• Computer science
      January 2011

      Building the Agile Database

      How to Build a Successful Application Using Agile Without Sacrificing Data Management

      by Larry Burns

      Hear the author, Larry Burns, talk about his book. Is fast development the enemy of good development? Not necessarily. Agile development requires that databases are designed and built quickly enough to meet fast-based delivery schedules - but in a way that also delivers maximum business value and reuse. How can these requirements both be satisfied? This book, suitable for practitioners at all levels, will explain how to design and build enterprise-quality high-value databases within the constraints of an Agile project. Starting with an overview of the business case for good data management practices, the book defines the various stakeholder groups involved in the software development process, explains the economics of software development (including "time to market" vs. "time to money"), and describes an approach to Agile database development based on the five PRISM principles. This book explains how to work with application developers and other stakeholders, examines critical issues in Agile Development and Data Management, and describes how developers and data professionals can work together to make Agile projects successful while delivering maximum value data to the enterprise. Building the Agile Database will serve as an excellent reference for application developers, data managers, DBAs, project managers, Scrum Masters and IT managers looking to get more value from their development efforts. Larry Burns has worked in IT for more than 25 years as a database administrator, application developer, consultant and teacher.

    • Computer science
      November 2011

      UML and Data Modeling

      A Reconciliation

      by David C. Hay

      Here you will learn how to develop an attractive, easily readable, conceptual, business-oriented entity/relationship model, using a variation on the UML Class Model notation. Hear the author, David Hay, talk about his book. This book has two audiences: Data modelers (both analysts and database designers) who are convinced that UML has nothing to do with them; and UML experts who don’t realize that architectural data modeling really is different from object modeling (and that the differences are important). David Hay’s objective is to finally bring these two groups together in peace. Here all modelers will receive guidance on how to produce a high quality (that is, readable) entity/relationship model to describe the data architecture of an organization. The notation involved happens to be the one for class models in the Unified Modeling Language, even though UML was originally developed to support object-oriented design. Designers have a different view of the world from those who develop business-oriented conceptual data models, which means that to use UML for architectural modeling requires some adjustments. These adjustments are described in this book. David Hay is the author of Enterprise Model Patterns: Describing the World, a comprehensive model of a generic enterprise. The diagrams were at various levels of abstraction, and they were all rendered in the slightly modified version of UML Class Diagrams presented here. This book is a handbook to describe how to build models such as these. By way of background, an appendix provides a history of the two groups, revealing the sources of their different attitudes towards the system development process. If you are an old-school ER modeler and now find yourself having to come up to speed on UML to get that next job (or keep the current one), this is your guidebook to success. If you are a long time object oriented programmer who has to interact with data modelers, this book is for you too. David has done the hard work of mapping out how to do a logical entity relationship model using standard (and accepted) UML diagram components. This book shows you step-by-step, with ample examples, how to get from here to there with the least pain possible for all concerned. Kent Graziano Certified Data Vault Master and Oracle ACE Past-President of ODTUG & RMOUG

