[Review] Data Modeling Made Simple (Steve Hoberman) Summarized.

[Review] Data Modeling Made Simple (Steve Hoberman) Summarized.
9Natree
[Review] Data Modeling Made Simple (Steve Hoberman) Summarized.

Oct 28 2026 | 00:09:45

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Episode • October 28, 2026 • 00:09:45

Show Notes

Data Modeling Made Simple (Steve Hoberman)

- Amazon USA Store: https://www.amazon.com/dp/B019PMZUR6?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Modeling-Made-Simple-Steve-Hoberman.html

- Apple Books: https://books.apple.com/us/audiobook/the-case-for-network-marketing-one-of-the/id985770091?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree

- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Modeling+Made+Simple+Steve+Hoberman+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/B019PMZUR6/

#Businessinformationwayfinding #Entitiesattributesrelationshipsandkeys #Conceptuallogicalandphysicalmodels #Normalizationanddimensionalmodeling #DataModelScorecard #DataModelingMadeSimple

Data Modeling Made Simple: A Practical Guide for Business and IT Professionals, 2nd Edition is a practical instructional guide by data-modeling specialist Steve Hoberman. It explains how data models help people describe, organize, communicate, and validate the information used by a business or application. Rather than treating modeling as a narrowly technical database activity, the book addresses the shared work of business users, analysts, architects, designers, and developers. Its progression moves from accessible everyday examples toward more formal modeling concepts, including entities, attributes, relationships, keys, abstraction, and normalization. It then distinguishes among conceptual or subject-area, logical, and physical models, emphasizing that each serves a different purpose and audience. Exercises and end-of-chapter key-point summaries make the book structured as a learning text as well as a reference. A defining feature is Hoberman’s Data Model Scorecard, a framework for reviewing model quality. The book therefore combines modeling notation and design decisions with communication, requirements gathering, and practical quality control.

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