🛢DBMS: Third Normal Form (Definitions)

"Table data that complies with both the first and second normal forms and directly relates to each rows primary key. See also first normal form; second normal form." (Robert D Schneider & Darril Gibson, "Microsoft SQL Server 2008 All-in-One Desk Reference For Dummies", 2008)

"In relational theory, the third of Dr. Codd’s constraints on a relational design: Each attribute must depend only on the primary key." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"Database design approach that eliminates redundancy and therefore facilitates insertion of new rows into tables in an OLTP application without introducing excessive data locking problems.  Sometimes referred to as normalized." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"A level of normalization in which all attributes in a table are fully dependent on its entire key. Third normal form is widely accepted as the optimal design for a transaction system. A schema in third normal form is often referred to as fully normalized, although there are actually additional degrees of normalization possible." (Christopher Adamson, "Mastering Data Warehouse Aggregates", 2006)

"A table is in 3NF if it is in 2NF and it contains no transitive dependencies." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"A table is in third normal form (3NF) if and only if for every functional dependency X->A, where X and A are either simple or composite attributes (data items), either X must be a superkey or A must be a member attribute of a candidate key in that table." (Toby J Teorey, ", Database Modeling and Design 4th Ed", 2010)

"A table is in 3NF when it is in 2NF and no non-key attribute is functionally dependent on another non-key attribute; that is, it cannot include transitive dependencies." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"An entity is in third normal form if and only if it is in second normal form and every non-key attribute is non-transitively dependent on the primary key." (Craig S Mullins, "Database Administration", 2012)

🛢DBMS: Backup (Definitions)

"(1) A system, component, file, procedure, or person available to replace or help restore a primary item in the event of a failure or externally caused disaster. (2) To create or designate a system, component, file, procedure, or person as in (1)." (IEEE, "IEEE Standard Glossary of Software Engineering Terminology", 1990)

"A copy of a database or transaction log, used to recover from a media failure." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A copy of a database, transaction log, file, or filegroup. Use this object to recover data after a system failure." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A spare copy of a file or files that have been created in case the original data is damaged or lost." (Andy Walker, "Absolute Beginner’s Guide To: Security, Spam, Spyware & Viruses", 2005)

"Making copies of data to a device other than the original data store." (Tom Petrocelli, "Data Protection and Information Lifecycle Management", 2005)

"This is a copy of a database that can be used to bring the database back to a stable condition in the event of a disaster." (Joseph L Jorden & Dandy Weyn, "MCTS Microsoft SQL Server 2005: Implementation and Maintenance Study Guide - Exam 70-431", 2006)

"The process of copying your database’s information to another form of media, such as tape or disk. A good backup strategy is vital for any production SQL Server environment." (Robert D Schneider & Darril Gibson, "Microsoft SQL Server 2008 All-in-One Desk Reference For Dummies", 2008)

"(1) The process of making a copy of data from a database to ensure its continued availability in the event of a hardware or software failure requiring recovery of the database to restore the data. (2) The copy itself." (Craig S Mullins, "Database Administration", 2012)

"A duplicate of a program, a disk, or data, made either for archiving purposes or for safeguarding files." (Microsoft, "SQL Server 2012 Glossary", 2012)

"A utility that copies databases, files, or subsets of databases and files to a storage medium. This copy can be used to restore the data in case of system failure." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A complete spare copy of data for purposes of disaster recovery. Backups are nonindexed mass storage and cannot substitute for indexed, archived information that can be quickly searched and retrieved (as in archiving)." (Robert F Smallwood, "Information Governance: Concepts, Strategies, and Best Practices", 2014)

"A copy of a database or table space that can be stored on a different medium and used to restore the database or table space in the event of failure or damage to the original." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

"Copying data to protect against loss of integrity or availability of the original." (ITIL)

🛢DBMS: Transaction Log Backup (Definitions)

 "A backup of the transaction log that flushes the transactions from the transaction log to a file. To have transaction log backup integrity, each consecutive file must not break the LSN chain." (Allan Hirt et al, "Microsoft SQL Server 2000 High Availability", 2004)

"A backup of transaction logs that includes all log records not backed up in previous log backups. Log backups are required under the full and bulk-logged recovery models and are unavailable under the simple recovery model." (SQL Server 2012 Glossary, "Microsoft", 2012)

