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Normalization is a database design technique, which is used to design a relational database table up to higher normal form. [9] The process is progressive, and a higher level of database normalization cannot be achieved unless the previous levels have been satisfied.
An alternative (and seldom used) name for the method is "Common Foundational Integration Modelling Architecture." [19] Data Vault 2.0 [20] [21] has arrived on the scene as of 2013 and brings to the table Big Data, NoSQL, unstructured, semi-structured seamless integration, along with methodology, architecture, and implementation best practices.
Set up the table relationships – Look at each table and decide how the data in one table is related to the data in other tables. Add fields to tables or create new tables to clarify the relationships, as necessary. Refine the design – Analyze the design for errors. Create tables and add a few records of sample data.
A common practice is to entitle list articles as List of ___ (for example List of Xs).If (as is often the case), the list has multiple columns and so is in layout table form, the name or title List of Xs is still preferable to Table of Xs or Comparison of Xs (though the latter may be appropriate for articles that are actual tables of data comparing numerous features, e.g. Comparison of Linux ...
All data tables need a table caption that succinctly describes what the table is about. [WCAG 2] It plays the role of a table heading, and is recommended as a best practice. [2] You would usually need some kind of heading or description introducing a new table anyway, and this is what the caption feature exists for. Table captions are made with |+.
The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions. "Snowflaking" is a method of normalizing the dimension tables in a star schema. When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. The principle ...
Although this design pattern is applicable to most programming languages, most software with persistence needs, and most databases, it is traditionally associated with Java EE applications and with relational databases (accessed via the JDBC API because of its origin in Sun Microsystems' best practice guidelines [1] "Core J2EE Patterns".
In metadata, Naming and Design Rules are the formal rules associated with how data elements are structured within a process of creating exchange documents between organizations. Naming and Design Rules are a set of guidelines and naming conventions that go beyond what a single data exchange standard specification will permit.