Data Integration Blueprint And Modeling
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| Author | : Anthony David Giordano |
| Publisher | : Pearson Education |
| Total Pages | : 476 |
| Release | : 2010-12-27 |
| Genre | : Business & Economics |
| ISBN | : 0137085281 |
Making Data Integration Work: How to Systematically Reduce Cost, Improve Quality, and Enhance Effectiveness Today’s enterprises are investing massive resources in data integration. Many possess thousands of point-to-point data integration applications that are costly, undocumented, and difficult to maintain. Data integration now accounts for a major part of the expense and risk of typical data warehousing and business intelligence projects--and, as businesses increasingly rely on analytics, the need for a blueprint for data integration is increasing now more than ever. This book presents the solution: a clear, consistent approach to defining, designing, and building data integration components to reduce cost, simplify management, enhance quality, and improve effectiveness. Leading IBM data management expert Tony Giordano brings together best practices for architecture, design, and methodology, and shows how to do the disciplined work of getting data integration right. Mr. Giordano begins with an overview of the “patterns” of data integration, showing how to build blueprints that smoothly handle both operational and analytic data integration. Next, he walks through the entire project lifecycle, explaining each phase, activity, task, and deliverable through a complete case study. Finally, he shows how to integrate data integration with other information management disciplines, from data governance to metadata. The book’s appendices bring together key principles, detailed models, and a complete data integration glossary. Coverage includes Implementing repeatable, efficient, and well-documented processes for integrating data Lowering costs and improving quality by eliminating unnecessary or duplicative data integrations Managing the high levels of complexity associated with integrating business and technical data Using intuitive graphical design techniques for more effective process and data integration modeling Building end-to-end data integration applications that bring together many complex data sources
| Author | : Anthony David Giordano |
| Publisher | : |
| Total Pages | : 413 |
| Release | : 1900 |
| Genre | : |
| ISBN | : |
Making Data Integration Work: How to Systematically Reduce Cost, Improve Quality, and Enhance Effectiveness Today's enterprises are investing massive resources in data integration. Many possess thousands of point-to-point data integration applications that are costly, undocumented, and difficult to maintain. Data integration now accounts for a major part of the expense and risk of typical data warehousing and business intelligence projects--and, as businesses increasingly rely on analytics, the need for a blueprint for data integration is increasing now more than ever. This book presen.
| Author | : Anthony Giordano |
| Publisher | : |
| Total Pages | : 384 |
| Release | : 2011 |
| Genre | : Data integration |
| ISBN | : 9780137085309 |
| Author | : AnHai Doan |
| Publisher | : Elsevier |
| Total Pages | : 522 |
| Release | : 2012-06-25 |
| Genre | : Computers |
| ISBN | : 0123914795 |
Principles of Data Integration is the first comprehensive textbook of data integration, covering theoretical principles and implementation issues as well as current challenges raised by the semantic web and cloud computing. The book offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand. Readers will also learn how to build their own algorithms and implement their own data integration application. Written by three of the most respected experts in the field, this book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. This text is an ideal resource for database practitioners in industry, including data warehouse engineers, database system designers, data architects/enterprise architects, database researchers, statisticians, and data analysts; students in data analytics and knowledge discovery; and other data professionals working at the R&D and implementation levels. - Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand - Enables you to build your own algorithms and implement your own data integration applications
| Author | : Piethein Strengholt |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 404 |
| Release | : 2020-07-29 |
| Genre | : Computers |
| ISBN | : 1492054739 |
As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata
| Author | : Raul F. Chong |
| Publisher | : IBM Press |
| Total Pages | : 783 |
| Release | : 2013-10-26 |
| Genre | : Computers |
| ISBN | : 0133461920 |
The Easy, Visual Introduction to IBM DB2 Version 10.5 for Linux, UNIX, and Windows Foreword by Judy Huber, Vice President, Distributed Data Servers and Data Warehousing; Director, IBM Canada Laboratory This book covers everything you need to get productive with the latest version of IBM DB2 and apply it to today’s business challenges. It discusses key features introduced in DB2 Versions 10.5, 10.1, and 9.7, including improvements in manageability, integration, security, Big Data support, BLU Acceleration, and cloud computing. DB2 Essentials illuminates key concepts with examples drawn from the authors’ extensive experience with DB2 in enterprise environments. Raul F. Chong and Clara Liu explain how DB2 has evolved, what’s new, and how to choose the right products, editions, and tools. Next, they walk through installation, configuration, security, data access, remote connectivity, and day-to-day administration. Each chapter starts with an illustrative overview to introduce its key concepts using a big picture approach. Clearly explained figures are used extensively, and techniques are presented with intuitive screenshots, diagrams, charts, and tables. Case studies illustrate how “theory” is applied in real-life environments, and hundreds of review questions help you prepare for IBM’s newest DB2 certification exams. Coverage includes • Understanding the role of DB2 in Big Data • Preparing for and executing a smooth installation or upgrade • Understanding the DB2 environment, instances, and databases • Configuring client and server connectivity • Working with database objects • Getting started with BLU Acceleration • Implementing security: authentication and authorization • Understanding concurrency and locking • Maintaining, backing up, and recovering data • Using basic SQL in DB2 environments • Diagnosing and solving DB2 problems This book is for anyone who plans to work with DB2, including DBAs, system administrators, developers, and consultants. It will be a great resource whether you’re upgrading from an older version of DB2, migrating from a competitive database, or learning your first database platform.
