| Acknowledgements |
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17 | (2) |
| Foreword |
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19 | (2) |
| Read me first! |
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21 | (4) |
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SECTION I: Data Modeling Introduction |
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25 | (30) |
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27 | (10) |
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28 | (1) |
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29 | (1) |
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30 | (1) |
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31 | (4) |
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35 | (2) |
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Why do we need a data model? |
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37 | (8) |
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37 | (2) |
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Communicating during the modeling process |
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38 | (1) |
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Communicating after the modeling process |
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39 | (1) |
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39 | (2) |
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41 | (2) |
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Converting the Non-Believer |
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43 | (2) |
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What camera settings also apply to a data model? |
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45 | (10) |
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The Data Model and the Camera |
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45 | (2) |
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47 | (1) |
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48 | (1) |
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49 | (1) |
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50 | (1) |
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51 | (1) |
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Choosing the Right Setting |
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52 | (3) |
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SECTION II: Data Model Components |
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55 | (38) |
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57 | (6) |
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57 | (2) |
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59 | (2) |
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61 | (2) |
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63 | (6) |
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63 | (1) |
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63 | (1) |
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64 | (3) |
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67 | (2) |
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69 | (12) |
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69 | (1) |
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69 | (2) |
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71 | (4) |
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75 | (2) |
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77 | (2) |
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79 | (2) |
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81 | (12) |
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81 | (1) |
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81 | (4) |
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Primary and Alternate Keys Explained |
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85 | (2) |
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87 | (3) |
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90 | (1) |
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91 | (2) |
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SECTION III: Subject Area, Logical, and Physical Data Models |
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93 | (120) |
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What are subject area models? |
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97 | (26) |
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98 | (1) |
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Subject Area Model Explained |
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99 | (5) |
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Types of Subject Area Models |
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104 | (13) |
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Business Subject Area Model (BSAM) |
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105 | (4) |
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Application Subject Area Model (ASAM) |
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109 | (4) |
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Comparison Subject Area Model (CSAM) |
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113 | (4) |
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How to Build a Subject Area Model |
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117 | (4) |
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121 | (2) |
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What are logical data models? |
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123 | (54) |
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Logical Data Model Explained |
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124 | (1) |
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Comparison of Relational with Dimensional Logical Models |
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125 | (7) |
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132 | (35) |
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136 | (8) |
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144 | (13) |
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157 | (7) |
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164 | (3) |
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167 | (5) |
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172 | (2) |
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Modifying a Logical Data Model |
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174 | (3) |
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What are physical data models? |
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177 | (36) |
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Physical Data Model Explained |
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178 | (1) |
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Denormalization Explained |
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179 | (19) |
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182 | (6) |
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188 | (4) |
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192 | (2) |
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194 | (2) |
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196 | (1) |
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197 | (1) |
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198 | (3) |
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201 | (1) |
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202 | (4) |
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204 | (2) |
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When Reference Data Values Change |
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206 | (3) |
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Getting Physical with Subtypes |
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209 | (4) |
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SECTION IV: Data Model Quality |
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213 | (62) |
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Which templates help capture requirements? |
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215 | (16) |
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215 | (3) |
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218 | (3) |
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221 | (5) |
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226 | (3) |
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229 | (2) |
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What is the Data Model Scorecard®? |
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231 | (26) |
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Data Model Scorecard® Explained |
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231 | (5) |
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How well do the characteristics of the model support the type of model? |
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236 | (2) |
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How well does the model capture the requirements? |
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238 | (1) |
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How complete is the model? |
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239 | (1) |
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How structurally sound is the model? |
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240 | (3) |
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How well does the model leverage generic structures? |
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243 | (2) |
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How well does the model follow naming standards? |
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245 | (1) |
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How well has the model been arranged for readability? |
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246 | (3) |
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How good are the definitions? |
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249 | (3) |
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How consistent is the model with the enterprise? |
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252 | (1) |
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How well does the metadata match the data? |
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253 | (1) |
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Determining the Most Challenging Category |
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254 | (3) |
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How can we work effectively with others? |
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257 | (18) |
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Recognizing People Issues |
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257 | (2) |
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259 | (6) |
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259 | (2) |
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Identifying the stakeholders |
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261 | (2) |
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263 | (1) |
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264 | (1) |
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265 | (4) |
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265 | (3) |
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Dealing with problems - and problem people |
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268 | (1) |
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269 | (3) |
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271 | (1) |
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271 | (1) |
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272 | (1) |
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272 | (3) |
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SECTION V: Essential Topics Beyond Data Modeling |
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275 | (48) |
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What is unstructured data? |
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277 | (18) |
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Unstructured Data Explained |
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277 | (2) |
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Data Modeling and Abstraction |
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279 | (2) |
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Immutable Unstructured Data |
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281 | (1) |
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282 | (11) |
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284 | (3) |
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Capturing taxonomy properties |
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287 | (3) |
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Maintaining taxonomies over time |
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290 | (2) |
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292 | (1) |
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293 | (1) |
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293 | (2) |
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295 | (18) |
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295 | (3) |
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298 | (1) |
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299 | (1) |
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300 | (7) |
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303 | (1) |
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304 | (2) |
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306 | (1) |
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307 | (4) |
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307 | (1) |
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307 | (4) |
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311 | (2) |
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What are the Top Five modeling questions? |
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313 | (10) |
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313 | (1) |
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How do you quantify the value of the logical data model? |
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314 | (1) |
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315 | (5) |
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320 | (1) |
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How do I keep my modeling skills sharp? |
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321 | (2) |
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323 | (4) |
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323 | (1) |
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324 | (3) |
| Appendix: Answers to Exercises |
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327 | (10) |
| Glossary |
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337 | (20) |
| Index |
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357 | |
