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SIT772.1 - Data and Information Retrieval

Amber Saxon SIT772 English 200 cards

Three Levels of Data Abstraction

Cards in this deck (200)

  1. 1DataData are raw facts and figures that on their own have no meaning (Raw Data)
  2. 2InformationInformation is DATA that has been PROCESSED within a CONTEXT to reveal its MEANING.
    Information consists of transformed DATA and facilitates DECISION MAKING
  3. 3Data ProcessingOrganising data to Reveal Patterns
    Make forecasts
    Draw inferences by using statistical modelling (Information in graphic format).
  4. 4Structured DataData with a well-defined model for information access. (eg, Student List, Product List).
    Data that has been formatted to facilitate storage, use and information generation
  5. 5Unstructured DataData that is not in a well-defined model for information access.
    Data that exists in its original, raw state, ie, in the format in which it was collected.
    Can include text documents, PDFs, voice messages, emails, web-pages etc
  6. 6DatabaseA shared, integrated computer structure that stores a collection of data (End-User Data or Meta-data) that allows access, retrieval and use of data.
    A structure that stores collections of data.
    An electronic filing cabinet
  7. 7End-User Dataraw facts of interest to the end user
  8. 8Metadatadata about data
  9. 9AttributeCOLUMN
    a character or group of characters that have a specific meaning (referred to as columns)
    An attribute has a name and a data type.
  10. 10RecordROW
    A collection of attributes that appear as a row in a database or table.
  11. 11TableA collection of related records
  12. 12Text Formatsword docs, PDFs
  13. 13Image FormatsJPEG, JPG, TIFF, BMP
  14. 14Audio FormatsWAV, MP3, AAC, AIFs
  15. 15Video FormatsSWF, .FLV, .AVI, .MOV or .MPEG.
  16. 16DBMS (Database Management System)A collection of programs that manage the database structure and controls access to the data stored in the database.
    Facilitate the sharing of data among multiple users & applications. Enable efficient and effective data management.
  17. 17Information Retrieval (IR)is the process of INDEXING and RETRIEVING UNSTRUCTURED DATA.
    The public interface for IR is SEARCH ONLY. (eg Web Search & Peer-to-peer Networks)
  18. 18QueryA search in a database for data.
    A question or task asked by an End-User of a Database in the form of SQL code. A specific request for Data Manipulation issued by the End-User of the application to the DBMS.
  19. 19FileA document that is stored on your computer. In Excel, a file is also known as a workbook.
  20. 20FolderA location on disk where you can store files.
  21. 21TableAn arrangement of data made up of horizontal rows and vertical columns.
  22. 22Unstructured Data and Information Retrieval (IR)The "surface web": Docs and search. "Crawler" INDEXES pages on the web. Keyword-based search for pages.
  23. 23DBMS examplesWeb-cache software at Google/Yahoo is a kind of DBMS
  24. 24What is special about IR?Source data is mostly prose, unstructured and untyped. Public interface is SEARCH ONLY. Cant modify data or get summaries. *Can't guarantee freshness of data, consistency, fault tolerance etc.
  25. 25Relational DBMS (RDBMS) examplesOracle, SQL Server, MySQL, DB2, MariaDB, PostgresSQL, Amazon Aurora
  26. 26Information Retrieval (IR) examplesDOCUMENT SEARCH ENGINES - Yahoo, Google, Search, Lucene, Ferret. DESKTOP SEARCH ENGINE - Google Desktop, Copernic desktop, Windows Desktop Search
  27. 27Data ModelA data model represents data structures and their characteristics, relationships, constraints, transformations, and other constructs with the purpose of clarifying a specific problem scenario.
    Simple (and usually graphical) representation of real-world data structures.
    Tool for facilitating interactions between Designers, Programmers and End-users.
  28. 28EntitiesAny object, event, or agent about which data are collected. (eg; employee, student, courses)
  29. 29AttributesCharacteristics of the Entity. (eg; ID, Name, DOB, Manufacturer's Number)
    COLUMN
  30. 30Relationship Pairs1:1 (One to One) 1:M (One to Many) M:N (Many to Many)
  31. 311:1 RelationshipOne to One
  32. 321:M RelationshipOne to Many
  33. 33M:N RelationshipMany to Many
  34. 34Business RulesPolicies, procedures and principles. Business Rules motivate need for information. Determine Database Design. *Data and Business Rules generate information.
  35. 35Data, Information & KnowledgeData are building blocks of Information. Information is the result of processed data. Information is used to reveal meaning of data. Knowledge is the appropriate collection of data. Accurate, relevant, and timely information is the key to good decision making. Good Decision Making is the key to organizational survival.
  36. 36Database ModelA database model helps us to determine how the data is stored, managed and administered.
    Therefore a database model is the tool we use to help us determine the structure of the database.
  37. 37Basic building blocks of a Data ModelEntities,
    Attributes
    Relationships.
  38. 38ERDEntity Relationship Diagram
  39. 39RelationshipsAn associations between entities.
