As world activities become more integrated, the rate of data growth has been increasing exponentially. And as a result of this data explosion, current data management methods can become inadequate. People are using the term big data (sometimes referred to as Big Data) to describe this latest industry trend. IBM® is preparing the next generation of technology to meet these data management challenges. To provide the capability of incorporating big data sources and analytics of these sources, IBM developed a stream-computing product that is based on the open source computing framework Apache Hadoop. Each product in the framework provides unique capabilities to the data management environment, and further enhances the value of your data warehouse investment. In this IBM Redbooks® publication, we describe the need for big data in an organization. We then introduce IBM InfoSphere® BigInsights™ and explain how it differs from standard Hadoop. BigInsights provides a packaged Hadoop distribution, a greatly simplified installation of Hadoop and corresponding open source tools for application development, data movement, and cluster management. BigInsights also brings more options for data security, and as a component of the IBM big data platform, it provides potential integration points with the other components of the platform. A new chapter has been added to this edition. Chapter 11 describes IBM Platform Symphony®, which is a new scheduling product that works with IBM Insights, bringing low-latency scheduling and multi-tenancy to IBM InfoSphere BigInsights. The book is designed for clients, consultants, and other technical professionals.

This comprehensive guide to IBM Cognos 10 Business Intelligence tools provides practical, hands-on learning to help you improve your business's data management and analysis capabilities. By mastering key features such as Report Studio, Analysis Studio, and Business Insight, you will be able to make smarter decisions, achieve better results, and gain a deeper understanding of your organization's data. What this Book will help me do Develop advanced reporting skills using IBM Cognos 10 Report Studio and Query Studio. Analyze data effectively with a thorough understanding of Analysis Studio features. Integrate statistical and real-time information into business reports for critical insights. Implement modern strategies to enhance business collaboration and decision-making. Master delivering high-impact business intelligence presentations to broader audiences. Author(s) The authors of this book are experienced IBM Cognos professionals who bring years of business intelligence development and consultancy expertise. They are committed to teaching in a practical and results-driven manner, providing readers with actionable skills. Their insight into IBM Cognos stems from years of real-world application, ensuring the book is rich with valuable advice. Who is it for? This book is ideal for IBM Cognos developers, business intelligence consultants, and analysts with foundational knowledge of Cognos 10 and some experience with Cognos 8. Readers who aim to deepen their understanding of reporting, administration, and analytics will find this guide valuable. It serves as both a learning resource for upgrading skills and a reference for optimizing IBM Cognos environments in professional settings.

IBM® InfoSphere® Master Data Management Reference Data Management Hub (InfoSphere MDM Ref DM Hub) is designed as a ready-to-run application that provides the governance, process, security, and audit control for managing reference data as an enterprise standard, resulting in fewer errors, reduced business risk and cost savings. This IBM Redbooks® publication describes where InfoSphere MDM Ref DM Hub fits into information management reference architecture. It explains the end-to-end process of an InfoSphere MDM Ref DM Hub implementation including the considerations of planning a reference data management project, requirements gathering and analysis, model design in detail, and integration considerations and scenarios. It then shows implementation examples and the ongoing administration tasks. This publication can help IT professionals who are interested or have a need to manage reference data efficiently and implement an InfoSphere MDM Ref DM Hub solution with ease.

Hadoop Beginner's Guide introduces you to the essential concepts and practical applications of Apache Hadoop, one of the leading frameworks for big data processing. You will learn how to set up and use Hadoop to store, manage, and analyze vast amounts of data efficiently. With clear examples and step-by-step instructions, this book is the perfect starting point for beginners. What this Book will help me do Understand the trends leading to the adoption of Hadoop and determine when to use it effectively in your projects. Build and configure Hadoop clusters tailored to your specific needs, enabling efficient data processing. Develop and execute applications on Hadoop using Java and Ruby, with practical examples provided. Leverage Amazon AWS and Elastic MapReduce to deploy Hadoop on the cloud and manage hosted environments. Integrate Hadoop with relational databases using tools like Hive and Sqoop for effective data transfer and querying. Author(s) The author of Hadoop Beginner's Guide is an experienced data engineer with a focus on big data technologies. They have extensive experience deploying Hadoop in various industries and are passionate about making complex systems accessible to newcomers. Their approach combines technical depth with an understanding of the needs of learners, ensuring clarity and relevance throughout the book. Who is it for? This book is designed for professionals who are new to big data processing and want to learn Apache Hadoop from scratch. It is ideal for system administrators, data analysts, and developers with basic programming knowledge in Java or Ruby looking to get started with Hadoop. If you have an interest in leveraging Hadoop for scalable data management and analytics, this book is for you. By the end, you'll gain the confidence and skills to utilize Hadoop effectively in your projects.

