole book is well written and I have no hesitation to recommend that this can be adapted as a textbook for graduate courses in Business Intelligence and Data Mining.” Dr. Edi Shivaji, Des Moines, Iowa “As a complete novice to this area just starting out on a MBA course I found the book incredibly useful and very easy to follow and understand. The concepts are clearly explained and make it an easy task to gain an understanding of the subject matter.” -- Mr. Craig Domoney, South Africa. Business Intelligence and Data Mining is a conversational and informative book in the exploding area of Business Analytics. Using this book, one can easily gain the intuition about the area, along with a solid toolset of major data mining techniques and platforms. This book can thus be gainfully used as a textbook for a college course. It is also short and accessible enough for a busy executive to become a quasi-expert in this area in a couple of hours. Every chapter begins with a case-let from the real world, and ends with a case study that runs across the chapters.

The importance of modern computer networks is steadily growing as increasing amounts of data are exchanged over company intranets and the Internet. Understanding current networking technologies and communication protocols that are available for the IBM® mainframe and System z® operating systems is essential for setting up your network infrastructure with IBM z/VSE®. This IBM Redbooks® publication helps you install, tailor, and configure new networking options for z/VSE that are available with TCP/IP for VSE/ESA, IPv6/VSE, and Fast Path to Linux on System z (Linux Fast Path). We put a strong focus on network security and describe how the new OpenSSL-based SSL runtime component can be used to enhance the security of your business. This IBM Redbooks publication extends the information that is provided in Security on IBM z/VSE, SG24-7691.

A practical guide to understanding economic forecasts In Inside the Crystal Ball: How to Make and Use Forecasts, UBS Chief U.S. Economist Maury Harris helps readers improve their own forecasting abilities by examining the elements and processes that characterize successful and failed forecasts. The book: , named among Bloomberg's 50 Most Influential People in Global Finance. Provides insights from Maury Harris Harris walks readers through the real-life steps he and other successful forecasters take in preparing their projections. These valuable procedures can help forecast users evaluate forecasts and forecasters as inputs for making their own specific business and investment decisions. Demonstrates "best practices" in the assembly and evaluation of forecasts. . Harris explores the prerequisites for sound forecasting judgment—a good sense of history and an understanding of contemporary theoretical frameworks—in readable and illuminating detail. Emphasizes the critical role of judgment in improving projections derived from purely statistical methodologies Harris also offers procedural guidelines for special circumstances, such as natural disasters, terrorist threats, gyrating oil and stock prices, and international economic crises. Addresses everyday forecasting issues, including the credibility of government statistics and analyses, fickle consumers, and volatile business spirits. —including the now commonplace hypothesis of sustained economic sluggishness, possible inflation outcomes in an environment of falling unemployment, and projecting interest rates when central banks implement unprecedented low interest rate and quantitative easing (QE) policies. Evaluates major contemporary forecasting issues and those of other leading economists in his almost four-decade career as a professional economist and forecaster. Dr. Harris presents his personal recipes for long-term credibility and commercial success to anyone offering advice about the future. Brings to life Harris's own experiences

Concise, thoroughly class-tested primer that features basic statistical concepts in the concepts in the context of analytics, resampling, and the bootstrap A uniquely developed presentation of key statistical topics, Introductory Statistics and Analytics: A Resampling Perspective provides an accessible approach to statistical analytics, resampling, and the bootstrap for readers with various levels of exposure to basic probability and statistics. Originally class-tested at one of the first online learning companies in the discipline, www.statistics.com, the book primarily focuses on applications of statistical concepts developed via resampling, with a background discussion of mathematical theory. This feature stresses statistical literacy and understanding, which demonstrates the fundamental basis for statistical inference and demystifies traditional formulas. The book begins with illustrations that have the essential statistical topics interwoven throughout before moving on to demonstrate the proper design of studies. Meeting all of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) requirements for an introductory statistics course, Introductory Statistics and Analytics: A Resampling Perspective also includes: Over 300 "Try It Yourself" exercises and intermittent practice questions, which challenge readers at multiple levels to investigate and explore key statistical concepts Numerous interactive links designed to provide solutions to exercises and further information on crucial concepts Linkages that connect statistics to the rapidly growing field of data science Multiple discussions of various software systems, such as Microsoft Office Excel®, StatCrunch, and R, to develop and analyze data Areas of concern and/or contrasting points-of-view indicated through the use of "Caution" icons Introductory Statistics and Analytics: A Resampling Perspective is an excellent primary textbook for courses in preliminary statistics as well as a supplement for courses in upper-level statistics and related fields, such as biostatistics and econometrics. The book is also a general reference for readers interested in revisiting the value of statistics.

