Data integration blueprint and modeling pdf

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Techniques for a Scalable and Sustainable Architecture paperback. However, few are satisfied with the value of their effort Anthony Giordano is a partner in IBM's Business Analytics and Optimization Consulting Practice and currently leads the Enterprise Information Management Service Line that focuses on data modeling, data integration, master data management, and data governance. He has more than 20 years of experience in the Information Technology field with a focus in the areas of business intelligence, data warehousing, and Information Management.

Modeling the Blueprint for MDM

Search this site. 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. 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.

Search this site. 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.

Top 15 Best Data Integration Books You Should Read

There is one more element often overlooked in this field and remains a key differentiator and the difference between success and failure among the major initiatives I have had the opportunity to witness firsthand — modeling the blueprint for MDM. This is an important first step to take, assuming the business case is completed and approved. It forces us to address the very real challenges up front, before embarking on a journey that our stakeholders must understand and support in order to succeed. Obtaining buy-in and executive support means we all share a common vision for what we are solving for. MDM is more than maintaining a central repository of master data.

Embed Size px x x x x Enterprise Master Data Managementprovides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical ana-lysts, consultants, solution designers, and senior IT decision makers. Written by the IBM data management innovators who are pioneering MDM, this book systemati-cally introduces MDMs key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere elseeverything you need to establish a consis-tent, manageable set of master data, and use it for competitive advantage. This book is a must read for any organization using data-integration or data-interchange technologies, or simply any organization that must trust data. Neal takes the reader through an entertaining and vital journey of SOA information management issues,risks, discovery, and solutions. He provides a fresh perspective that no corporation should overlook; in fact, corporations might head blindly into SOA implementations without this awareness.

Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture by

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.

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.

data integration blueprint and modeling

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