    • Data warehousing
      January 2011

      Building the Unstructured Data Warehouse

      Architecture, Analysis & Design

      by Bill Inmon, Krish Krishnan

      Learn essential techniques from data warehouse legend Bill Inmon on how to build the reporting environment your business needs now!Answers for many valuable business questions hide in text. How well can your existing reporting environment extract the necessary text from email, spreadsheets, and documents, and put it in a useful format for analytics and reporting? Transforming the traditional data warehouse into an efficient unstructured data warehouse requires additional skills from the analyst, architect, designer, and developer. This book will prepare you to successfully implement an unstructured data warehouse and, through clear explanations, examples, and case studies, you will learn new techniques and tips to successfully obtain and analyze text.Master these ten objectives:Build an unstructured data warehouse using the 11-step approachIntegrate text and describe it in terms of homogeneity, relevance, medium, volume, and structureOvercome challenges including blather, the Tower of Babel, and lack of natural relationshipsAvoid the Data Junkyard and combat the Spider's WebReuse techniques perfected in the traditional data warehouse and Data Warehouse 2.0,including iterative developmentApply essential techniques for textual Extract, Transform, and Load (ETL) such as phrase recognition, stop word filtering, and synonym replacementDesign the Document Inventory system and link unstructured text to structured dataLeverage indexes for efficient text analysis and taxonomies for useful external categorizationManage large volumes of data using advanced techniques such as backward pointersEvaluate technology choices suitable for unstructured data processing, such as data warehouse appliancesThe following outline briefly describes each chapter's content:Chapter 1 defines unstructured data and explains why text is the main focus of this book.Chapter 2 addresses the challenges one faces when managing unstructured data.Chapter 3 discusses the DW 2.0 architecture, which leads into the role of the unstructured data warehouse. The unstructured data warehouse is defined and benefits are given. There are several features of the conventional data warehouse that can be leveraged for the unstructured data warehouse, including ETL processing, textual integration, and iterative development. Chapter 4 focuses on the heart of the unstructured data warehouse: Textual Extract, Transform, and Load (ETL).Chapter 5 describes the 11 steps required to develop the unstructured data warehouse.Chapter 6 describes how to inventory documents for maximum analysis value, as well as link the unstructured text to structured data for even greater value.Chapter 7 goes through each of the different types of indexes necessary to make text analysis efficient. Indexes range from simple indexes, which are fast to create and are good if the analyst really knows what needs to be analyzed before the indexing process begins, to complex combined indexes, which can be made up of any and all of the other kinds of indexes.Chapter 8 explains taxonomies and how they can be used within the unstructured data warehouse.Chapter 9 explains ways of coping with large amounts of unstructured data. Techniques such as keeping the unstructured data at its source and using backward pointers are discussed. The chapter explains why iterative development is so important.Chapter 10 focuses on challenges and some technology choices that are suitable for unstructured data processing. In addition, the data warehouse appliance is discussed.Chapters 11, 12, and 13 put all of the previously discussed techniques and approaches in context through three case studies. About Bill Bill Inmon, the father of data warehousing, has written 52 books translated into 9 languages. Bill has written over 1000 articles and conducted seminars and spoken at conferences on every continent except Antarctica. Bill holds three software patents and his latest company is Forest Rim Technology, a company dedicated to the access and integration of unstructured data into the structured world. About Krish Krish Krishnan is a recognized thought leader in Data Warehouse Performance and Architecture. Krish writes and teaches Social Intelligence across the world and is a frequent speaker at industry conferences. He provides consulting advice to CxO's on DW Strategy and is an Independent Analyst covering the Data Warehouse and Business Intelligence Industry.

    • Computer science
      July 2012

      The Analytical Puzzle

      by David Haertzen

      Do you enjoy completing puzzles? Perhaps one of the most challenging (yet rewarding) puzzles is delivering a successful data warehouse suitable for data mining and analytics. The Analytical Puzzle describes an unbiased, practical, and comprehensive approach to building a data warehouse which will lead to an increased level of business intelligence within your organization. New technologies continuously impact this approach and therefore this book explains how to leverage big data, cloud computing, data warehouse appliances, data mining, predictive analytics, data visualization and mobile devices. Here are the main objectives for each of the book's 19 chapters: Chapter 1: Develop a foundational knowledge of data warehousing, business intelligence and analytics Chapter 2: Build the business case needed to sell your data warehousing project, and then produce a project plan that avoids common pitfalls Chapter 3: Elicit and organize business intelligence and data warehousing business requirements Chapter 4: Specify the technical architecture of the data warehousing system, including software and infrastructure components, technology stack, and non-functional requirements. Gain an understanding of cloud based data warehousing and data warehouse appliances Chapter 5: Learn about data attributes including metrics and key performance indicators (KPIs), the raw material of data warehousing and business intelligence Chapter 6: Learn about data modeling and how to apply design patterns for each part of the data warehouse Chapter 7: Speak the dimensional modeling language of measures, dimensions, facts, cubes, stars, and snowflakes Chapter 8: Organize a successful data governance program. Learn how to manage metadata for your data warehousing and business intelligence project Chapter 9: Identify useful data sources and implement a data quality program Chapter 10: Use database technology for your data warehousing project, and understand the impact of data warehouse appliances, big data, in memory databases, columnar databases and OnLine Analytical Processing (OLAP) Chapter 11: Apply data integration and understand the role data mapping, data cleansing, data transformation, and loading data play in a successful data warehouse Chapter 12: Use the business intelligence (BI) operations of slice, dice, drill down, roll up, and pivot to analyze and present data Chapter 13: Learn about descriptive and predictive statistics, and calculate mean, median, mode, variance and standard deviation Chapter 14: Harness analytical methods such as regression analysis, data mining, and statistics to make profitable decisions and anticipate the future Chapter 15: Appreciate the components and design patterns that compose a successful analytic application Chapter 16: Gain an understanding of the uses and benefits of scorecards and dashboards including support of mobile device users Chapter 17: Gain insight into applications of business intelligence that could profit your organization, including risk management, finance, marketing, government, healthcare, science and sports Chapter 18: Perform customer analytics to better understand and segment your customers Chapter 19: Test, roll out, and sustain the data warehouse David Haertzen is a seasoned data warehouse architect who has helped a diverse set of organizations from start-ups to multinationals to utilize data for their advantage. David teaches data modeling, data warehousing, data architecture, business intelligence and is also active as editor of the Infogoal.com Data Management Center. David is a graduate of the University of Minnesota and holds an MBA from the University of St. Thomas.