"This type of backup makes a copy of all transactions in the transaction log, and it can clear all the inactive transactions from the log, thus giving the log more space to hold new transactions." (Joseph L Jorden & Dandy Weyn, "MCTS Microsoft SQL Server 2005: Implementation and Maintenance Study Guide - Exam 70-431", 2006)

"A backup of transaction logs that includes all log records not backed up in previous log backups. Log backups are required under the full and bulk-logged recovery models and are unavailable under the simple recovery model." (Microsoft, "SQL Server 2012 Glossary", 2012)

"Special database backups that contain a sequential record of all data modifications that have occurred within a database. Transaction log backups can be used to perform point-in-time recovery. See also point-in-time recovery." (Mark Rhodes-Ousley, "Information Security: The Complete Reference, Second Edition, 2nd Ed.", 2013)

🛢DBMS: Full Backup (Databases)

"A complete point-in-time backup of a database." (Allan Hirt et al, "Microsoft SQL Server 2000 High Availability", 2004)

"A backup of the entire hard drive or array." (Tom Petrocelli, "Data Protection and Information Lifecycle Management", 2005)

"This is a type of backup that backs up the entire database, but not the transaction logs." (Joseph L Jorden & Dandy Weyn, "MCTS Microsoft SQL Server 2005: Implementation and Maintenance Study Guide - Exam 70-431", 2006)

"A backup of the entire database that includes the database files, the locations of those files, and the portions of the transaction log (from the LSN recorded at the start of the backup to the LSN at the end of the backup). This is the first type of backup you will need to do in any backup strategy because all the other backup types depend on the existence of a full backup. A full backup is sometimes called a baseline in a backup strategy." (Marilyn Miller-White et al, "MCITP Administrator: Microsoft® SQL Server™ 2005 Optimization and Maintenance 70-444", 2007)

"A full backup backs up the complete database. This includes all data, all objects, and all files. A full backup also backs up the transaction log, but does not truncate it. Both differential and transaction log backups need to have a full backup done first." (Darril Gibson, "MCITP SQL Server 2005 Database Developer All-in-One Exam Guide", 2008)

"As its name implies, this type of backup archives all information within a database. Should the database be lost or damaged, you can restore it to its state as of the time you created the full backup. See also full differential backup; partial backup; restore." (Robert D Schneider & Darril Gibson, "Microsoft SQL Server 2008 All-in-One Desk Reference For Dummies", 2008)

"A backup of an entire database." (SQL Server 2012 Glossary, "Microsoft", 2012)

"A backup operation that backs up all files and sets their archive attribute to Off." (Faithe Wempen, "Computing Fundamentals: Introduction to Computers", 2015)

🛢DBMS: First Normal Form (Definitions)

"Eliminate repeating groups, such that all records in all tables can be identified uniquely, by a primary key in each table. In other words, all fields other than the primary key must depend on the primary key." (Gavin Powell, "Beginning Database Design", 2006)

"A relation is in first normal form if it contains no repeating groups." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"One of the three normal forms that make up relational database guidelines, this rule states that a table should not have any repeating fields." (Robert D Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"A table is in 1NF if it satisfies basic conditions to be a relational table." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"A table is in first normal form (1NF) if and only if there are no repeating columns of data taken from the same domain and having the same meaning." (Toby J Teorey, ", Database Modeling and Design 4th Ed", 2010)

"In relational theory, the first of Dr. Codd’s constraints on a relational design: Every tuple may have only one value for an attribute in a relation." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"The first stage in the normalization process. It describes a relation depicted in tabular format, with no repeating groups and with a primary key identified." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"An entity is in first normal form if and only if all underlying domains contain atomic values only." (Craig S Mullins, "Database Administration", 2012)

🛢DBMS: Incremental Backup (Definitions)

"Backups that only copy objects that have changed since the last backup." (Tom Petrocelli, "Data Protection and Information Lifecycle Management", 2005)

"A database backup containing only the data that has changed since the last full backup or incremental copy was made." (Craig S Mullins, "Database Administration", 2012)

"A backup that saves files that have changed since the last backup. When data is backed up, the archive bit on a file is turned off, and when changes are made to the file, the archive bit is set again. An incremental backup uses this information to only back up files that have changed since the last backup. An incremental backup turns the archive bit off again, and the next incremental backup backs up only the files that have changed since the last incremental backup. This sort of backup saves time, but it means that the restore process will involve restoring the last full backup and every incremental backup made after it." (Mark Rhodes-Ousley, "Information Security: The Complete Reference, Second Edition, 2nd Ed.", 2013)

