Types of Schema are as following below.
- Star Schema –
In figuring, the star schema is the least complex style of information store composition and is the methodology most broadly used to create information distribution centers. The star schema schema of at least one actuality tables referencing any number of dimension tables. The star diagram is a significant uncommon instance of the snowflake composition, and is increasingly viable for dealing with less difficult inquiries.
- Snowflake Schema –
Not at all like Star pattern, the dimensions table in a snowflake diagram are standardized. For instance, the thing dimensions table in star construction is standardized and part into two dimensions tables, to be specific thing and provider table.
- Fact Constellation Schema –
The Fact constellation implies at least two reality tables sharing at least one measurements. It is likewise called Galaxy schema. Fact Constellation Schema portrays a consistent structure of data warehouse. Fact Constellation Schema can structure with an assortment of de-standardized FACT Dimension, Shared Dimension, and Conformed Dimension tables.
Types of Keys :
- Primary Key –
Dimension table’s every row is identified by a unique value which is generally known as primary key of the table. Extraordinary type of one of a kind limitation which can be utilized as the essential method to recover an interesting record from the table. Tables can have numerous interesting records, however it can have just a single Primary Key Constraint. This requirement is actualized by means of a one of a kind file and is accessible to be referenced by a Foreign Key.
- Surrogate Key –
These are the keys which are generated by the system and generally does not have any built in meaning. It is UNIQUE since it is consecutively created number for each record being embedded in the table.
It is MEANINGLESS since it doesn’t convey any business significance in regards to the record it is connected to in any table. It is SEQUENTIAL since it is doled out in successive request as and when new records are made in the table, beginning with one and going up to the most elevated number that is required.
For example, on the off chance that the data warehouse contains information around 20,000 clients, who on normal made 15 buys, at that point the fact table will contain around 300,000 surrogate key values, though the dimension table will contain 20,000 business key qualities notwithstanding a similar number of surrogate key values.
- Foreign Key –
In the fact table the primary key of other dimension table is act as the foreign key.
- Alternate key –
It is also a unique value of the table and generally knows as secondary key of the table.
- Composite key –
It is the key which consist of two or more attribute.
For example, the entity has a clientID and a employeeCode as its primary key. Every one of the characteristics that make up the primary key are basic keys on the grounds that each speaks to an exceptional reference while distinguishing a client in one occasion and a employee in the other, so this key is a composite key.
- Candidate key –
A substance type in an intelligent information model will have at least zero competitor keys, likewise alluded to just as one of a kind identifiers . For instance, on the off chance that we just interface with American residents, at that point SSN is one up-and-comer key for the Person element type and the mix of name and telephone number (expecting the mix is one of a kind) is possibly a subsequent competitor key. Both of these keys are called up-and-comer keys since they are possibility to be picked as the essential key, a substitute key or maybe not so much as a key at all inside a physical information model.
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- Snowflake Schema in Data Warehouse Model
- Star Schema in Data Warehouse modeling
- Difference between Star Schema and Snowflake Schema
- Difference between Snowflake Schema and Fact Constellation Schema
- Difference between Star Schema and Fact Constellation Schema
- Difference between Data Warehouse and Data Mart
- Data Mining: Data Warehouse Process
- Difference between Data Lake and Data Warehouse
- Characteristics and Functions of Data warehouse
- Data Warehouse Architecture
- ETL Process in Data Warehouse
- Fact Constellation in Data Warehouse modelling
- Building a Data Warehouse in DBMS
- Difference between Database System and Data Warehouse
- Differences between Operational Database Systems and Data Warehouse
- Testing in Data warehouse
- Difference between Data Warehouse and Hadoop
- Types of Keys in Relational Model (Candidate, Super, Primary, Alternate and Foreign)
- Schema Integration in DBMS
- Strategies for Schema design in DBMS
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