    • Computer science
      August 2012

      UML Requirements Modeling For Business Analysts

      by Norman Daoust

      Hear the author, Norman Daoust, talk about his book. This book provides you with a collection of best practices, guidelines, and tips for using the Unified Modeling Language (UML) for business analysis. The contents have been assembled over the years based on experience and documented best practices. Over sixty easy to understand UML diagram examples will help you to apply these ideas immediately. If you use, expect to use, or think you should use the Unified Modeling Language (UML) or use cases in your business analysis activities, this book will help you: communicate more succinctly and effectively with your stakeholders including your software development team, increase the likelihood that your requirements will be reviewed and understood, reduce requirements analysis, documentation, and review time. The first three chapters explain the reasons for utilizing the UML for business analysis, present a brief history of the UML and its diagram categories, and describe a set of general modeling guidelines and tips applicable to all of the UML diagram types. Each of the next thirteen chapters is dedicated to a different UML diagram type: Use Case Diagrams Activity Diagrams Interaction Overview Diagrams Class Diagrams Object Diagrams State Machine Diagrams Timing Diagrams Sequence Diagrams Communication Diagrams Composite Structure Diagrams Component Diagrams Deployment Diagrams Package Diagrams The next two chapters explain additional diagram types that are important for business analysts and that can be created using UML notation: Context Diagrams using Communication diagram notation Data Models using Class diagram notation These chapters are followed by a chapter that describes criteria for selecting the various diagram types. The final chapter presents a case study. Norman Daoust is a business analyst trainer, requirements modeler, data modeler, healthcare electronic data exchange specialist, fretted instrument specialist, and organic gardener. He is the principal consultant for Daoust Associates, a company based in Cambridge, Massachusetts, United States. He specializes in business analyst training, information modeling, and healthcare systems data integration.

    • Computer science
      October 2013

      UML Database Modeling Workbook

      by Michael Blaha

      Hear the author, Mike Blaha, talk about his book. With our appetites for data on the rise, it has become more important than ever to use UML (Unified Modeling Language) to capture and precisely represent all of these data requirements. Learn how to construct UML data models by working through a series of exercises and self-assessment tests. Beginners can learn the UML directly. Experienced modelers can leverage their understanding of existing database notations, as the book extensively compares the UML to traditional data modeling (Information Engineering). Discover a new way of representing data requirements and communicating better with your business customers. Understand what UML constructs mean and how to properly use them. Learn subtleties of the UML. Become a power UML developer. Practice constructing data models with the exercises. The back of the book answers every exercise. Assess your mastery of the material. Each part has a multiple-choice test that can quantify your understanding. Improve your ability to abstract - think about different ways of representation - as you construct data models. Measure the quality of your data models. Be able to create database designs (DDL code) starting from a UML data model. Be able to write SQL database queries using a data model as a blueprint. Know the differences among operational models, data warehouse models, enterprise models, and master models. They are all aspects of data modeling. This book is concise and to the point. You will learn by induction through reading, practice, and feedback. Since 1994 Michael Blaha has been a consultant and trainer in conceiving, architecting, modeling, designing, and tuning databases. He has worked with dozens of organizations around the world. Blaha has authored seven U.S. patents, six books, and numerous articles. He received his doctorate from Washington University in St. Louis and is an alumnus of GE Global Research in Schenectady, New York. He has worked in many problem domains and specializes in financial applications.