"A backup operation that backs up all files that have the archive attribute set to On and then sets the attribute to Off." (Faithe Wempen, "Computing Fundamentals: Introduction to Computers", 2015)

"A copy of all database data that has changed since the most recent successful full backup operation. An incremental backup is also known as a cumulative backup image because each incremental backup includes the contents of the previous incremental backup." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Differential Backup (Definitions)

"A database backup that records only pages that have changed in the database since the last full database backup. A differential backup is smaller and faster to restore than a full backup and has minimal effect on performance." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"This type of database backup records only those changes made to the database since the last full database backup. A differential backup is smaller, and is faster to restore than a full backup and has minimal effect on performance." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A type of database backup that only backs up changes made to the database since the last full database backup." (Allan Hirt et al, "Microsoft SQL Server 2000 High Availability", 2004)

"This is a type of backup that backs up changes to the database only since the last full backup was made." (Joseph L Jorden & Dandy Weyn, "MCTS Microsoft SQL Server 2005: Implementation and Maintenance Study Guide - Exam 70-431", 2006)

"A backup type that backs up all the changes since the last full backup. Since the differential backup only backs up the changes, it can be done much quicker than a full backup. A possible backup strategy might include performing a full backup once a week and doing differential backups daily." (Darril Gibson, "MCITP SQL Server 2005 Database Developer All-in-One Exam Guide", 2008)

"A backup containing only changes made to the database since the preceding data backup on which the differential backup is based." (Microsoft, "SQL Server 2012 Glossary", 2012)

"A database backup operation that copies only the database pages that have been modified since the last full database backup." (Mark Rhodes-Ousley, "Information Security: The Complete Reference, Second Edition" 2nd Ed., 2013)

"Like an incremental backup, but only backs up files with the archive bit set—files that have changed since the last backup. Unlike the incremental backup, however, it does not reset the archive bit. Each differential backup backs up all files that have changed since the last backup that reset the bits. Using this strategy, a full backup is followed by differential backups. A restore consists of restoring the full backup and then only the last differential backup made." (Mark Rhodes-Ousley, "Information Security: The Complete Reference, Second Edition, 2nd Ed.", 2013)

"A backup operation that backs up all files that have the archive attribute set to On but does not change that attribute." (Faithe Wempen, "Computing Fundamentals: Introduction to Computers", 2015)

[delta backup:] "A copy of all database data that has changed since the last successful backup (full, incremental, or delta) of the table space in question. A delta backup is also known as a differential, or noncumulative, backup image. The predecessor of a delta backup image is the most recent successful backup that contains a copy of each of the table spaces in the delta backup image." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Cardinality (Definitions)

 "The classification of a relationship; for example, one-to-many, many-to-many, and so on." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"The number of tuples (rows) in a relationship. For example, a relationship can be one-to-one, one-to-many, or many-to-many." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"The number of unique values for a given column in a relational table. Low cardinality refers to a limited number of values, relative to the overall number of rows in the table." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit 2nd Ed ", 2002)

"Cardinality denotes the maximum number of occurrences of one entity that can be related to another entity. Usually, these are expressed as “one” or “many.” Change Data Capture Change data capture is a technique for propagating only changes to source data through the data acquisition process." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"The number of distinct values in a column of a table." (Bob Bryla, "Oracle Database Foundations", 2004)

"The cardinality of a relationship represents the number of occurrences between entities. An entity with a cardinality of one is called a parent entity, and an entity with a cardinality of one or more is called a child entity." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"The number of distinct values taken on by an attribute." (Christopher Adamson, "Mastering Data Warehouse Aggregates", 2006)

"The number of tuples in a relation." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A representation of the minimum and maximum allowed number of values for an attribute. In semantic object models, written as L.U where L and U are the lower and upper bounds. For example, 1.10 means an attribute must occur between 1 and 10 times." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"A relationship in a data model denoting how many instances of one entity class can be related to an instance of another entity class - zero, one, or many." (Danette McGilvray, "Executing Data Quality Projects", 2008)

"The measure of the number of elements within a set of values. For example, the set A = { 2, 4, 6 } contains 3 elements, and has a cardinality of 3." (MongoDb, "Glossary", 2008)