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. This book is designed for use as a scientific/business calculator so that you can get numerical solutions to problems involving a wide array of mathematics using MATLAB. Just look up the function you want in the book and you are ready to use it in MATLAB or use the book to learn about the enormous range of options that MATLAB offers. MATLAB Numerical Calculations focuses on MATLAB capabilities to give you numerical solutions to problems you are likely to encounter in your professional or scholastic life. It introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. Starting with a look at basic MATLAB functionality with integers, rational numbers and real and complex numbers, and MATLAB's relationship with Maple, you will learn how to solve equations in MATLAB, and how to simplify the results. You will see how MATLAB incorporates vector, matrix and character variables, and functions thereof. MATLAB is a powerful tool used to defined, manipulate and simplify complex algebraic expressions. With MATLAB you can also work with ease in matrix algebra, making use of commands which allow you to find eigenvalues, eigenvectors, determinants, norms and various matrix decompositions, among many other features. Lastly, you will see how you can write scripts and use MATLAB to explore numerical analysis, finding approximations of integrals, derivatives and numerical solutions of differential equations.

Numerical Methods with MATLAB provides a highly-practical reference work to assist anyone working with numerical methods. A wide range of techniques are introduced, their merits discussed and fully working MATLAB code samples supplied to demonstrate how they can be coded and applied. Numerical methods have wide applicability across many scientific, mathematical, and engineering disciplines and are most often employed in situations where working out an exact answer to the problem by another method is impractical. Numerical Methods with MATLAB presents each topic in a concise and readable format to help you learn fast and effectively. It is not intended to be a reference work to the conceptual theory that underpins the numerical methods themselves. A wide range of reference works are readily available to supply this information. If, however, you want assistance in applying numerical methods then this is the book for you.

Many corporations are finding that the size of their data sets are outgrowing the capability of their systems to store and process them. The data is becoming too big to manage and use with traditional tools. The solution: implementing a big data system. As Big Data Made Easy: A Working Guide to the Complete Hadoop Toolset shows, Apache Hadoop offers a scalable, fault-tolerant system for storing and processing data in parallel. It has a very rich toolset that allows for storage (Hadoop), configuration (YARN and ZooKeeper), collection (Nutch and Solr), processing (Storm, Pig, and Map Reduce), scheduling (Oozie), moving (Sqoop and Avro), monitoring (Chukwa, Ambari, and Hue), testing (Big Top), and analysis (Hive). The problem is that the Internet offers IT pros wading into big data many versions of the truth and some outright falsehoods born of ignorance. What is needed is a book just like this one: a wide-ranging but easily understood set of instructions to explain where to get Hadoop tools, what they can do, how to install them, how to configure them, how to integrate them, and how to use them successfully. And you need an expert who has worked in this area for a decade—someone just like author and big data expert Mike Frampton. Big Data Made Easy approaches the problem of managing massive data sets from a systems perspective, and it explains the roles for each project (like architect and tester, for example) and shows how the Hadoop toolset can be used at each system stage. It explains, in an easily understood manner and through numerous examples, how to use each tool. The book also explains the sliding scale of tools available depending upon data size and when and how to use them. Big Data Made Easy shows developers and architects, as well as testers and project managers, how to: Store big data Configure big data Process big data Schedule processes Move data among SQL and NoSQL systems Monitor data Perform big data analytics Report on big data processes and projects Test big data systems Big Data Made Easy also explains the best part, which is that this toolset is free. Anyone can download it and—with the help of this book—start to use it within a day. With the skills this book will teach you under your belt, you will add value to your company or client immediately, not to mention your career.