    • Computer science
      September 2013

      Extreme Scoping

      by Larissa T. Moss

      Do your business intelligence (BI) projects take too long to deliver? Is the value of the deliverables less than satisfactory? Do these projects propagate poor data management practices? If you screamed "yes" to any of these questions, read this book to master a proven approach to building your enterprise data warehouse and BI initiatives. Extreme Scoping, based on the Business Intelligence Roadmap, will show you how to build analytics applications rapidly yet not sacrifice data management and enterprise architecture. In addition, all of the roles required to deliver all seven steps of this agile methodology are explained along with many real-world examples. From Wayne Eckerson's Foreword I've read many books about data warehousing and business intelligence (BI). This book by Larissa Moss is one of the best. I should not be surprised. Larissa has spent years refining the craft of designing, building, and delivering BI applications. Over the years, she has developed a keen insight about what works and doesn't work in BI. This book brings to light the wealth of that development experience. Best of all, this is not some dry text that laboriously steps readers through a technical methodology. Larissa expresses her ideas in a clear, concise, and persuasive manner. I highlighted so many beautifully written and insightful paragraphs in her manuscript that it became comical. I desperately wanted the final, published book rather than the manuscript so I could dog-ear it to death and place it front-and-center in my office bookshelf! From David Well's Foreword Extreme Scoping is rich with advice and guidance for virtually every aspect of BI projects from planning and requirements to deployment and from back-end data management to front-end information and analytics services. Larissa is both a pragmatist and an independent thinker. Those qualities come through in the style of this book. Extreme Scoping is a well-written book that is easy to absorb. It is not full of surprises. It is filled with a lot of common sense and lessons learned through experience. Larissa Moss is founder and president of Method Focus Inc. She began her IT career over 30 years ago, and since 1988 she has worked primarily in data warehousing and business intelligence. She is a world renown author, lecturer, and speaker on the topics of data warehousing, business intelligence, master data management, project management, methodologies, data governance, and enterprise information management. She co-authored the books Data Warehouse Project Management, Impossible Data Warehouse Situations, Business Intelligence Roadmap, and Data Strategy.

    • Computer science
      October 2013

      Enterprise Architecture Made Simple

      by Håkan Edvinsson, Lottie Aderinne

      Hear one of the authors, Håkan Edvinsson, talk about his book. Learn how to institute and implement enterprise architecture in your organization. You can make a quick start and establish a baseline for your enterprise architecture within ten weeks, then grow and stabilize the architecture over time using the proven Ready, Set, Go Approach. Reading this book will: Give you directions on how to institute and implement enterprise architecture in your organization. You will be able to build close relationships with stakeholders and delivery teams, but you will not need to micromanage the architecture’s operations. Increase your awareness that enterprise architecture is about business, not information technology. Enable you to initiate and facilitate dramatic business development. The architecture of an enterprise must be tolerant of currently unknown business initiatives. Show you how to get a holistic view of the process of implementing enterprise architecture. Make you aware that information is a key business asset and that information architecture is a key part of the enterprise architecture. Allow you to learn from our experiences. This book is based on our 30 years of work in the enterprise architecture field, colleagues in Europe, customer cases, and students. We do not pretend to cover all you need to know about enterprise architecture within these pages. Rather, we give you the information that is most important for effective and successful guidance. Sometimes, less is more.