"In relationships, the characteristic  of a relationship that specifies the upper and lower bounds of how many instances of one entity or object type can be related to each instance of the same or some other entity or object type. Cardinality is separately specified at each end of the relationship. At each end the choices are 0, 1, or M. Combining the cardinality at both ends of a binary relationship, yields 3 x 9 - 1 = 8 possibilities (0:0 is not a valid option)." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The number of entities or members in a set." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The number of entities that can exist on each side of a relationship." (Microsoft, "SQL Server 2012 Glossary", 2012)

"The number of occurrences that may exist between a pair of entities. Another way of looking at cardinality is as the number of entity occurrences applicable to a specific relationship. Sometimes the term degree is used instead of cardinality. An alternate usage of the term cardinality within the realm of database administration is a database statistic used by the relational optimizer defining the number of occurrences of a value within a column (or set of columns)." (Craig S Mullins, "Database Administration", 2012)

"The number of rows that is expected to be or is returned by an operation in an execution plan. Data has low cardinality when the number of distinct values in a column is low in relation to the total number of rows." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

"The number of occurrences of two units of data that participate in a relationship" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"The cardinality of a relationship is the number of instances that can be associated with each entity type in a relationship." (Robert J Glushko, "The Discipline of Organizing: Professional Edition, 4th Ed", 2016)

"The number of rows in a database table or the number of elements in an array. See also associative array." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Second Normal Form [2nd NF] (Definitions)

"The second normal form (2NF) requires that all attributes be dependent on the whole key. To attain 2NF, the entity must be in 1NF and every nonprimary attribute must be dependent on the entire primary key for its existence. 2NF further reduces possible redundancy in the data model by removing attributes that are dependent on part of the key and placing them in their own entity." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A relation schema R is in 2NF if every nonprime attribute A in R is fully functionally dependent on the primary key of R." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A table is in 2NF if it is in 1NF and every field that is not part of the primary key depends on every part of the primary key." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"Data is said to be in the second normal form if it complies with the first normal form and has one or more columns in a table that uniquely identify each row." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"A table is in second normal form (2NF) if and only if each non-key attribute (data item) is fully dependent on the primary key, that is either the left side of every functional dependency (FD) is a primary key or can be derived from a primary key." (Toby J Teorey, ", Database Modeling and Design" 4th Ed, 2010)

"In relational theory, the second of Dr. Codd’s constraints on a relational design: Each attribute must depend on the entire primary key." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"The second stage in the normalization process in which a relation is in 1NF and there are no partial dependencies (dependencies in only part of the primary key)." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"An entity is in second normal form if and only if it is in first normal form and every non-key attribute is fully dependent on the key." (Craig S Mullins, "Database Administration", 2012)

"The second level of normalization for a table in a relational database. A table is in 2NF if:" (Rod Stephens, "Beginning Software Engineering", 2015)

🛢DBMS: Denormalization (Definitions)

"The technique of placing data often accessed/used together in a physical location that optimizes the performance of the system." (Margaret Y Chu, "Blissful Data ", 2004)

"An intentional violation of the rules of normalization done to increase performance of a database. It typically occurs in varying degrees during all phases of physically implementing a database. Database designs are often denormalized to accomplish a specific performance-related goal. Denormalization can’t be done without a thorough understanding of the data and the needs of the customer." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"The process of adding planned redundancy to an already fully normalized data model." (Thomas Moore, "EXAM CRAM™ 2: Designing and Implementing Databases with SQL Server 2000 Enterprise Edition", 2005)

"The technique of placing normalized data in a physical location that optimizes the performance of the system." (William H Inmon, "Building the Data Warehouse", 2005)

"Most often the opposite of normalization, more commonly used in data warehouse or reporting environments. Denormalization decreases granularity by reversing normalization, and otherwise." (Gavin Powell, "Beginning Database Design", 2006)

"Organization of data by minimizing joins between tables and storing redundant values in a single table to reduce query time." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

"The process of adding planned redundancy to an already fully normalized data model." (Thomas Moore, "MCTS 70-431: Implementing and Maintaining Microsoft SQL Server 2005", 2006)

"Denormalization is the process of combining tables so that they are easier to query. Denormalization is opposite to normalization. Denormalization is done to improve query performance." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"The formal process of introducing redundancy back into the database design to improve performance." (Victor Isakov et al, "MCITP Administrator: Microsoft SQL Server 2005 Optimization and Maintenance (70-444) Study Guide", 2007)