Master the essentials of Informatica PowerCenter 9.x with this comprehensive guide. Whether you are new to the platform or an experienced user, this book provides the knowledge and techniques needed to extract, integrate, and manage data effectively across diverse systems. By learning key functionalities and advanced techniques, you'll become proficient in creating and optimizing data integration workflows. What this Book will help me do Install, configure, and customize Informatica PowerCenter to suit your project requirements. Understand graphical interfaces such as the Designer and Workflow Manager for effective development. Implement data warehousing concepts like Slowly Changing Dimensions (SCDs) using Informatica tools. Optimize data integration workflows through performance tuning and advanced debugging techniques. Execute seamless migrations of components across environments using repository management features. Author(s) Rahul Malewar is an experienced data integration specialist with a strong background in Informatica and data warehousing. With years of practical experience in implementing and deploying complex Informatica solutions, Rahul brings technical expertise combined with a clear and accessible teaching style. His books and courses are widely recognized for helping readers efficiently tackle real-world data challenges. Who is it for? This book is best suited for IT professionals, data analysts, and developers interested in mastering data integration concepts and tools through Informatica PowerCenter. If you work in data warehousing or are stepping into the field, this book provides essential knowledge. Beginner users will find step-by-step guidance, while experienced professionals will deepen their expertise. Prior knowledge in programming and data warehousing is beneficial.

This book, "Cassandra High Availability", equips you with the knowledge and practical skills to harness Apache Cassandra's capabilities for building resilient, scalable, and highly-available systems. Suitable for developers or DevOps engineers with foundational knowledge of Cassandra, this resource takes you deeper into advanced topics necessary for maintaining robust distributed systems. What this Book will help me do Understand and utilize Cassandra's replication protocols and consistency levels to balance performance and reliability. Configure and manage multi-data-center setups in Cassandra for failover and geographic redundancy. Implement techniques to efficiently scale your Cassandra cluster with no downtime. Learn how to design high-availability data models optimized for performance and resilience. Identify and avoid common anti-patterns in Cassandra to maintain system efficiency and reliability. Author(s) None Strickland, the author of "Cassandra High Availability", is an experienced data engineer with a deep understanding of distributed systems and database technologies. None has worked extensively with Apache Cassandra in designing and optimizing scalable infrastructures. They bring a hands-on and detailed approach to explaining complex topics, making them accessible to both developers and system operators. Who is it for? This book is tailored for developers and DevOps engineers who have foundational knowledge of Apache Cassandra and are aiming to deepen their expertise. If your goal is to design, manage, and optimize high-availability distributed systems, this book provides practical strategies and technical insights for mastering Cassandra's capabilities. Ideal for those seeking to build fault-tolerant, scalable infrastructures.

Embark on a journey to master Hadoop and its advanced features with this comprehensive book. "Mastering Hadoop" equips you with the knowledge needed to tackle complex data processing challenges and optimize your Hadoop workflows. With clear explanations and practical examples, this book is your guide to becoming proficient in leveraging Hadoop technologies. What this Book will help me do Optimize Hadoop MapReduce jobs, Pig scripts, and Hive queries for better performance. Understand and employ advanced data formats and Hadoop I/O techniques. Learn to integrate low-latency processing with Storm on YARN. Explore the cloud deployment of Hadoop and advanced HDFS alternatives. Enhance Hadoop security and master techniques for analytics using Hadoop. Author(s) None Karanth is an experienced Hadoop professional with years of expertise in data processing and distributed computing. With a practical and methodical approach, None has crafted this book to empower learners with the essentials and advanced features of Hadoop. None's focus on performance optimization and real-world applications helps bridge the gap between theory and practice. Who is it for? This book is ideal for data engineers and software developers familiar with the basics of Hadoop who seek to advance their understanding. If you aim to enhance Hadoop performance or adopt new features like YARN and Storm, this book is for you. Readers interested in Hadoop deployment, optimization, and newer capabilities will also greatly benefit. It's perfect for anyone aiming to become a Hadoop expert, from intermediate learners to advanced practitioners.

This IBM® Redbooks® publication provides a technical overview of the features, functions, and enhancements available in IBM i 7.1, including all the Technology Refresh (TR) levels from TR1 to TR7. It provides a summary and brief explanation of the many capabilities and functions in the operating system. It also describes many of the licensed programs and application development tools that are associated with IBM i. The information provided in this book is useful for clients, IBM Business Partners, and IBM service professionals who are involved with planning, supporting, upgrading, and implementing IBM i 7.1 solutions.

