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Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines: Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked.Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs.  Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines.  Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way.Learn how to quickly define scope and architecture before programming starts Includes techniques of process and data engineering that enable iterative and incremental delivery Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges Use the provided 120-day road map to establish a robust, agile data warehousing program

Extreme Scoping: An Agile Approach to Enterprise Data Warehousing and Business Intelligence (Paperback or Softback) 1.65

CUTTING-EDGE CONTENT AND GUIDANCE FROM A DATA WAREHOUSING EXPERT―NOW EXPANDED TO REFLECT FIELD TRENDS Data warehousing has revolutionized the way businesses in a wide variety of industries perform analysis and make strategic decisions. Since the first edition of Data Warehousing Fundamentals, numerous enterprises have implemented data warehouse systems and reaped enormous benefits. Many more are in the process of doing so. Now, this new, revised edition covers the essential fundamentals of data warehousing and business intelligence as well as significant recent trends in the field. The author provides an enhanced, comprehensive overview of data warehousing together with in-depth explanations of critical issues in planning, design, deployment, and ongoing maintenance. IT professionals eager to get into the field will gain a clear understanding of techniques for data extraction from source systems, data cleansing, data transformations, data warehouse architecture and infrastructure, and the various methods for information delivery. This practical Second Edition highlights the areas of data warehousing and business intelligence where high-impact technological progress has been made. Discussions on developments include data marts, real-time information delivery, data visualization, requirements gathering methods, multi-tier architecture, OLAP applications, Web clickstream analysis, data warehouse appliances, and data mining techniques. The book also contains review questions and exercises for each chapter, appropriate for self-study or classroom work, industry examples of real-world situations, and several appendices with valuable information. Specifically written for professionals responsible for designing, implementing, or maintaining data warehousing systems, Data Warehousing Fundamentals presents agile, thorough, and systematic development principles for the IT professional and anyone working or researching in information management.

Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines: Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked.Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs.  Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines.  Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way.Learn how to quickly define scope and architecture before programming starts Includes techniques of process and data engineering that enable iterative and incremental delivery Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges Use the provided 120-day road map to establish a robust, agile data warehousing program

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You have to make sense of enormous amounts of data, and while the notion of “agile data warehousing might sound tricky, it can yield as much as a 3-to-1 speed advantage while cutting project costs in half. Bring this highly effective technique to your organization with the wisdom of agile data warehousing expert Ralph Hughes. Agile Data Warehousing Project Management will give you a thorough introduction to the method as you would practice it in the project room to build a serious “data mart. Regardless of where you are today, this step-by-step implementation guide will prepare you to join or even lead a team in visualizing, building, and validating a single component to an enterprise data warehouse.Provides a thorough grounding on the mechanics of Scrum as well as practical advice on keeping your team on trackIncludes strategies for getting accurate and actionable requirements from a team’s business partnerRevolutionary estimating techniques that make forecasting labor far more understandable and accurateDemonstrates a blends of Agile methods to simplify team management and synchronize inputs across IT specialtiesEnables you and your teams to start simple and progress steadily to world-class performance levels

Cloud Data Warehousing Volume I 0.66

Organization of data warehouses is a vital, but often neglected, aspect of growing an enterprise. Unlike most books on the subject that focus on either the technical aspects of building data warehouses or on business strategies, this valuable reference synthesizes technological know-how with managerial best practices to show how improved alignment between data warehouse plans and business strategies can lead to successful data warehouse adoption capable of supporting an enterprise’s entire infrastructure.Strategic Data Warehousing: Achieving Alignment with Business provides data warehouse developers, business managers, and IT professionals and administrators with an integrated approach to achieving successful and sustainable alignment of data warehouses and business goals. More complete than any other text in the field, this comprehensive reference details the joint roles and responsibilities of the data warehouse and business managers in achieving strategic alignment, business user satisfaction, technical integration, and improved flexibility. Complete with case studies that depict real-world scenarios, the text: Examines the organizational, user, data, and technological factors proven to promote successful data warehousing Includes actionable solutions for achieving strategic alignment Provides a model that readers can apply in aligning their own data warehouse needs and business goals Achieving sustainable alignment between the data warehouse and business strategies is a continuous process. Armed with this valuable reference, readers will be able to gain the solid understanding of the organizational, technical, data, and user factors needed to promote a successful data warehouse adoption and become active partners in leveraging this powerful, but often overlooked, information reso