"Denormalization is the process of extracting data from normalized tables in the relational model of a data warehouse." (Robert Nisbet et al, "Handbook of statistical analysis and data mining applications", 2009)

"The consolidation of database tables to increase performance in data retrieval (query), despite the potential loss of data integrity. Decisions on when to denormalize tables are based on cost/benefit analysis by the DBA." (Toby J Teorey, ", Database Modeling and Design 4th Ed", 2010)

"A process by which a table is changed from a higher level normal form to a lower level normal form. Usually done to increase processing speed. Potentially yields data anomalies." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed, 2011)

"Undoing the effect of normalization; the process of putting one fact in numerous places in the database." (Craig S Mullins, "Database Administration", 2012)

"The intentional duplication of columns in multiple tables to increase data redundancy. Denormalization is sometimes used to improve performance." (Sybase, "Open Server Server-Library/C Reference Manual", 2019) 

🛢DBMS: Transaction Log File (Definitions)

"A system table (syslogs) in which all changes to the database are recorded." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A reserved area of the database in which all changes to the database are recorded. The transaction log is stored in the Syslogs system table and is used by SQL Server during automatic recovery." (Patrick Dalton, "Microsoft SQL Server Black Book", 1997)

"A reserved area set aside for each database on the SQL Server that records all changes diat are made to die database. This enables SQL to recover a database if system problems are encountered." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"A file or set of files containing a record of a database's transactions." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A file or set of files containing a record of the modifications made in a database." (Thomas Moore, "EXAM CRAM™ 2: Designing and Implementing Databases with SQL Server 2000 Enterprise Edition", 2005)

"Transactions in SQL Server are written to the transaction log before they are written to the database. This log information is used primarily for database recovery in the event of a disaster." (Joseph L Jorden & Dandy Weyn, "MCTS Microsoft SQL Server 2005: Implementation and Maintenance Study Guide - Exam 70-431", 2006)

"A file containing a record of database changes." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"File that records transactional changes occurring in a database, providing a basis for updating a master file and establishing an audit trail." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A file-system–based, internal database construct that records data and table modifications, making it possible to restore information to its previous state should the application roll back a transaction." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"A file used by the database management system to record all database transactions. The log file is used for recovery of the database in case of failures." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

"A feature used by the DBMS to keep track of all transaction operations that update the database. The information stored in this log is used by the DBMS for recovery purposes." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"A collection of records describing the sequence of events that occur during DBMS execution to be used for database recovery in the event of a DBMS failure." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed., 2012)

"A file that records transactional changes occurring in a database, providing a basis for updating a master file and establishing an audit trail." (Microsoft, "SQL Server 2012 Glossary", 2012)

"A collection of records that sequentially describes the events that occur in a system. A record of events." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

"A set of primary and secondary log files consisting of log records that record all changes to a database. The database log is used to roll back changes for units of work that are not committed and to recover a database to a consistent state." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Entity Relationship Diagram [ERD] (Definitions)

"A graphical method of showing the entities, relationships, and attributes in a data model." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"Drawings of boxes and lines to communicate the relationship between tables. Both third normal form (3NF) and dimensional models can be represented as ER diagrams because both consist of joined relational tables. The key difference between the models is the degree of dimension normalization. A dimensional model is a second normal form (2NF) model." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"The ERD is a proven and reliable data-modeling approach with straightforward rules of construction. The normalization rules yield a stable, consistent data model that upholds the policies and rules of engagement established by the enterprise. The resulting database schema is the most efficient in terms of storage and data loading as well." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A diagram that represents the structural contents (the fields) in tables for an entire schema, in a database. Additionally included are schematic representations of relationships between entities, represented by various types of relationships, plus primary and foreign keys." (Gavin Powell, "Beginning Database Design", 2006)

"A diagram (or graph) of entities and their relationships, and possibly the attributes of those entities." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"A diagram that depicts an entity relationship model’s entities, attributes, and relations." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed, 2011)

"The graphical diagram for an Entity Relationship data model. The underlying data model generally includes more semantics than is or can be represented in the view shown on the diagram, e.g., some business rules." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

 "An E/R diagram graphically depicts the entities and relationships of a data model." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed, 2012)