Biostatistics is exclusively designed for the undergraduate students of Botany, Biotechnology and Zoology for gaining fundamental knowledge on biostatistics and its applications. Adequate coverage has been provided to the concepts of biostatistics making this book useful in biological data management.

A fresh approach to bridging research design with statistical analysis While good social science requires both research design and statistical analysis, most books treat these two areas separately. Understanding and Applying Research Design introduces an accessible approach to integrating design and statistics, focusing on the processes of posing, testing, and interpreting research questions in the social sciences. The authors analyze real-world data using SPSS software, guiding readers on the overall process of science, focusing on premises, procedures, and designs of social scientific research. Three clearly organized sections move seamlessly from theoretical topics to statistical techniques at the heart of research procedures, and finally, to practical application of research design: Premises of Research introduces the research process and the capabilities of SPSS, with coverage of ethics, Empirical Generalization, and Chi Square and Contingency Table Analysis Procedures of Research explores key quantitative methods in research design including measurement, correlation, regression, and causation Designs of Research outlines various design frameworks, with discussion of survey research, aggregate research, and experiments Throughout the book, SPSS software is used to showcase the discussed techniques, and detailed appendices provide guidance on key statistical procedures and tips for data management. Numerous exercises allow readers to test their comprehension of the presented material, and a related website features additional data sets and SPSS code. Understanding and Applying Research Design is an excellent book for social sciences and education courses on research methods at the upper-undergraduate level. The book is also an insightful reference for professionals who would like to learn how to pose, test, and interpret research questions with confidence.

Business Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks at the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge. Organized into 21 chapters, this book begins with an overview of the kind of knowledge that can be exposed and exploited through the use of BI. It then proceeds with a discussion of information use in the context of how value is created within an organization, how BI can improve the ways of doing business, and organizational preparedness for exploiting the results of a BI program. It also looks at some of the critical factors to be taken into account in the planning and execution of a successful BI program. In addition, the reader is introduced to considerations for developing the BI roadmap, the platforms for analysis such as data warehouses, and the concepts of business metadata. Other chapters focus on data preparation and data discovery, the business rules approach, and data mining techniques and predictive analytics. Finally, emerging technologies such as text analytics and sentiment analysis are considered. This book will be valuable to data management and BI professionals, including senior and middle-level managers, Chief Information Officers and Chief Data Officers, senior business executives and business staff members, database or software engineers, and business analysts. Guides managers through developing, administering, or simply understanding business intelligence technology Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization’s data into actionable knowledge Contains a handy, quick-reference to technologies and terminology

Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts. Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book. Learn basic concepts of measurement and probability theory, data management, and research design Discover basic statistical procedures, including correlation, the t-test, the chi-square and Fisher’s exact tests, and techniques for analyzing nonparametric data Learn advanced techniques based on the general linear model, including ANOVA, ANCOVA, multiple linear regression, and logistic regression Use and interpret statistics for business and quality improvement, medical and public health, and education and psychology Communicate with statistics and critique statistical information presented by others

Discover how to leverage Talend Open Studio for Data Integration to manage and optimize your data workflow. This book provides a hands-on introduction to creating integration jobs and automating data processes using Talend's drag-and-drop interface. Explore practical examples, and realize how powerful and approachable data integration can be. What this Book will help me do Develop and deploy scalable data integration pipelines using Talend Open Studio. Master common data operations like filtering, sorting, transforming, and aggregating. Gain expertise in connecting various data sources, both relational and non-relational. Implement complex flow logic, including conditional processing and dependencies. Learn to package and manage production-ready integration jobs for real-world scenarios. Author(s) Jonathan Bowen is an experienced technologist and author specializing in data integration and software tools. With years of hands-on experience, Jonathan has guided many organizations in adopting efficient data workflows. He conveys technical concepts with clarity and provides practical, actionable content to help readers succeed. Who is it for? This book is perfect for developers, business analysts, and IT professionals tasked with integration projects. Whether you're a novice to data integration or looking to deepen your hands-on experience with Talend, this guide will support your journey. Some prior familiarity with SQL and a data management background are advantageous. Choose this book if you aim to become a proficient data integrator.

