Steve Hoberman
Born
New York City
Occupation(s)Data Modeler, writer
Years active1992 - present[1]
Notable workData Modeling Master Class[2]

Steve Hoberman is an American data modeler, writer and data modeling instructor.[3][4][5][6] He is a lecturer at Columbia University in the Applied Analytics graduate program.[7] He is the recipient of the 2012 Data Administration Management Association (DAMA) International Professional Achievement Award.[8]

Early life

Steve Hoberman was born and educated in Queens, New York.[7] He graduated from Queens College in 1990 with a major in computer science and minors in business and math.

Career

He joined Bell Communications Research (Bellcore) in 1990. Bellcore sponsored his Master of Science in Information Networking degree at Carnegie Mellon University, where he graduated in 1991. While at Bellcore, he worked as an analyst and data modeler on a team tasked with building an enterprise data model for the telecommunications industry. This project provided exposure to various disciplines of the 1990s, including enterprise data modeling, object-oriented modeling techniques, Computer Aided Software Engineering (CASE), and metadata repositories.

In 1994, he began working on Wall Street, where he performed data modeling work for critical financial applications. In 1997, Hoberman joined Mars, Inc. as their Data Warehouse Architect. During his nine-year tenure at Mars, he held various roles, including Lead Data Modeler, Developer Team Lead, and SAP Functional Analyst.[5]

Hoberman's first book was published in 2001. He authored "Data Modeling Made Simple." Since then, he has written or coauthored over 15 books on data modeling and published more than 150 books on data.

Some of Hoberman's innovations used by organizations worldwide include:

Importance of precision
Hoberman's definition of a data model is a "precise representation of an information landscape." Precision means the model can be read only one way, making it an essential diagram for application development.[9]
Data model settings
Hoberman teaches that five settings can categorize all data models. It is important to decide the Scope, Focus, Filter, Timer, and Mode before starting to build any data model.[10]
Data Model Scorecard
Hoberman's assessment approach for reviewing a data model includes analyzing a data model across ten categories: Correctness, Completeness, Scheme, Structure, Abstraction, Standards, Readability, Definitions, Consistency, and Data.[11]
Normalization approach
Hoberman has a unique approach to normalizing a model up to Fifth Normal Form (5NF). It is a "hiking up a mountain" analogy that he has used for over 25 years.[12]
Abstraction Safety Guide
Hoberman's three-question approach focusing on Commonality, Value, and Effort helps data modelers decide where to abstract.[13]
Business Terms Model
He redefined the Conceptual Data Model (CDM) into a Business Terms Model (BTM) to make it more useful and applicable to a business audience, including data governance.[14]
Align > Refine > Design
He redefined the Conceptual, Logical, and Physical modeling approach into an Align, Refine, and Design approach. The Align > Refine > Design approach encompasses a broader database technology than relational, allowing NoSQL solutions to follow good design principles.[15]
Definition assessment
His "3 c's" assessment of definitions (Correctness, Completeness, and Clarity) improves entity and attribute definitions across all types of data models.[16]

Bibliography

  • Author of "Data Modeling Made Simple"[17][18]
  • Author of "The Rosedata Stone: Achieving a Common Business Language using the Business Terms Model"[14]
  • Author of "Data Model Scorecard: Applying the Industry Standard on Data Model Quality"[19]
  • Author of "Blockchainopoly: How Blockchain Changes the Rules of the Game"[20]
  • Author of "Data Modeler's Workbench"[21]
  • Author of "Data Modeling Made Simple with ER/Studio Data Architect"[22]
  • Coauthor of "Data Modeling for the Business"[23]
  • Coauthor of "Data Modeling Made Simple with PowerDesigner"[24]
  • Coauthor of "Data Modeling Made Simple with erwin DM"[25]
  • Coauthor of "MongoDB Data Modeling and Schema Design"[15]
  • Coauthor of "Neo4j Data Modeling"[26]
  • Coauthor of "Elasticsearch Data Modeling and Schema Design"[27]
  • Coauthor of "TerminusDB Data Modeling and Schema Design"[28]
  • Contributor to "Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World, 3rd Edition"[29]

References

  1. ↑ Hoberman, Steve (July 5, 2023). "Steve Hoberman – TDAN.com".
  2. ↑ Hoberman, Steve (July 2015). Data Modeling Master Class Training Manual: Steve Hoberman's Best Practices Approach to Developing a Competency in Data Modeling. Technics Publications, LLC. ISBN 9781634620901.
  3. ↑ "Steve Hoberman".
  4. ↑ "Mastering MongoDB: Data modeling, schema design and the future of AI". 24 June 2023.
  5. 1 2 "ELearningCurve - Steve Hoberman".
  6. ↑ "Steve Hoberman".
  7. 1 2 "Steve Hoberman | Columbia University School of Professional Studies".
  8. ↑ "Award History".
  9. ↑ Hoberman, Steve (29 December 2015). Data Modeling Made Simple: A Practical Guide for Business and IT Professionals. Technics Publications. ISBN 9781634620161.
  10. ↑ "Data Model Scorecard – Technics Publications".
  11. ↑ "The Data Model Scorecard Category 4 of 10". November 2014.
  12. ↑ Data Modeling Made Simple. Technics Publication. August 18, 2009. ISBN 978-0977140060.
  13. ↑ Hoberman, Steve (5 March 2020). The Rosedata Stone: Achieving a Common Business Language using the Business Terms Model. Technics Publications. ISBN 9781634627757.
  14. 1 2 "The Rosedata Stone – Technics Publications".
  15. 1 2 "The Align > Refine > Design Series – Technics Publications".
  16. ↑ Data Model Scorecard: Applying the Industry Standard on Data Model Quality. Technics Publication. 2015. ISBN 9781634620826.
  17. ↑ "Data Modeling Made Simple – Technics Publications".
  18. ↑ Hoberman, Steve (2009). Data Modeling Made Simple: A Practical Guide for Business and IT Professionals. Technics Publications. ISBN 9780977140060.
  19. ↑ "Data Model Scorecard – Technics Publications".
  20. ↑ "Blockchainopoly – Technics Publications".
  21. ↑ https://www.wiley.com/en-us/Data+Modeler' s+Workbench:+Tools+and+Techniques+for+Analysis+and+Design-p-9780471233398
  22. ↑ "Data Modeling Made Simple with ER/Studio Data Architect – Technics Publications".
  23. ↑ "Data Modeling for the Business – Technics Publications".
  24. ↑ "Data Modeling Made Simple with PowerDesigner – Technics Publications".
  25. ↑ "Data Modeling Made Simple with erwin DM – Technics Publications".
  26. ↑ "The Align > Refine > Design Series – Technics Publications".
  27. ↑ "The Align > Refine > Design Series – Technics Publications".
  28. ↑ "TerminusDB Data Modeling and Schema Design – Technics Publications".
  29. ↑ "Data and Reality – Technics Publications".
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