| Author | : Dirk Nicol |
| Publisher | : IBM Press |
| Total Pages | : 272 |
| Release | : 2013-04-24 |
| Genre | : Business & Economics |
| ISBN | : 0133094944 |
Navigate the Mobile Landscape with Confidence and Create a Mobile Strategy That Wins in the Market Place Mobile Strategy gives IT leaders the ability to transform their business by offering all the guidance they need to navigate this complex landscape, leverage its opportunities, and protect their investments along the way. IBM’s Dirk Nicol clearly explains key trends and issues across the entire mobile project lifecycle. He offers insights critical to evaluating mobile technologies, supporting BYOD, and integrating mobile, cloud, social, and big data. Throughout, you’ll find proven best practices based on real-world case studies from his extensive experience with IBM’s enterprise customers. Coverage includes • Understanding the profound implications and challenges of consumerized IT in the mobile space • Uncovering powerful new opportunities to drive value from mobile technology • Transforming “systems of record” to “systems of engagement” that fully reflect context and intelligence • Identifying proven patterns for delivering common mobile capabilities in operations, commerce, collaboration, and marketing • Managing security threats related to lost/stolen devices, insecure Wi-Fi, and built-in cameras • Choosing mobile data protection, security, and management options: wrappers, containers, virtualization, mobile Software Development Kits (SDKs), virtual private networks (VPNs), Mobile Device Management (MDM), Mobile Application Management (MAM), and anti-malware • Handling the “app store” distribution model and managing updates • Using mobile middleware to support multiple platforms and back-end connectivity with less complexity • Building and integrating high-quality mobile apps—and getting useful customer feedback to improve them • Addressing international considerations and emerging markets • Mastering methodologies for successfully and rapidly executing mobile projects • Converging mobile, cloud, social, and big data into a single high-value IT delivery platform
| Author | : Murtaza Haider |
| Publisher | : IBM Press |
| Total Pages | : 942 |
| Release | : 2015-12-14 |
| Genre | : Business & Economics |
| ISBN | : 0133991237 |
Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy! Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. You’ll master data science by answering fascinating questions, such as: • Are religious individuals more or less likely to have extramarital affairs? • Do attractive professors get better teaching evaluations? • Does the higher price of cigarettes deter smoking? • What determines housing prices more: lot size or the number of bedrooms? • How do teenagers and older people differ in the way they use social media? • Who is more likely to use online dating services? • Why do some purchase iPhones and others Blackberry devices? • Does the presence of children influence a family’s spending on alcohol? For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.
| Author | : Qamar Shahbaz |
| Publisher | : Elsevier |
| Total Pages | : 181 |
| Release | : 2015-12-08 |
| Genre | : Computers |
| ISBN | : 0128053356 |
Data mapping in a data warehouse is the process of creating a link between two distinct data models' (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle. - Covers all stages of data warehousing and the role of data mapping in each - Includes a data mapping strategy and techniques that can be applied to many situations - Based on the author's years of real-world experience designing solutions
| Author | : Nauman Sheikh |
| Publisher | : Newnes |
| Total Pages | : 234 |
| Release | : 2013-05-06 |
| Genre | : Computers |
| ISBN | : 0124016812 |
Implementing Analytics demystifies the concept, technology and application of analytics and breaks its implementation down to repeatable and manageable steps, making it possible for widespread adoption across all functions of an organization. Implementing Analytics simplifies and helps democratize a very specialized discipline to foster business efficiency and innovation without investing in multi-million dollar technology and manpower. A technology agnostic methodology that breaks down complex tasks like model design and tuning and emphasizes business decisions rather than the technology behind analytics. - Simplifies the understanding of analytics from a technical and functional perspective and shows a wide array of problems that can be tackled using existing technology - Provides a detailed step by step approach to identify opportunities, extract requirements, design variables and build and test models. It further explains the business decision strategies to use analytics models and provides an overview for governance and tuning - Helps formalize analytics projects from staffing, technology and implementation perspectives - Emphasizes machine learning and data mining over statistics and shows how the role of a Data Scientist can be broken down and still deliver the value by building a robust development process
