Impossible Data Warehouse Situations: Solutions from the Experts
Authors: Sid Adelman, Joyce Bischoff
Venue:  (2002)

From the Book:In the seminars, presentations and classes we teach on data warehouse, we are often subjected to what appear to be “Impossible Situations.” Likewise, on the DMReview “Ask the Experts” forum (reference www.dmreview.com) we are confronted with questions that, at first glance, appear to have no answers or solutions. They do have solutions and that’s what this book is all about.The 91 Impossible Situations in this book were taken from our classes, from the DMReview “Ask the Expert” forum, from data warehouse consultants and colleagues in the field who have experienced these situations. These are all real situations but they have been disguised and sanitized to protect the authors as well as to protect the organizations experiencing the situations from the attendant shame and humiliation. As a side note, as the situations were disseminated, reviewers were quick to say, “I know what company this describes,” and they were almost always wrong. Purpose of This BookThere is no reason that each organization, as it begins and continues to develop data warehouse projects, must wrestle with many of the very difficult situations that have confounded other organizations. The same impossible situations continue to raise their ugly heads, often with surprisingly little relation to the industry, the size of the organization, or the makeup of the organizational structure. This book is, first of all, to let you know you are not alone and your problems are not unique. The book should give hope to the perplexed who see no obvious solution to their problems. Some of the situations should resonate with those of you planningto enhance your data warehouse, to add new data, additional users, and new applications. It may be that the impossible situation has not yet emerged, but you definitely see it just around the bend. This means that you should be able to avoid the situation rather than having it develop and then needing to fix it.Who Should Read This BookEvery stakeholder, data warehouse architect, data warehouse project manager, and user liaison responsible for any portion of the data warehouse will be faced with the challenges identified in these pages. These people are looking for solutions to situations that, at first, appear to have no answer and appear to be impossible. This is not an introduction to data warehouse. Readers should have some level of familiarity with data warehouse either through practical experience, conferences, or previous reading of data warehouse texts. This book is also not geared to any primary topic such as meta data or data quality but covers a broad range of areas. The reference section has both introductory as well as more advanced suggested reading material. User liaisons and managers may only be interested in and want to read Section I, Impossible Managerial Situations. How This Book is OrganizedThe first part of the book deals with managerial situations and the second part with technical situations. The order within these sections is very roughly the order in which projects are developed and situations are encountered but the sections are not dependent on each other. The book can be read from front to back but more likely, the readers will be drawn to the sections that cause them the most pain. For example, if the reader is struggling with data quality issues, Section 11, Data Quality, would be the place to start. The order of the answers is alphabetical by the experts’ last name.A technical glossary at the back of the book should clarify some terms and will also keep the reader from going down the wrong path. Terminology misunderstanding in this fast-changing field has caused significant misinterpretation that has resulted in wasted time and money, dissension and hurt feelings. The glossary contains acronyms and data warehouse and IT terminology. There will be a few cases with more than one definition. Please refer to the definitions to avoid any misunderstandings on your part. Those whose native language is not English will find the Colloquial Glossary useful since the experts were fond of using colloquial expressions. The reader will notice strong biases in the experts’ responses. The experts came to these dearly held opinions honestly through extensive experience in real world situations. The reader will also quickly realize that some of the answers are in sharp disagreement and appear to be contradictory while a few are embarrassingly similar. The editor made no attempt to reconcile the differences. Recognizing that there is usually more than one answer, very much depending on the organization and the situation, the different approaches have been maintained. Any reconciliation or choice of approach is left to the reader who, we assume, is astute enough to find the relevant answer and pick the solution that will work in his or her organization. The ExpertsSid AdelmanJoyce BischoffJill DycheDouglas HackneySean IvoghliChuck KelleyDavid MarcoLarissa MossClay RehmThe experts represented in this book are all real experts in data warehouse. They have been working in the data warehouse arena for a cumulative 130 (+12) years. If anyone can address these impossible situations, they can. The experts have suggested best practices based on their experiences with both successful and unsuccessful implementations. The experts correctly identified many of the situations as reflecting the symptoms of a dysfunctional organization, knowing that without understanding the real causes, no effective solution could be honestly recommended. The experts resorted to making assumptions about the situations when not enough information was provided. The experts’ bios are in the Appendix.Follow-onThere were a number of impossible situations that came in after the original batch of 91 were sent to the experts and we all feel sure more will appear. If you have a situation you would like to contribute, please send it to impossibles@sidadelman.com. If there is to be a second edition, your situation may be included.