Data Modeling Best Practices Article by Dale Anderson

Data Modeling Best Practices 

 I found a very good article written by May 5, 2017 -- Dale Anderson, on Best Practices of Data Modeling. We can see complete article using below links :

https://www.talend.com/blog/2017/05/05/data-model-design-best-practices-part-1/#comment-1439

I have copied few of highlights below.

• Adaptability – creating schemas that withstand enhancement or correction
• Expandability – creating schemas that grow beyond expectations
• Fundamentality – creating schemas that deliver on features and functionality
• Portability – creating schemas that can be hosted on disparate systems
• Exploitation – creating schemas that maximize a host technology
• Efficient Storage – creating optimized schema disk footprint
• High Performance – creating optimized schemas that excel

Things to be avoid while designing Data model:

• χ Composite Primary Keys avoid them, rarely effective or appropriate; there are some exceptions depending upon the data model
• χ Bad Primary Keys usually datetime and/or strings (except a GUID or Hash) are inappropriate
• χ Bad Indexing either too few or too many
• χ Column Datatypes when you only need an Integer don’t use a Long (or Big Integer), especially on a primary key
• χ Storage Allocation inconsiderate of data size and growth potential
• χ Circular References where a table A has a relationship with table B, table B has a relationship with table C, and table C has a relationship with table A – this is simply bad design (IMHO)