MATLAB enables you to work with its graphics capabilities in almost all areas of the experimental sciences and engineering. The commands that MATLAB implements in job related graphics are quite useful and are very efficient. MATLAB has functions for working with two-dimensional and three-dimensional graphics, statistical graphs, curves and surfaces in explicit, implicit, parametric and polar coordinates. It also works perfectly with twisted curves, surfaces, volumes and graphical interpolation. MATLAB Graphical Programming addresses all these issues by developing the following topics:This book is a reference designed to give you a simple syntax example of the commands and to graph it so that you can see the result for: Two dimensional graphics Statistical graphics Curves in explicit coordinates Curves in parametric coordinates Curves in polar coordinates Logarithmic and semi-logarithmic plots Bar graphs and histograms sectors Three-dimensional graphics Twisted curves and surfaces Graphs of surfaces, meshes and contours Graphs of surfaces in explicit coordinates parametric surfaces Viewing volumes and specialized graphics Special commands for graphics

Learn how to leverage the power of R for geospatial analysis in this comprehensive guide. Whether you're processing spatial datasets, creating publication-quality maps, or performing GIS operations, this book covers the necessary tools and techniques for effective analysis, without requiring prior programming knowledge. What this Book will help me do Discover how to manipulate and analyze geospatial data effectively using R. Gain proficiency in loading, reshaping, and visualizing spatial data. Master key concepts like spatial queries and overlays for GIS tasks. Learn to automate spatial data workflows using reproducible R scripts. Create high-quality visualizations and maps tailored to your datasets. Author(s) None Dorman, the author of this book, is an experienced data science educator and practitioner with a particular focus on geospatial data analysis in R. With years of teaching and applied geospatial research, Dorman brings expertise in making advanced topics approachable. Their practical approach ensures readers can immediately put concepts into practice. Who is it for? This book is ideal for GIS analysts, geospatial researchers, educators, and students looking to enhance their skillset with R programming. It's particularly suited for those familiar with geographic concepts like coordinates but new to programming or R. If you aim to efficiently analyze spatial data and produce professional-grade visualizations and GIS analyses, this book is for you.

Database Systems: A Pragmatic Approach provides a comprehensive, yet concise introduction to database systems. It discusses the database as an essential component of a software system, as well as a valuable, mission critical corporate resource. The book is based on lecture notes that have been tested and proven over several years, with outstanding results. It also exemplifies mastery of the technique of combining and balancing theory with practice, to give students their best chance at success. Upholding his aim for brevity, comprehensive coverage, and relevance, author Elvis C. Foster's practical and methodical discussion style gets straight to the salient issues, and avoids unnecessary fluff as well as an overkill of theoretical calculations. The book discusses concepts, principles, design, implementation, and management issues of databases. Each chapter is organized systematically into brief, reader-friendly sections, with itemization of the important points to be remembered. It adopts a methodical and pragmatic approach to solving database systems problems. Diagrams and illustrations also sum up the salient points to enhance learning. Additionally, the book includes a number of Foster's original methodologies that add clarity and creativity to the database modeling and design experience while making a novel contribution to the discipline. Everything combines to make Database Systems: A Pragmatic Approach an excellent textbook for students, and an excellent resource on theory for the practitioner.

MATLAB Mathematical Analysis is a reference book that presents the techniques of mathematical analysis through examples and exercises resolved with MATLAB software. The purpose is to give you examples of the mathematical analysis functions offered by MATLAB so that you can use them in your daily work regardless of the application. The book supposes proper training in the mathematics and so presents the basic knowledge required to be able to use MATLAB for calculational or symbolic solutions to your problems for a vast amount of MATLAB functions. The book begins by introducing the reader to the use of numbers, operators, variables and functions in the MATLAB environment. Then it delves into working with complex variables. A large section is devoted to working with and developing graphical representations of curves, surfaces and volumes. MATLAB functions allow working with two-dimensional and three-dimensional graphics, statistical graphs, curves and surfaces in explicit, implicit, parametric and polar coordinates. Additional work implements twisted curves, surfaces, meshes, contours, volumes and graphical interpolation. The following part covers limits, functions, continuity and numerical and power series. Then differentiation is addressed in one and several variables including differential theorems for vector fields. Thereafter the topic of integration is handled including improper integrals, definite and indefinite integration, integration in multiple variables and multiple integrals and their applications. Differential equations are exemplified in detail, Laplace transforms, Tayor series, and the Runga-Kutta method and partial differential equations.