    • Computer science
      May 2014

      Data Scientist

      by Zacharias Voulgaris, PhD

      As our society transforms into a data-driven one, the role of the Data Scientist is becoming more and more important. If you want to be on the leading edge of what is sure to become a major profession in the not-too-distant future, this book can show you how. Each chapter is filled with practical information that will help you reap the fruits of big data and become a successful Data Scientist: Learn what big data is and how it differs from traditional data through its main characteristics: volume, variety, velocity, and veracity. Explore the different types of Data Scientists and the skillset each one has. Dig into what the role of the Data Scientist requires in terms of the relevant mindset, technical skills, experience, and how the Data Scientist connects with other people. Be a Data Scientist for a day, examining the problems you may encounter and how you tackle them, what programs you use, and how you expand your knowledge and know-how. See how you can become a Data Scientist, based on where you are starting from: a programming, machine learning, or data-related background. Follow step-by-step through the process of landing a Data Scientist job: where you need to look, how you would present yourself to a potential employer, and what it takes to follow a freelancer path. Read the case studies of experienced, senior-level Data Scientists, in an attempt to get a better perspective of what this role is, in practice. At the end of the book, there is a glossary of the most important terms that have been introduced, as well as three appendices - a list of useful sites, some relevant articles on the web, and a list of offline resources for further reading. Dr. Zacharias Voulgaris was born and raised in Greece. Upon completing a 5-year Engineering degree at the Technical University of Crete, he enrolled in the City University of London for a Masters course in Information Systems and Technology. Afterwards, he pursued a PhD in Birkbeck College (University of London), under the joint supervision of Prof. G. Magoulas and Prof. B. Mirkin, in the field of Machine Learning. Upon receiving his doctorate, he was recruited by the Georgia Institute of Technology as a research fellow. Since January 2013 he has been working as a Data Scientist.

    • Computer science
      October 2012

      Secrets of Analytical Leaders

      by Wayne Eckerson

      Imagine spending a day with top analytical leaders and asking any question you want. In this book, Wayne Eckerson illustrates analytical best practices by weaving his perspective with commentary from seven directors of analytics who unveil their secrets of success. With an innovative flair, Eckerson tackles a complex subject with clarity and insight. Each of the book's 20 chapters is a stand-alone essay on an analytical topic, yet collectively they form a concise methodology about how to implement a successful analytics program. Wayne Eckerson has created a unique - and uniquely valuable - book in "The Secrets of Analytical Leaders." He's pulled together the insights of seven leading analytics practitioners, and combined them with his own considerable experience. The result is an interesting dialogue among some really smart and distinguished people. I'm not sure which is more interesting - the format or the content! Thomas H. Davenport Visiting Professor, Harvard Business School Co-Founder and Director of Research International Institute for Analytics Professors are hard at work molding the world's future analytical leaders - but the chasm between theoretical textbook learning and the real world is considerable. Wayne, with his customary clarity and insight, helps professors cross the chasm by delivering frameworks, commentary, and scenarios that are real, interesting, and important. Hugh Watson Professor of MIS and a C. Herman and Mary Virginia Chair of Business Administration Terry College of Business, University of Georgia and Barbara Wixom Associate Professor at the McIntire School of Commerce, University of Virginia Research Affiliate, Sloan School of Management, Massachusetts Institute of Technology From the Foreword by Michael Halbherr, Executive Vice President, Nokia We are living in a time of radical change. From my vantage point as head of Nokia's Location and Commerce business, I see many business and technical trends shaping our future—and all depend on a new commodity: data. In our mapping business, I see the need to evolve from a road-centric tool to something that allows people to truly understand and maneuver the complexities of a modern city. To accomplish this, we need a lot of data and ways to correlate disparate information into what we call "Smart Data." Analytics is core to what we do, and how we deliver value to customers today and in the future. I recently spoke to the Nokia board about our data, and some members questioned how we could monetize this asset. Since a few members are executives in the oil industry, I told them that data is the "oil of the future", and that you monetize this new resource the same way you monetize oil, by spending time and money refining it. In our case, we are refining data about people, locations, social interactions, traffic, musical preferences, and so on to bring maps to life. The analytical leaders profiled in this book demonstrate how to refine data for business gain and innovation. They play a pivotal role by bridging the worlds of business and technology. When supported by the business, they've delivered remarkable solutions that have given their organizations a competitive edge. I highly recommend this book to anyone who wants to monetize the most important resource of our time: data. It's written in language that both a CEO and a CIO can understand, and carries important lessons no matter what side of the business-technology aisle someone sits. Wayne Eckerson has been a thought leader in the business intelligence and analytics field since the early 1990s. He has conducted numerous in-depth research studies and is the author of the best-selling book Performance Dashboards: Measuring, Monitoring, and Managing Your Business. He is a noted keynote speaker and blogger, and he consults and conducts workshops on many topics. Wayne is the founder of BI Leadership Forum, a network of business intelligence (BI) directors who meet regularly to exchange ideas about best practices in BI and educate the larger BI community. Wayne is also director of research at TechTarget where he writes a popular weekly blog called “Wayne's World of BI” that focuses on industry trends and examines best practices in the application of business intelligence. For many years, Wayne served as director of education and research at The Data Warehousing Institute (TDWI) where he oversaw the company's content and training programs and chaired its BI Executive Summit.