This IBM® Redbooks® publication provides a detailed look at the features, benefits, and capabilities of the IBM System Storage® N series hardware offerings. The IBM System Storage N series systems can help you tackle the challenge of effective data management by using virtualization technology and a unified storage architecture. The N series delivers low- to high-end enterprise storage and data management capabilities with midrange affordability. Built-in serviceability and manageability features help support your efforts to increase reliability; simplify and unify storage infrastructure and maintenance; and deliver exceptional economy. The IBM System Storage N series systems provide a range of reliable, scalable storage solutions to meet various storage requirements. These capabilities are achieved by using network access protocols such as Network File System (NFS), Common Internet File System (CIFS), HTTP, and iSCSI, and storage area network technologies such as Fibre Channel. Using built-in Redundant Array of Independent Disks (RAID) technologies, all data is protected with options to enhance protection through mirroring, replication, Snapshots, and backup. These storage systems also have simple management interfaces that make installation, administration, and troubleshooting straightforward. In addition, this book also addresses high-availability solutions including clustering and MetroCluster supporting highest business continuity requirements. MetroCluster is a unique solution that combines array-based clustering with synchronous mirroring to deliver continuous availability.

Master Oracle’s PeopleSoft PeopleTools Data Administration and Upgrade Toolset Maximize data integrity, maintain peak application performance, and keep your PeopleSoft environment up to date. PeopleSoft PeopleTools Data Management and Upgrade Handbook explains the latest techniques and provides best practices, case studies, and programming examples. Find out how to develop and deploy data mover scripts, audit database health, apply patches, and generate project comparison reports. This Oracle Press guide offers thorough coverage of Oracle’s PeopleSoft life cycle management tools. Understand PeopleSoft PeopleTools architecture Manage metadata using PeopleSoft Application Designer Create and execute PeopleSoft Data Mover scripts Learn how to use PeopleSoft Data Archive Manager Read best practices for applying updates, patches, and fixes Implement PeopleSoft change control features Build automated functional tests Plan and execute application and platform upgrades

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

Data is getting bigger and more complex by the day, and so are the choices in handling that data. As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology. Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each. You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2). Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once. Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs. What You Need: To get the most of of this book you'll have to follow along, and that means you'll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

IBM’s Definitive One-Stop Guide to IMS Versions 12, 11, and 10: for Every IMS DBA, Developer, and System Programmer Over 90% of the top Fortune® 1000 companies rely on IBM’s Information Management System (IMS) for their most critical IBM System z® data management needs: 50,000,000,000+ transactions run through IMS databases every day. What’s more, IBM continues to upgrade IMS: Versions 12, 11, and 10 meet today’s business challenges more flexibly and at a lower cost than ever before. In An Introduction to IMS, Second Edition, leading IBM experts present the definitive technical introduction to these versions of IMS. More than a complete tutorial, this book provides up-to-date examples, cases, problems, solutions, and a complete glossary of IMS terminology. Prerequisite reading for the current IBM IMS Mastery Certification Program, it reflects major recent enhancements such as dynamic information generation; new access, interoperability and development tools; improved SOA support; and much more. Whether you’re a DBA, database developer, or system programmer, it brings together all the knowledge you’ll need to succeed with IMS in today’s mission critical environments. Coverage includes What IMS is, how it works, how it has evolved, and how it fits into modern enterprise IT architectures Providing secure access to IMS via IMS-managed application programs Understanding how IMS and z/OS® work together to use hardware and software more efficiently Setting up, running, and maintaining IMS Running IMS Database Manager: using the IMS Hierarchical Database Model, sharing data, and reorganizing databases Understanding, utilizing, and optimizing IMS Transaction Manager IMS application development: application programming for the IMS Database and IMS Transaction Managers, editing and formatting messages, and programming applications in Java™ IMS system administration: the IMS system definition process, customizing IMS, security, logging, IMS operations, database and system recovery, and more IMS in Parallel Sysplex® environments: ensuring high availability, providing adequate capacity, and balancing workloads

