176 ;;Quote: data records are entities; inserted, deleted, retrieved, identifies, typed

176 ;;Quote: most data models use data records for real entities and assume that other things are not real entities

177 ;;Quote: there are no objective criteria for the entities identified by data analysis; boundary between entity and non-entity is highly subjective

177 ;;Quote: "important" is subjective and a continuous scale; different things are important to different people in different contexts at different times

177 ;;Quote: the target of most information can be replaced by any of the things involved in the information; e.g., employees in a department

180 ;;Quote: some records correspond one-to-one with entities; the entity exists only if the record exists; referential integrity and primary keys

181 ;;Quote: a field in a record contains a character string that represents something in the real world; e.g., a color

181+;;Quote: any of the things in the real world can be represented by different strings in different fields

181 ;;Quote: a record represents an aggregate of facts, i.e., connections between fields

181+;;Quote: information is expressed by the connections among fields; e.g., a money field is connected to the salary of an employee

181 ;;Quote: describe fields of a data record by entity type, representation type, and relationship to other fields; what, how, and why

183 ;;Quote: a record stores multiple, single-valued facts about the primary key, or it stores a multi-valued/n-ary fact

183 ;;Quote: in fact-based data analysis, identify single-valued facts and multi-valued facts; don't distinguish entities, relationships, or attributes

185 ;;Quote: a data dictionary documents each field by what it is, how it's represented, and why it's there; ties conceptual schema to database