The present invention relates to information processing and more particularly to database access systems and methods such as a relational database access system and method.
Relational database systems are well known in the prior art, and include tabular structures and structured query languages used for database queries. To aid in an understanding of the present invention, a glossary of terms is included hereinbelow.
Relational database technology has made possible an independence between the way data is physically stored and the way it can be handled logically. Relational technology has been widely accepted in business, industry and engineering as valuable for storing data.
Heretofore, most of the advances provided by relational databases has been limited to those users who understand the mathematical principles of relational algebra. Querying a relational database implies a good knowledge of Structured Query Language (SQL) and a good understanding of relational data structures.
Numerous information systems that hide the complexity of SQL and relational databases are based on predefined query techniques. Using those solutions, users can specify parameters in order to add some conditions, but they can never change the meaning of the result. The semantic components of the SQL language (joins and group functions) are stored in the body of the predefined query. When an MIS staff builds an infocenter solution they create user-dedicated tables, relational views or predefined SQL queries accessible by menu triggers.
Usually, if end-users want to change the meaning of a query, either they have to ask the MIS staff to program another query or they have to program the SQL commands themselves. If they do so they will encounter many problems:
the syntax of non procedural structured query language (in particular SQL) is complex. PA1 the data structure is not adapted to the users' everyday work. Relational databases store information as well as relational data such as keys. PA1 is the SQL query semantically correct? Although a query is syntaxically correct, results are not always reliable. SQL as a programmer language does not check the semantic of a query. A more concrete example is the SQL language producing totally a meaningless cross product. This represents a major limitation for end-user access to relational data. PA1 Data: Raw facts or values which are physically recorded and which can be extracted and objectively verified PA1 Information: Anything learned from data, the "meaning" of the data. PA1 Value: An amount of worth PA1 Database: A computerized collection of data PA1 Relational Database: A database in which all data are stored and organized in tables and in which each field containing a datum is equally accessible. PA1 Relational Database Management System (RDBMS): The software environment supporting a Relational database. PA1 Record: A collection of fields; the basic accessible element of a file. PA1 Field: An elemental entity of a record. PA1 Relation: An orderly arrangement of data in columns and rows; a table. PA1 Attribute: A column of a relation, a field of a Tuple. PA1 Tuple: A record of a relational database; one line or row of a table or relation. PA1 Relational Structure: Set of Relations definitions PA1 Infocenter: Environment in which the Users, without any technical knowledge, have "self-service" access to the information system, in a manner controlled by MIS staff. PA1 Universe: An easy-to-understand partial or total representation of the database, designed for a particular application or group of users. PA1 Business Objects: Objects corresponding to concepts close to the user's everyday business. They are defined by the Infocenter Manager and are the basic elements of a Universe. PA1 Context: set of logical equations linking tables (joins) providing a closed graph of table.
USPTO Backgrounds
USPTO Backgrounds