    • Computing & IT
      January 2014

      The Audacity to Spy

      How Government, Business, and Hackers Rob Us of Privacy

      by Catherine Nolan and Ashley M. Wilson, JD

      Ever get the feeling you're being watched? The thieves that steal identities are using cutting-edge, high-tech tools that can take one fact from a social media site, another from an online travel survey, a third from a purchase made via the internet and even access highly confidential medical records. Little by little they piece together your buying habits, your religious and school affiliations, the names of your family and pets, your political views, your driving habits, the places you have vacationed, and much, much more. This is not science fiction and this is not the future, this is what is happening to each and every one of us now - today. And although the vast majority of adults say they are concerned about providing personal information online, nearly 1/3 say they have never used a privacy setting on their computer, never inquired about the charities to whom they donate their money, never worried about someone accessing their medical information and never thought twice about giving a financial institution their social security number over the internet. The Audacity to Spy, written by an attorney with an interest in privacy laws and legislation and her grandmother who is an experienced Information Analyst, reveals the ways in which your identity and personal data have been stolen by various sources. Yes, you should be concerned about the NSA and other government agencies having your phone logs and emails; but you should worry more about the insidious data brokers that are collecting information about you every time you log on to your laptop, use your cell phone, access an app, or use your GPS. Companies are collecting a variety of data about you, combining it with location information, and using it to both personalize their own services and to sell to other advertisers for behavioral marketing. Law enforcement agencies are tracking your car and insurance companies are installing devices to monitor your driving. Clerks are making copies of your credit cards. And if that wasn't enough, the FBI has reported that hackers have been discovered embedding malicious software in two million computers, opening a virtual door for criminals to rifle through users's valuable personal and financial information. More than warning you about the ways your data can be stolen, at the end of each chapter are suggestions for limiting the amount of personal data that is available to be seized and divulged. Can you completely cut off the flow of information about yourself? The answer is no, not completely - there is already too much data out there and increasingly sophisticated ways to obtain bits and pieces. But knowing how it is collected, and by whom, gives you the power to control sensitive information and determine how much of your life you wish to expose to those more than willing to exploit it.

    • Computing & IT
      January 2014

      Non-Invasive Data Governance

      The Path of Least Resistance and Greatest Success

      by Robert S. Seiner

      Data-governance programs focus on authority and accountability for the management of data as a valued organizational asset. Data Governance should not be about command-and-control, yet at times could become invasive or threatening to the work, people and culture of an organization. Non-Invasive Data Governance™ focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources. Non-Invasive Data Governance will provide you with a complete set of tools to help you deliver a successful data governance program. Learn how: Steward responsibilities can be identified and recognized, formalized, and engaged according to their existing responsibility rather than being assigned or handed to people as more work. Governance of information can be applied to existing policies, standard operating procedures, practices, and methodologies, rather than being introduced or emphasized as new processes or methods. Governance of information can support all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives. A practical and non-threatening approach can be applied to governing information and promoting stewardship of data as a cross-organization asset. Best practices and key concepts of this non-threatening approach can be communicated effectively to leverage strengths and address opportunities to improve.