🛢DBMS: Normalization (Definitions)

"Normalization is the database design process of discarding repeating groups, minimizing redundancy, eliminating composite keys for partial dependency, and separating non-key attributes. Various levels of normalization and various rules or tests have been formalized for performing normalization." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"The process of transforming database designs into logical structures by following rules and principles of relational database theory. Different 'normal forms' exist, each further reducing both redundancy and the possibility of update anomalies. 'Third normal form' is a design in which all the attributes of each row 'depend on the key, the whole key, and nothing but the key'." (Bill Pribyl & Steven Feuerstein, "Learning Oracle PL/SQL", 2001)

"The process of designing a database so that its tables follow the rules specified by relational theory. In practice, this usually means that all database tables are in third normal form." (Peter Gulutzan & Trudy Pelzer, "SQL Performance Tuning", 2002)

"Normalization is a method for ensuring that the data model meets the objectives of accuracy, consistency, simplicity, nonredundancy, and stability. It is a physical database design technique that applies mathematical rules to the relational data model to identify and reduce insertion, updating, or deletion anomalies." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A formal approach in data modeling that examines and validates attributes and their entities in the Logical data model. The purpose of data normalization is to ensure that each attribute belongs to the entity to which it has been assigned, that redundant storage of information is minimized, and that storage anomalies are eliminated." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling 2nd Ed.", 2005)

"Developed by Dr. E. F. Codd in 1970, database normalization is the process of simplifying data and database design to achieve maximum performance and simplicity. This process involves the removing of useless and redundant data." (Thomas Moore, "EXAM CRAM™ 2: Designing and Implementing Databases with SQL Server 2000 Enterprise Edition", 2005)

"A process by which a relational schema design is adjusted to reduce the possibility of storing data redundantly. As a schema is normalized, attributes that contain repeating values are moved into new tables and replaced by a foreign key. This process requires analyzing and understanding the dependencies among attributes and key columns. There are several degrees of normalization, which formally describe the extent to which redundancies have been removed. Third normal form (3NF) is widely accepted as the optimal relational design for a transaction system. A star schema design is often referred to as denormalized, although it is actually in second normal form." (Christopher Adamson, "Mastering Data Warehouse Aggregates", 2006)

"The organization of data to reduce redundancy by creating many linked tables so that a value is stored in only one place." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

"The process of simplifying the structure of data. Normalization increases granularity and Granularity is the scope of a definition for any particular thing. The more granular a data model is, the easier it becomes to manage, up to a point, depending, of course, on the application of the database model." (Gavin Powell, "Beginning Database Design", 2006)

"A formal process of removing redundancy from a database design by separating it into children tables from the parent table." (Victor Isakov et al, "MCITP Administrator: Microsoft SQL Server 2005 Optimization and Maintenance (70-444) Study Guide", 2007)

"Logical design process in which data is separated into multiple, related tables. The process allows databases to perform optimally." (Sara Morganand & Tobias Thernstrom , "MCITP Self-Paced Training Kit : Designing and Optimizing Data Access by Using Microsoft SQL Server 2005 - Exam 70-442", 2007)

"The design process for generating entity specifications to minimize both data redundancy and update anomalies." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A series of database design recommendations that dictate how information should be dispersed among tables as well as how these tables should relate." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"The process of transforming the database's structure to minimize the changes of certain kinds of data anomalies." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"The process of designing relations to adhere to increasingly stringent sets of rules to avoid problems with poor database design." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"The process of breaking up a table into smaller tables to eliminate problems with unwanted loss of data (the egregious side effects of losing data integrity) from the deletion of records and inefficiencies associated with multiple data updates." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"The process, originally articulated by Dr. E. F. Codd in his relational theory, for organizing data to reduce redundancy to the minimum possible. It involves guaranteeing that each attribute in a 'relation' (table or entity class) is truly an attribute of that relation and none other. The process involves organizing data to follow the constraints of at least first normal form, second normal form, and third normal form. Additional value is found in Boyce-Codd normal form, fourth normal form, and fifth normal form." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"A process that assigns attributes to entities in such a way that data redundancies are reduced or eliminated." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"The process of organizing data to minimize redundancy and remove ambiguity. In simple terms, normalization is the process of identifying the one best place each fact belongs." (Craig S Mullins, "Database Administration", 2012)

