There are the various strategies which are considered while designing schema. Most of these strategies follow an incremental approach that is, they must start with some schema constructs derived from the requirements and then they incrementally modify, refine or build on them. Let’s discuss some of these strategies:
- Top-down strategy –
In this strategy, we basically start with a schema that contents high-level of abstraction and then applies successive top-down refinement. Let’s try to understand this with an example, we may specify only a few level entities types and then we specify their attributes split them into lower-level entity types and relationship. The process of specialization to refine an entity type into subclass is also an example of this strategy.
- Bottom-up strategy –
In these type of strategy, we basically start with basic abstraction and then goes on adding to these abstraction. For example, we may start with attributes and group these into entity types and relationships. We can also add a new relationship among entity types as the design go ahead. The basic example is the process of generalizing entity types into the higher-level generalized superclass.
- Inside-Out Strategy –
This is a special case of a bottom-up strategy when attention is basically focused on a central set of concepts that are most evident. Modeling then basically spreads outward by considering new concepts in the vicinity of existing ones. We could specify a few clearly evident entity types in the schema and continue by adding other entity types and relationship that are related to each other.
- Mixed Strategy –
Instead of using any particular strategy throughout the design the requirements are partitioned according to a top-down strategy and part of the schema is designed for each partition according to a bottom-up strategy after that various schema are combined.
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- Relation Schema in DBMS
- Schema Integration in DBMS
- Difference between Schema and Instance in DBMS
- Difference between Snowflake Schema and Fact Constellation Schema
- Difference between Star Schema and Fact Constellation Schema
- Difference between Star Schema and Snowflake Schema
- Mapping Strategies for File records into Blocks
- Difference between Schema and Database
- Create, Alter and Drop schema in MS SQL Server
- Snowflake Schema in Data Warehouse Model
- Star Schema in Data Warehouse modeling
- Types of Keys in Data Warehouse Schema
- Need for DBMS
- The CAP Theorem in DBMS
- Cascadeless in DBMS
- Difference between DDL and DML in DBMS
- Recoverability in DBMS
- Interfaces in DBMS
- Disadvantages of DBMS
- Starvation in DBMS
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