“A data model is a collection of concepts ... used to describe the structure of a database...data types, relationships and constraints...is basically a conceptualization between attributes and entities ...
The building blocks in the data model are as follows:

• Entity − An entity represents a particular type of object in the real world.
• Entity set − Sets of entities of the same type which share the same properties are called entity Sets.
• Attribute − An attribute is a characteristic of an entity.
• Constraints − A constraint is a restriction placed on the data. It is helpful to ensure data integrity.
• Relationship − A relationship describes an association among entities.

--TutorialsPoint.com

Fallacies, Misconceptions and Confusion

• A data model:

- does not describe (just) the structure of a database.
- is not "a conceptualization between attributes and entities" (whatever that means).

• Entities, entity sets and relationships are not building blocks of a data model.

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LATEST POSTS

01/21 Read My Lips: If There's NULLs, It's Not Relational

01/16 OBG: No Understanding without Foundation Knowledge Part 3 -- Debunking an Online Exchange 3

01/08 OBG: No Understanding without Foundation Knowledge Part 3 -- Debunking an Online Exchange 2

01/01 Schema and Performance: Never the Twain Shall Meet

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- 08/19 Logical Symmetric Access, Data Sub-language, Kinds of Relations, Database Redundancy and Consistency, paper #2 in the new UNDERSTANDING THE REAL RDM series.
- 02/18 The Key to Relational Keys: A New Understanding, a new edition of paper #4 in the PRACTICAL DATABASE FOUNDATIONS series.
- 04/17 Interpretation and Representation of Database Relations, paper #1 in the new UNDERSTANDING THE REAL RDM series.
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Fundamentals and Debunking -- References

A data model is a theory of data used to formalize conceptual models of reality as logical models for database representation. It defines not just the database structure, but also its manipulation for inferential purposes and integrity for consistency with conceptual models and correctness of inferences.

• What Is a Data Model and What It Is Not
• Data Model: Neither Business, Nor Logical, Nor Physical Model
• TYFK Data Model, Logical Model and Schema 

Levels of representation

Conceptual: entity,  entity group,  property,  property in context,  relationship
Logical (RDM): tuple,  relation, domain,  attribute,  constraint

• Understanding Conceptual vs. Data Modeling series
• OBG Don't Confuse Levels of Representation series
• The Conceptual-Logical Conflation and the Logical-Physical Confusion
• Levels of Representation: Conceptual Modeling, Logical Design and Physical Implementation
• TYFK Facts, Properties, Relationships, Domains, Relations, Tuples
• Relationships and the RDM series

Note: Entity is a primitive atomic object, entity group is a derived compound object at the conceptual level. RDM domains are distinct from programming data types.

Components of a data model:

Structure (RDM: relation -- domains, attributes, tuples).
Integrity (RDM: constraints -- domain, attribute, tuple, multi-tuple, multi-relation).
Manipulation (RDM: relational algebra -- restrict, project, join, ...)

• What Relations Really Are and Why They Are Important
• Understanding Relations series
• TYFK What Is A Database Relationship
• Understanding Domains and Attributes
• TYFK What Domains Are and Are Not
• Understanding Relational Constraints
• TYFK Semantics, Relations and the Missed Link: Constraints
• Relational and Referential Integrity
• Data Sublanguage: Relational vs. Computational Completeness
• Data Sublanguage: Data Manipulation and Definition
• Data Sublanguages vs. Programming Languages