"The process of organizing data at its detailed level into according to its existence criteria" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"The process of restructuring a data model by reducing its relations to their simplest forms. It is a key step in the task of building a logical relational database design. Normalization helps avoid redundancies and inconsistencies in data. An entity is normalized if it meets a set of constraints for a particular normal form (first normal form, second normal form, and so on)." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Transactions (Definitions)

"A mechanism for ensuring that a set of actions is treated as a single unit of work." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A series of SQL statements that constitute an atomic unit of work: either all are committed as a unit or they are all rolled back as a unit. A transaction begins with the first statement since the last transaction end and finishes with a transaction end (either COMMIT or ROLLBACK) statement." (Peter Gulutzan & Trudy Pelzer, "SQL Performance Tuning", 2002)

"A group of database operations combined into a logical unit of work that is either wholly committed or rolled back. A transaction is atomic, consistent, isolated, and durable." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A logical unit of work consisting of one or more SQL statements that must all succeed or all fail to keep the database in a logically consistent state. A transfer of funds from a bank account is a logical transaction, in that both the withdrawal from one account and the deposit to another account must succeed for the transaction to succeed." (Bob Bryla, "Oracle Database Foundations", 2004)

"A series of database operations that should be treated as a single atomic operation so either they all occur or none of them occur." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"One or more SQL statements that make up a unit of work performed against the database. Either all the statements in a transaction are committed as a unit or all the statements are rolled back as a unit." (John Goodson & Robert A Steward, "The Data Access Handbook", 2009)

"A group of database operations combined into a logical unit of work that is either wholly committed or rolled back. A transaction is atomic, consistent, isolated, and durable." (Jim Joseph, "Microsoft SQL Server 2008 Reporting Services Unleashed", 2009)

"An atomic unit of work with respect to recovery and consistency." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed, 2012)

"An atomic unit of work with respect to recovery and consistency." (Craig S Mullins, "Database Administration", 2012)

"Each individual purchase. Each time customers swipe a card, shell out cash, or press the purchase confirmation button online, a transaction takes place. This data often is referred to as transaction log (T-log) data." (Brittany Bullard, "Style and Statistics", 2016)

🛢DBMS: Entity-Relationship Model [ERM] (Definitions)

"A common way to organize, think about, or discuss the elements of the 'real world' that a database design will represent, by dividing them into entities and relationships." (Bill Pribyl & Steven Feuerstein, "Learning Oracle PL/SQL", 2001)

"A type of conceptual data model that represents structured data in terms of entities and relationships. An entity-relationship diagram can be used to represent information objects and their relationships visually. Because the constructs used in the entity-relationship model can easily be transformed into relational tables, this type of model is often used in database design." (J P Getty Trust, "Introduction to Metadata" 2nd Ed., 2008)

"A data model that is used to represent data in its purest form and to define relationships between different entities." (Laura Reeves, "A Manager's Guide to Data Warehousing", 2009)

"A technique for representing entity relationships that is independent of any specific data model and any specific software." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"A conceptual data model involving entities, relationships among entities, and attributes of those entities." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"A data model developed by P. Chen in 1975. It describes relationships (1:1, 1:M, and M:N) among entities at the conceptual level with the help of ER diagrams." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"An abstract and conceptual representation of data. Entity-relationship model consists of a set of entities, characterized by attributes and linked by relationships." (International Qualifications Board for Business Analysis, "Standard glossary of terms used in Software Engineering", 2011)

"1.Generally, a record-based data modeling scheme that focuses on entities and relationships in the presentation of data model diagrams, thus suppressing the display of attributes. A true ER model allows multi-valued data items and repeating groups of items (nested relations, thus violating first normal form), retains M:N relationships, attributed relationships, subtypes/supertypes, ternary and higher-order relationships, none of which can be represented directly in a relational data model. A true ER model generally excludes (defers) the representation of entity identifiers and foreign keys. Originally proposed and named by Peter Chen (1976). 2.In relational modeling, the most popular style of data model, defining entities and the business relationships between the entities. Some more detailed models include also some of the attributes of these entities, usually those involved in the relationships as keys." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A data management approach that graphically represents relationships between data. This allows developers to create new relationships between data sources without complex programming." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A logical view of data within a system, representing the entities in the system as well as relationships among the entities, attributes of the entities, and attributes of the relationships." (IEEE 610.5-1990)