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Modelling Business Information - Entity relationship and class modelling for Business Analysts

Book Description

It is almost universally accepted that requirements documents for new or enhanced IT systems by business analysts should include a ‘data model’ to represent the information that has to be handled by the system. Starting from first principles, this book will help business analysts to develop the skills required to construct data models through comprehensive coverage of entity relationship and class modelling, in line with the BCS Data Analysis syllabus. In addition to covering the topics in the syllabus, the book also includes extra information of interest including data model quality and taking a requirement model into database design. -- 'Anyone interested in a thoughtful, well-done text on how to do high-quality business analytical data modelling should definitely proceed with this book.’ David Hay, Essential Strategies International, CEO --- '“Modelling Business Information” provides an introduction to data modeling, to the nomenclature used by common modeling techniques, and to techniques for representing common patterns. This is a useful book for business analysts who are creating the information model as well as for business and IT users who need to understand a data model.' Keith W. Hare, JCC Consulting, Inc., Senior Consultant ---- 'Keith Gordon’s wonderfully compact yet thorough introduction to business-friendly information modelling is a terrific contribution to the field. Globally, there’s a surge of interest in data modelling as a powerful tool for improving communication, especially with professionals who used to think business-oriented entity-relationship modelling didn't need to be in their tool kits. Business analysts, Agile developers, data scientists, big data specialists, and other professionals will all benefit from Keith’s work.' Alec Sharp , Senior Consultant, Clariteq --- 'As the roles of Data and Business Analysts become more intertwined, this book is timely in its publication. Businesses often fail to recognise information is a key resource and are confused by how it is presented or overwhelmed its complexity during use. Keith brings to the forefront of the readers mind the importance of communicating and analysing the relationship between Business, Information, Systems and Data, and the value in developing models cooperatively, gaining "consensus, not perfection“ from stakeholders. Simple everyday examples and analogies to support the readers understanding and make the subject more relatable are used. I enjoyed reading the book and completing the exercises. An excellent learning aid for Analysts who are new to modelling or need reminding of good practice.' Katie Walsh , Business Analyst and Mentor

Table of Contents

  1. Front Cover
  2. Half Title
  3. BCS, THE CHARTERED INSTITUTE FOR IT
  4. Title Page
  5. Copyright Page
  6. Contents
  7. List of figures and tables
  8. About the Author
  9. Foreword
  10. Acknowledgements
  11. Glossary
  12. Introduction
  13. PART 1 THE BASICS
  14. 1. WHY BUSINESS ANALYSTS SHOULD MODEL INFORMATION
  15. What is business analysis?
  16. Information and data
  17. The importance for a business analyst of understanding information needs
  18. The role of models in business analysis
  19. Data models and data
  20. Entity relationship modelling
  21. Class modelling
  22. Use of data models in business analysis
  23. What makes a good data model?
  24. Introducing data analysis
  25. 2. MODELLING THE THINGS OF INTEREST TO THE BUSINESS AND THE RELATIONSHIPS BETWEEN THEM
  26. Entities and objects
  27. Naming of entity types and object classes
  28. Introduction to relationships and associations
  29. Relationship notation in entity relationship models
  30. Association notation in UML class models
  31. Degrees of cardinality and optionality
  32. Multiple relationships and associations
  33. Recursive relationships and reflexive associations
  34. Exercises for Chapter 2
  35. 3. MODELLING MORE COMPLEX RELATIONSHIPS
  36. The problems with many-to-many relationships and associations
  37. Resolving entity relationship model many-to-many relationships
  38. Resolving class model many-to-many associations
  39. The ‘bill of materials’ structure
  40. Mutually exclusive relationships and associations
  41. Generalisation and specialisation in entity relationship models
  42. Generalisation and specialisation in class models
  43. Aggregation and composition
  44. Exercises for Chapter 3
  45. 4. DRAWING AND VALIDATING INFORMATION MODEL DIAGRAMS
  46. The model drawing process
  47. Identifying the entity types or the object classes
  48. Identifying the relationships or associations
  49. Drawing the initial diagram
  50. Validating the diagram
  51. Exercises for Chapter 4
  52. 5. RECORDING INFORMATION ABOUT THINGS
  53. Revisiting entity types, object classes, relationships and associations
  54. Introduction to attributes
  55. The naming of attributes
  56. Entity type, object class or attribute?
  57. Unique identifiers
  58. Domains
  59. The UML extended attribute notation
  60. Showing operations on class models
  61. Exercises for Chapter 5
  62. 6. RATIONALISING DATA USING NORMALISATION
  63. What is normalisation?
  64. The relational model of data
  65. The rules of normalisation
  66. Starting the normalisation process
  67. First normal form
  68. Second normal form
  69. Third normal form
  70. The third normal form data model
  71. Candidate keys, primary keys and alternate keys
  72. The relationship of normalisation to modelling
  73. Exercises for Chapter 6
  74. PART 2 SUPPLEMENTARY MATERIAL
  75. 7. OTHER MODELLING NOTATIONS
  76. The IDEF1X notation
  77. The Information Engineering notation
  78. The Chen notation
  79. Comparison of the notations
  80. 8. THE NAMING OF ARTEFACTS ON INFORMATION MODELS
  81. The naming of entity types or object classes
  82. The naming of domains
  83. The naming of attributes
  84. The naming of relationships in Ellis-Barker entity relationship models
  85. The naming of associations on UML class models
  86. 9. INFORMATION MODEL QUALITY
  87. Genericity and specificity in models
  88. The nine characteristics of a good data model
  89. The six principles of high quality data models
  90. The five dimensions of data model quality
  91. The layout of models
  92. 10. CORPORATE INFORMATION AND DATA MODELS
  93. The problems
  94. Principles for the development of a corporate model
  95. 11. DATA AND DATABASES
  96. The data landscape
  97. Databases
  98. 12. BUSINESS INTELLIGENCE
  99. The data warehouse
  100. The multidimensional model of data
  101. Dimensional modelling
  102. 13. ADVANCES IN SQL (OR WHY BUSINESS ANALYSTS SHOULD NOT BE IN THE WEEDS)
  103. The basics of SQL
  104. New SQL data types
  105. The future
  106. Implications for business analysts and information modellers
  107. 14. TAKING A REQUIREMENTS INFORMATION MODEL INTO DATABASE DESIGN
  108. First-cut database design stage
  109. Optimised database design stage
  110. APPENDICES
  111. Appendix A: Table of equivalences
  112. Appendix B: Bibliography
  113. Appendix C: Solutions to the exercises
  114. Index
  115. Back Cover