To make better informed business decisions, better serve clients, and increase operational efficiencies, you must be aware of changes to key data as they occur. In addition, you must enable the immediate delivery of this information to the people and processes that need to act upon it. This ability to sense and respond to data changes is fundamental to dynamic warehousing, master data management, and many other key initiatives. A major challenge in providing this type of environment is determining how to tie all the independent systems together and process the immense data flow requirements. IBM® InfoSphere® Change Data Capture (InfoSphere CDC) can respond to that challenge, providing programming-free data integration, and eliminating redundant data transfer, to minimize the impact on production systems. In this IBM Redbooks® publication, we show you examples of how InfoSphere CDC can be used to implement integrated systems, to keep those systems updated immediately as changes occur, and to use your existing infrastructure and scale up as your workload grows. InfoSphere CDC can also enhance your investment in other software, such as IBM DataStage® and IBM QualityStage®, IBM InfoSphere Warehouse, and IBM InfoSphere Master Data Management Server, enabling real-time and event-driven processes. Enable the integration of your critical data and make it immediately available as your business needs it.

SAP NetWeaver MDM 7.1 Administrator's Guide acts as a complete resource for mastering the administration and configuration of SAP's Master Data Management solution: NetWeaver MDM 7.1. With a hands-on and practical approach, this book connects theoretical understanding with real-world application, tailored specifically for MDM administrators. What this Book will help me do Understand the core concepts and business scenarios associated with SAP NetWeaver MDM. Master the configuration of MDM Console, Servers, repositories, and the underlying database. Learn to maintain repository integrity through backup, restore, and management techniques. Automate data operations like importing and syndicating through MDM tools. Grasp the integration aspects of MDM with other SAP NetWeaver components. Author(s) Uday Rao is an experienced administrator and consultant in SAP systems, specializing in Master Data Management. With years of field experience, Uday brings deep technical insights combined with an approach that simplifies complex administration tasks. His guide emphasizes practical scenarios with step-by-step instructions that empower SAP professionals. Who is it for? This book is ideal for SAP administrators aiming to specialize in Master Data Management with NetWeaver MDM. It targets professionals with foundational knowledge in SAP who are looking to gain expertise in configuring and managing MDM systems. Novices in SAP MDM can still benefit from the guide's structured approach. Whether you're managing corporate data systems or overseeing MDM projects, this guide aligns with your goals.

Using Agile methods, you can bring far greater innovation, value, and quality to any data warehouse, business intelligence, or analytics project. However, conventional Agile methodologies must be carefully adapted to address the unique characteristics of DW/BI projects. In , Agile pioneer Ken Collier shows how to do just that. Agile Analytics Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets; support enormous and fast-growing data volumes; and more. Collier's techniques offer equal value whether your projects involve "back-end" data management, "front-end" business analysis, or both. Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your agile DW/BI project community works together towards success Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, DBA, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way.

Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers the various applied areas of data, including data modelling and data model management, data quality, data governance, enterprise information management, database design, data warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality. The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results. Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management. Presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios Teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions Includes the detail needed to illustrate how the fundamental principles are used in current business practice

Database Modeling and Design, Fifth Edition, focuses on techniques for database design in relational database systems. This extensively revised fifth edition features clear explanations, lots of terrific examples and an illustrative case, and practical advice, with design rules that are applicable to any SQL-based system. The common examples are based on real-life experiences and have been thoroughly class-tested. This book is immediately useful to anyone tasked with the creation of data models for the integration of large-scale enterprise data. It is ideal for a stand-alone data management course focused on logical database design, or a supplement to an introductory text for introductory database management. In-depth detail and plenty of real-world, practical examples throughout Loaded with design rules and illustrative case studies that are applicable to any SQL, UML, or XML-based system Immediately useful to anyone tasked with the creation of data models for the integration of large-scale enterprise data

The DB2® pureXML® feature offers sophisticated capabilities to store, process and manage XML data in its native hierarchical format. By integrating XML data intact into a relational database structure, users can take full advantage of DB2's relational data management features. In this IBM® Redbooks® publication, we document the steps for the implementation of a simple but meaningful XML application scenario. We have chosen to provide samples in COBOL and Java™ language. The purpose is to provide an easy path to follow to integrate the XML data type for the traditional DB2 for z/OS® user. We also add considerations for the data administrator and suggest best practices for ease of use and better performance.