Data warehousing is one of the hottest business topics, and there’s more to understanding data warehousing technologies than you might think. Find out the basics of data warehousing and how it facilitates data mining and business intelligence with Data Warehousing For Dummies, 2nd Edition. Data is probably your company’s most important asset, so your data warehouse should serve your needs. The fully updated Second Edition of Data Warehousing For Dummies helps you understand, develop, implement, and use data warehouses, and offers a sneak peek into their future. You’ll learn to: Analyze top-down and bottom-up data warehouse designs Understand the structure and technologies of data warehouses, operational data stores, and data marts Choose your project team and apply best development practices to your data warehousing projects Implement a data warehouse, step by step, and involve end-users in the process Review and upgrade existing data storage to make it serve your needs Comprehend OLAP, column-wise databases, hardware assisted databases, and middleware Use data mining intelligently and find what you need Make informed choices about consultants and data warehousing products Data Warehousing For Dummies, 2nd Edition also shows you how to involve users in the testing process and gain valuable feedback, what it takes to successfully manage a data warehouse project, and how to tell if your project is on track. You’ll find it’s the most useful source of data on the topic!

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CUTTING-EDGE CONTENT AND GUIDANCE FROM A DATA WAREHOUSING EXPERT―NOW EXPANDED TO REFLECT FIELD TRENDS Data warehousing has revolutionized the way businesses in a wide variety of industries perform analysis and make strategic decisions. Since the first edition of Data Warehousing Fundamentals, numerous enterprises have implemented data warehouse systems and reaped enormous benefits. Many more are in the process of doing so. Now, this new, revised edition covers the essential fundamentals of data warehousing and business intelligence as well as significant recent trends in the field. The author provides an enhanced, comprehensive overview of data warehousing together with in-depth explanations of critical issues in planning, design, deployment, and ongoing maintenance. IT professionals eager to get into the field will gain a clear understanding of techniques for data extraction from source systems, data cleansing, data transformations, data warehouse architecture and infrastructure, and the various methods for information delivery. This practical Second Edition highlights the areas of data warehousing and business intelligence where high-impact technological progress has been made. Discussions on developments include data marts, real-time information delivery, data visualization, requirements gathering methods, multi-tier architecture, OLAP applications, Web clickstream analysis, data warehouse appliances, and data mining techniques. The book also contains review questions and exercises for each chapter, appropriate for self-study or classroom work, industry examples of real-world situations, and several appendices with valuable information. Specifically written for professionals responsible for designing, implementing, or maintaining data warehousing systems, Data Warehousing Fundamentals presents agile, thorough, and systematic development principles for the IT professional and anyone working or researching in information management.

A revolutionary new approach to unearthing business opportunities, from the father of the data warehouseLet Bill Inmon, the father of the data warehouse, along with Robert Terdeman and Claudia Imhoff, introduce you to exploration warehousing, an innovative new approach to finding business opportunities hidden in patterns of data. In this groundbreaking book, they clearly explain the exploration process and identify the types of data warehouse designs best suited for exploration. They then outline the steps that must be followed in order to turn data into a competitive advantage. Using numerous case examples, the authors describe original exploration techniques and demonstrate how IT managers can work together with business managers to identify significant value in the data. These patterns can reveal opportunities in the marketplace for new products and services, when to discontinue products and services, where to streamline operations, and much more. To verify the strength and accuracy of these patterns, they show you how to use exploration with data mining techniques to assure business value. With this book, you'll gain a better understanding of: - The process of exploring data - The infrastructure of exploration - The roles that analysts play in your organization - How to form a basis of data that can be used for analysis - How patterns in data can be turned into business opportunity - When patterns should not be turned into business opportunity - The role of data mining