Thinking of migrating to PostgreSQL? This clear, fast-paced introduction helps you understand and use this open source database system. Not only will you learn about the enterprise class features in versions 9.2, 9.3, and 9.4, you’ll also discover that PostgeSQL is more than a database system—it’s also an impressive application platform.

R Recipes is your handy problem-solution reference for learning and using the popular R programming language for statistics and other numerical analysis. Packed with hundreds of code and visual recipes, this book helps you to quickly learn the fundamentals and explore the frontiers of programming, analyzing and using R. R Recipes provides textual and visual recipes for easy and productive templates for use and re-use in your day-to-day R programming and data analysis practice. Whether you're in finance, cloud computing, big or small data analytics, or other applied computational and data science - R Recipes should be a staple for your code reference library.

SQL Server Integration Services Design Patterns is newly-revised for SQL Server 2014, and is a book of recipes for SQL Server Integration Services (SSIS). Design patterns in the book help to solve common problems encountered when developing data integration solutions. The patterns and solution examples in the book increase your efficiency as an SSIS developer, because you do not have to design and code from scratch with each new problem you face. The book's team of expert authors take you through numerous design patterns that you'll soon be using every day, providing the thought process and technical details needed to support their solutions. SQL Server Integration Services Design Patterns goes beyond the surface of the immediate problems to be solved, delving into why particular problems should be solved in certain ways. You'll learn more about SSIS as a result, and you'll learn by practical example. Where appropriate, the book provides examples of alternative patterns and discusses when and where they should be used. Highlights of the book include sections on ETL Instrumentation, SSIS Frameworks, Business Intelligence Markup Language, and Dependency Services. Takes you through solutions to common data integration challenges Provides examples involving Business Intelligence Markup Language Teaches SSIS using practical examples

Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects. Shares the specific experience of leading researchers and techniques developed to handle data problems in the realm of software engineering Explains how to start a project of data science for software engineering as well as how to identify and avoid likely pitfalls Provides a wide range of useful qualitative and quantitative principles ranging from very simple to cutting edge research Addresses current challenges with software engineering data such as lack of local data, access issues due to data privacy, increasing data quality via cleaning of spurious chunks in data

This IBM® Redpaper Redbooks® publication introduces the IBM System z® New Application License Charges (zNALC) pricing structure and provides examples of zNALC workload scenarios. It describes the products that can be run on a zNALC logical partition (LPAR), reasons to consider such an implementation, and covers the following topics: Using the IBM WebSphere Application Server Liberty profile to host applications within an IBM CICS® environment and how it interacts with CICS applications and resources Security technologies available to applications that are hosted within a WebSphere Application Server Liberty profile in CICS How to implement modern presentation in CICS with a CICS Liberty Java virtual machine (JVM) server How to share scenarios to develop Liberty JVM applications to gain benefits from IBM CICS Transaction Server for IBM z/OS® Value Unit Edition Considerations when using mobile devices to interact with CICS applications and explains specific CICS technologies for connecting mobile devices by using the z/OS Value Unit Edition How IBM Operational Decision Manager for z/OS runs in the transaction server to provide decision management services for CICS COBOL and PL/I applications Installing the CICS Transaction Server for z/OS (CICS TS) Feature Pack for Modern Batch to enable the IBM WebSphere® batch environment to schedule and manage batch applications in CICS This book also covers what is commonly referred to as plain old Java objects (POJOs). The Java virtual machine (JVM) server is a full-fledged JVM that includes support for Open Service Gateway initiative (OSGi) bundles. It can be used to host open source Java frameworks and does just about anything you want to do with Java on the mainframe. POJO applications can also qualify for deployment using the Value Unit Edition. Read about how to configure and deploy them in this companion Redbooks publication: IBM CICS and the JVM server: Developing and Deploying Java Applications, SG24-8038 Examples of POJOs are terminal-initiated transactions, CICS web support, web services, requests received via IP CICS sockets, and messages coming in via IBM WebSphere MQ messaging software.