    Relationships are derived from the description of what the business needs (or Business Rules)
  40. 40A Relational ModelA Relational model enables us to visualise data logically, seeing the entities, their attributes, and their relationships
  41. 41TupleROW
    A row in a table represents an individual entity, and technically called a tuple. Each row provides values for each of the table’s columns
  42. 42Entity Relationship Modeldescribes;
    Relationships among Entities
    at the conceptual level with the help of an
    Entity Relationship Diagram (ERD).
  43. 43Entity Relationship Diagram (ERD)A diagram that depicts an;
    Entity relationship model’s
    Entities, Attributes and Relations.
  44. 44Entity integrityPrimary Keys are UNIQUE.
    No part of PK may be NULL.
  45. 45Referential integrityReferences between data are;
    VALID and COMPLETE.
  46. 46PKPrimary Key
  47. 47ConstraintsConstraints are RULES
    that force DBMSs to check that data satisfies the semantics.
  48. 48FKForeign Key
  49. 49Every OS includes a File System. These File Systems..?File Systems
    - manage Files on a magnetic disk
    - allows open, read, seek, close on a file
    - allows protection to be set on a file
    - drawbacks relative to RAM?
  50. 50What more could we want than a File System?- Simple, efficient ad hoc queries
    - concurrency control
    - recovery
    - benefits of good data modeling
  51. 51A Data Model facilitates interactions among...?- Designers
    - Programmers
    - End Users
  52. 52Why do we need Data Models?- The foundation of a good database
    - Blueprint for a database
    - Different users have different needs and views
    - Organizes data for different users
  53. 53Types of Data Models- Relational Model
    - Entity-Relationship Model
    - External Model
    - Conceptual Model
    - Internal Model
    - Physical Model
  54. 54Data Model Relational Model- Developed by Edgar Frank Codd of IBM in 1970.
    - Lets users/designers work in human logical environment
    - Conceptually simple and powerful modelling capabilities
    * Two table can be linked by matching attributes
  55. 55Data Model Entity Relationship (ER) Model- A graphical model introduced in 1976
    - Defines database structures in terms of entities and their relationships.
    - An ER Model maps to relational tables
    - Each entity maps to a relational table
    - Each Entity Instance relate to a table entry (ie, row)
  56. 56Data Model External Model- ER Diagrams are used to represent external views
    - End-users view of the database environment (ie subsets of the database)
    Advantages
    - Easy to identify specific data required to support each business unit's operation
    -Facilitates designers job by providing feedback about the model's adequacy
    - Ensures security constraints in database design
    - Simplifies application program development
  57. 57Data Model Conceptual ModelA global view of the DB (i.e. an integration of all external views)
    - Enterprise wide, Bird's eye level representation
    - Model avoids details
    - Only main objects represented
    - Independent of the software/hardware
    - ER (Entity Relationship) is the most commonly used Database Model
  58. 58Data Model Internal ModelRepresents what the DB 'sees'
    - Translates the Conceptual Model to the DBMS's implementation
    * software dependent
    * hardware independent
    -RELATIONAL (TABLE) MODEL is the most common INTERNAL MODEL.
  59. 59Data Model Physical ModelOperates at the lowest level of ABSTRACTION
    - Specifies how the data are stored
    - software and hardware dependent
    The "data specialist" kind of work
    - Detailed knowledge of hardware and software
    - "Standardize"
  60. 60An Entity SetGroup of Related Entities
  61. 61Table (aka)Aka (A Relation or Entity Set)
    - 2D structure composed of COLUMNS and ROWS
    - Contains group of related entities (ie entity set)
  62. 62The Data DictionaryProvides a detailed description of all tables found within the user/designer-created database
    - Contains (at least) all the ATTRIBUTE names and CHARACTERISTICS for each table in the data system
    i.e.: contains METADATA
  63. 63System Catalog- Contains Metadata
    - Describes all objects within the database.
    - Terms "system catalog" and "data dictionary" are often used interchangeably.
    - Can be queried just like any user/designer-created table
  64. 64Three Levels of Data AbstractionThree Levels of Data Abstraction
  65. 65KeyOne or more ATTRIBUTES whose values can uniquely identify each row
    Each row in a table must be uniquely identifiable.
  66. 66How to identify a KEY?If an ATTRIBUTE or a combination of attributes determines all other attributes, the ATTRIBUTE or the COMBINATION is a KEY.How to identify a KEY?
  67. 67Key AttributeAny attribute that is part of a Key
    eg; STU_NUM, STU_DOB...
  68. 68Composite KEYComposed of more than one Attribute
    eg; STU_FNAME + STU_DOB + STU_PHONE
  69. 69SuperkeyAny key that uniquely identifies EACH ENTITY
    e.g. STU_NUM + STU_FNAME + STU_DOB
  70. 70Candidate KeyA SUPERKEY without REDUNDANCIES
    e.g. STU_NUM
  71. 71Primary Key (PK)A candidate key chosen to be the unique row identifier
    e.g. STU_NUM
    Each table must have a PRIMARY KEY
  72. 72Entity IntegrityPK Column has NO NULL entries
    All entries are UNIQUE
  73. 73NULL ("No data entry")Can represent
    - An unknown attribute value
    - A known, but missing, attribute value
    - A "not applicable" condition
  74. 74Foreign Key (FK)An attribute whose values match Primary Keys in a related table.