    • Computer science
      April 2009

      Data Modeling for the Business

      A Handbook for Aligning the Business With It Using High-level Data Models

      by Steve Hoberman, Donna Burbank, Chris Bradley

      Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach and hands-on exercises to help you practice topics on your own. Hear one of the authors, Steve Hoberman, talk about this book. In this book, we review data modeling basics and explain why the core concepts stored in a high-level data model can have significant business impact on an organization. We explain the technical notation used for a data model and walk through some simple examples of building a high-level data model. We also describe how data models relate to other key initiatives you may have heard of or may be implementing in your organization. This book contains best practices for implementing a high-level data model, along with some easy-to-use templates and guidelines for a step-by-step approach. Each step will be illustrated using many examples based on actual projects we have worked on. Names have been changed to protect the innocent, but the pain points and lessons have been preserved. One example spans an entire chapter and will allow you to practice building a high-level data model from beginning to end, and then compare your results to ours. Building a high-level data model following the ten step approach you’ll read about is a great way to ensure you will retain the new skills you learn in this book. As is the case in many disciplines, using the right tool for the right job is critical to the overall success of your high-level data model implementation. To help you in your tool selection process, there are several chapters dedicated to discussing what to look for in a high-level data modeling tool and a framework for choosing a data modeling tool, in general. This book concludes with a real-world case study that shows how an international energy company successfully used a high-level data model to streamline their information management practices and increase communication throughout the organization—between both businesspeople and IT. One of the most critical systems issues is aligning business with IT and fulfilling business needs using data models. The authors of Data Modeling for the Business do a masterful job at simply and clearly describing the art of using data models to communicate with business representatives and meet business needs. The book provides many valuable tools, analogies, and step-by-step methods for effective data modeling and is an important contribution in bridging the much needed connection between data modeling and realizing business requirements. Len Silverston, author of The Data Model Resource Book series

    • Computer science
      October 2011

      Data Modeling Made Simple with PowerDesigner

      by Steve Hoberman, George McGeachie

      Data Modeling Made Simple with PowerDesigner will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices, and how to apply these principles with PowerDesigner. Hear one of the authors, Steve Hoberman, talk about this book. You'll build many PowerDesigner data models along the way, increasing your skills first with the fundamentals and later with more advanced feature of PowerDesigner. This book combines real-world experience and best practices to help you master the following ten objectives: This book has ten key objectives for you, the reader: You will know when a data model is needed and which PowerDesigner models are the most appropriate for each situation You will be able to read a data model of any size and complexity with the same confidence as reading a book You will know when to apply and how to make use of all the key features of PowerDesigner You will be able to build, step-by-step in PowerDesigner, a pyramid of linked data models, including a conceptual data model, a fully normalized relational data model, a physical data model, and an easily navigable dimensional model You will be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design You will improve data governance and modeling consistency within your organization by leveraging features such as PowerDesigner’s reference models, Glossary, domains, and model comparison and model mapping techniques You will know how to utilize dependencies and traceability links to assess the impact of change You will know how to integrate your PowerDesigner models with externally-managed files, including the import and export of data using Excel and Requirements documents You will know where you can take advantage of the entire PowerDesigner model set, to increase the success rate of corporate-wide initiatives such as business intelligence and enterprise resource planning (ERP) You will understand the key differentiators between PowerDesigner and other data modeling tools you may have used before

