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Static Testing the Logical Design
Published in William E. Lewis, David Dobbs, Gunasekaran Veerapillai, Software Testing and Continuous Quality Improvement, 2017
William E. Lewis, David Dobbs, Gunasekaran Veerapillai
Each entity is a table divided horizontally into rows and columns. Each row is a specific occurrence of each entity, much like records in a file. Each column is an attribute that helps describe the entity. Examples of attributes include size, date, value, and address. Each entity in a data model does not exist by itself; it is linked to other entities by relationships. A relationship is an association between two or more entities of interest to the user, about which the application is to maintain and report data. There are three types of relationships: a one-to-one relationship links a single occurrence of an entity to zero or one occurrence of another entity; a one-to-many relationship links one occurrence of an entity to zero or more occurrences of an entity; and a many-to-many relationship links many occurrences of an entity to many occurrences of an entity. The type of relationship defines the cardinality of the entity relationships. See Appendix G10, “Database Testing,” for more details about data modeling.
Database administration
Published in Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, Texts in Statistical Science, 2017
Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
PRIMARY KEY: a column or set of columns in a table that uniquely identifies each row. By convention, this column is often called id. A table can have at most one primary key, and in general it is considered good practice to define a primary key on every table (although there are exceptions to this rule). If the index spans k < p columns, then even though the primary key must by definition have n rows itself, it only requires nk pieces of data, rather than the np that the full table occupies. Thus, the primary key is always smaller than the table itself, and is thus faster to search. A second critically important role of the primary key is enforcement of non-duplication. If you try to insert a row into a table that would result in a duplicate entry for the primary key, you will get an error.
General introduction
Published in Adedeji B. Badiru, Handbook of Industrial and Systems Engineering, 2013
The idea that database systems should present the user with a view of data organized as tables called relations was originally proposed by Codd (1979). Each relation is made up of attributes. Attributes are values describing properties of an entity, a concrete object in its reality. Furthermore, the connections among two or more sets of entities are called relationships. The idea of a key on a table is central to the relational model. The purpose of a key is to identify each row uniquely. A primary key is the attribute (or combination of attributes) that uniquely identifies one row or record. On the other hand, a foreign key is the attribute (or combination of attributes) that appears as a primary key in another table. Foreign key relationships provide the basis for establishing relationships across tables in a relational database.
Business-Driven Data Recommender System: Design and Implementation
Published in Journal of Computer Information Systems, 2023
Sarah Pinon, Corentin Burnay, Isabelle Linden
The implementation of the second module aims to map the technical jargon of the use’s case database with its business semantic. To achieve it, we instantiated the High-Level Business DWH Ontology with two input’s: The DWH Data Definition Language file: the DDL file of a DWH contains the DWH schema. It includes information on metadata of the DWH such as tables and columns names, primary and foreign keys and the tables’ relationships.37 For our study, we had access to the DDL file of the UNamur DWH;The DWH Data Catalog: this catalog contains several additional information to the DDL file, as explained before, such as some data column values but especially business terms associated to the different data and a business description.18 The Data Catalog of UNamur DWH is partially represented in Table 3 (i.e. a part of the rows representing column values’s business metadata).
An Enhanced Entity Model for Converting Relational to Non-Relational Documents in Hospital Management System Based on Cloud Computing
Published in IETE Technical Review, 2022
A. Samydurai, K. Revathi, L. Karthikeyan, B. Vanathi, K. Devi
Apart from that, SQL also faces a few troubles in writing programs particularly object-oriented language. It is due to the fact that, in the relational database system, the data are stored in the form of tables and each table comprises rows and columns with a pre-determined schedule; however, in object-oriented programming, the data stored in rows and columns are not supported. However, the term template is developed by the designer that describes the information regarding the specified classes. In a few major scenarios, the relational databases suffer from runtime issues, and in the case of sparse tables, these relational databases exhibit several inefficient features. The sparse tables are ordinary tables that comprise rows and columns but the value of numerous rows remains empty for several columns. The shape that represents the sparse table is of semi-structured form whereas the relational database system comprises numerous tables, and for inter-relating the sparse table and the relational database, it is necessary to establish a joining method. Every single join is defined as a jump among two different nodes and along the edge of the network [33].
An efficient approach for land record classification and information retrieval in data warehouse
Published in International Journal of Computers and Applications, 2021
C. B. David Joel Kishore, T. Bhaskara Reddy
In a relational database, the data structure will compose multiple rows and columns in the table, such as user, articles, comments, tags, and sections. In Mongo DB, this information may be transformed into two sets of information and article with textual and spatial land record information. Every blog document contains many comments, multiple tags and many categories. Each section is expressed as a fixed array. In this work, the land record information stored in the database is based on a particular format. This includes the username, the desired land information, the location of the land, the length of the land, and the amount of the land stored in each field of the database. In our structure, the classified data is stored in mongo database as rows and columns. The individual information is stored in a database of personal information. So the information is retrieved from Mongo database in a particular format. Therefore, the fuzzy base ranking function technique is used to get accurate information retrieval.