    • Computing & IT
      February 2008

      fruITion

      Creating the Ultimate Corporate Strategy for Information Technology

      by Chris Potts

      Ian is a Chief Information Officer (CIO) who is about to go on a journey of change - whether he likes it or not. He will be expected to explore, challenge and radically recast the complex, often hostile relationships that can exist between a business and the people in its Information Technology (IT) department. On the way, Ian, his Chief Executive Officer, Chief Financial Officer and other key stakeholders, experience a transformation in how a business needs to think about the value of its IT people and the work that they do. This results in some truly groundbreaking innovations in the scope and contribution of Ian's role as CIO, the people that work for him and the strategy that he leads. Watch the characters in this extraordinary business novel as they meet the challenge, struggle and grow. Share in Ian's transformation, and join the author in observing key messages as the adventure unfolds. Part entertaining novel and part enlightening textbook - FruITion takes the reader through a discovery process revealing indispensable messages about the next generation of strategies for Information Technology. - Jeremy Hall, Managing Director, IRM UK Strategic IT Training FruITion brings vividly to life the issues of being a CIO in today's corporate world and how IT, when properly integrated into the objectives of a business can drive massive value creation. His insights into how to win the engagement war and bring technology strategies alive for the non technical are absolutely spot on. - Steve Adams, COO and Managing Director for Card Services, Euronet Worldwide The modern CIO is to be seen as part of the business rather than a service provider to the business. Chris Potts is at the forefront of thinking that will put us all there if we act on his inspiration. - David Brown, CIO of Scottish WaterMore from the author, Chris PottsThe debate over the CIO role, and about the extent to which it should be about business or technology, is taking place in an increasing vacuum of strategic context. Some CIOs have abandoned strategy altogether, while others persevere with a traditional IT Strategy founded in the mindset of the mainframe era. Meanwhile, business managers and staff continue to develop their knowledge of technology and understanding of how to exploit it. There seems to be a presumption that the next-generation strategic purpose of the CIO will be an incremental step on from what has gone before - significant, maybe, but still incremental. What if the CIO's new strategic context is not incremental but disruptive, requiring a very different mindset and skillset? And, most crucially, what if the corporate strategists - rather than the CIO community - are the ones deciding what context is? Their offer to the CIO: you can become one of the corporate strategists like us, but not with your traditional scope and approach to strategy. What does that offer look like and what does it mean for incumbent CIOs and the people who work for them? Chris Potts works with executives and CIOs in industry-leading companies around the world, formulating and executing the new generation of corporate strategies for exploiting IT. He delivers public seminars that are founded on his own breakthrough work with clients, and has provided training to some of the worlds leading consultancies.

    • Databases
      October 2009

      Data Modeling Made Simple

      A Practical Guide for Business and It Professionals

      by Steve Hoberman

      Hear the author, Steve Hoberman, talk about his book. Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives: Know when a data model is needed and which type of data model is most effective for each situation Read a data model of any size and complexity with the same confidence as reading a book Build a fully normalized relational data model, as well as an easily navigatable dimensional model Apply techniques to turn a logical data model into an efficient physical design Leverage several templates to make requirements gathering more efficient and accurate Explain all ten categories of the Data Model Scorecard Learn strategies to improve your working relationships with others Appreciate the impact unstructured data has, and will have, on our data modeling deliverables Learn basic UML concepts Put data modeling in context with XML, metadata, and agile development

    • Sociology
      October 2007

      The Digital Condition

      Class and Culture in the Information Network

      by Rob Wilkie

    • Mind, Body, Spirit

      For Pet's Sake Do Something! Book Three

      How to Heal Your Pets Using Alternative & Complementary Therapies

      by Dr. Monica Diedrich

      What can I do to make my pet more comfortable if he has to cope with pain, illness, or a chronic condition? How can I improve my pet s overall health? How can I tell ahead of time if something I want to try may, or may not, work? In book three of the series, animal communicator Dr Monica Diedrich provides you with clear information about a variety of effective healing modalities you can easily use at home. Dr Monica shows you how to use: Flower Essences to restore spiritual balance and promote physical healing; Essential Oils to quickly and effectively transport oxygen and nutrients into every cell of the body; Homeopathy for healing based on the principle that "like heals like"; Magnetic Therapy, Massage, and Reflexology for relaxation, relieving pain, reducing anxiety, and promoting overall well-being; Sound, in its different healing forms, to serve as a bridge between body, mind, and spirit; Colour to influence how a pet feels and behaves; Crystals as a means for focusing healing energy; Incense fragrances to heal emotional and behavioural imbalances; Animal Communication and how important it is to heal at every level -- spiritual, mental and emotional Acupuncture and Acupressure to eliminate blockages in the body's energy system; Chiropractic to correct misalignments in a pet's body; Hydrotherapy to promote healing in a weightless environment. You will also learn about how to pre-test remedies, how pets age, what to have in a first aid kit, first aid for emergencies, poison-proofing your home, and how to provide for your pet if you are no longer there.

    • Civil engineering, surveying & building

      Practical Stress Analysis With Finite Elements (2nd Edition)

      by

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