    Makes reference to another Table via PK.
  75. 75Referential IntegrityForeign Key contains a value that refers to an existing valid tuple (row) in another relation
  76. 76Secondary KeyKey used strictly for Data retrieval purposes, narrowing down a search
  77. 77RELATIONSHIPS WITHIN THE RDB 1:M Relationship- Relational Modeling ideal
    - Should be the norm in any Relational DB design
  78. 78RELATIONSHIPS WITHIN THE RDB 1:1 RelationshipsShould be rare within any Relational Database Design
  79. 79RELATIONSHIPS WITHIN THE RDB M:N Relationships- Not for ERDs, lead to DATA REDUNDANCIES
    - M:N relationships can be split into two 1:M Relationships    RELATIONSHIPS WITHIN THE RDB M:N Relationships
  80. 80KnowledgeThe body of information and facts about a specific subject.
    Knowledge implies familiarity, awareness and understanding of information as it applies to an environment.
    A key characteristic is that new knowledge can be derived from old knowledge.
  81. 81Data ManagementA process that focuses on data collection, storage and retrieval.
    Common DATA MGT functions include addition, deletion, modification and listing.
  82. 82Data InconsistencyA condition in which different versions of the same data yield different (inconsistent) results.
  83. 83ad hoc queryA "spur of the moment" question.
  84. 84Query Result SetThe Collection of Data rows returned by a Query
  85. 85Data QualityA comprehensive approach to ensuring the Accuracy, Validity and Timeliness of Data.
  86. 86Single-User DatabaseA database that supports only one user at a time
  87. 87Desktop DatabaseA single-user database that runs on a personal computer.
  88. 88Multi-User DatabaseA database that supports multiple concurrent users.
  89. 89Workgroup DatabaseA multi-user database that supports multiple concurrent users.
  90. 90Enterprise DatabaseThe overall company data representation, which provides support for present and expected future needs.
  91. 91Centralized DatabaseA database located at a single site.
  92. 92Distributed DatabaseA logically related database that is stored in two or more physically independent sites.
  93. 93Cloud DatabaseA database that is created and maintained using cloud services, such as Microsoft Azure or Amazon AWS.
  94. 94General Purpose DatabaseA database that contains a wide variety of data used in multiple disciplines.
  95. 95Discipline-specific DatabaseA database that contains data focused on specific subject areas
  96. 96Operational DatabaseA database designed primarily to support a company's day-to-day operations.
    Aka a:
    - TRANSACTIONAL DATABASE
    - OLTP Database
    - Production Database
  97. 97OLTP - Online Transaction Processing DatabaseA database designed primarily to support a company's day-to-day operations.
    Aka a:
    - TRANSACTIONAL DATABASE
    - Operational Database
    - Production Database
  98. 98Analytical DatabaseA database focused primarily on storing historical data and business metrics used for tactical or strategic decision making.
  99. 99Data WarehouseA specialized database that stores historical and aggregated data in a format optimized for decision support.
  100. 100OLAPOnline Analytical Processing
  101. 101Online Analytical Processing (OLAP)A set of tools that provide advanced data analysis for retrieving, processing, and modeling data from the data warehouse.
  102. 102Business IntelligenceA set of tools and processes used to capture, collect, integrate, store and analyze data to support business decision making.
  103. 103Semi-structured DataData that has already been processed to some extent.
  104. 104XMLExtended Mark-up Language
  105. 105Extended Markup Language (XML)A metalanguage used to represent and manipulate data elements.
    Unlike other markup languages, XML permits the manipulation of a document's data elements.
  106. 106XML DatabaseA database system that stores and manages semi-structured XML data.
  107. 107Social MediaWeb and Mobile Technologies that enable "anywhere, anytime, always on" human interactions.
  108. 108NoSQLNot Only SQL
    A new generation of database management systems that is NOT based on the traditional Relational Database Model.
  109. 109Database DesignThe process that yields the description of the database structure and determines the database components.
    The Second Phase of the
    Database Life Cycle.
  110. 110Data Processing (DP) SpecialistThe person responsible for developing and managing a computerized file processing system.
  111. 111FieldA character or group of characters (alphabetic or numeric) that has a specific meaning.
    A field is used to define and store data.
  112. 112Structural DependenceA data characteristic in which a change in the database schema affects data access, thus requiring changes in all access programs.
  113. 113Structural IndependenceA data characteristic in which changes in the database schema do not affect data access.
  114. 114Data DependenceA data condition in which data representation and manipulation are dependent on the physical data storage characteristics.
  115. 115Logical Data FormatThe way a person views data within the context of a problem domain.
  116. 116Physical Data FormatThe way a computer "sees" (stores) data.
  117. 117Islands of InformationIn the old file system environment, pools of independent, often duplicated and inconsistent data created and managed by different departments
  118. 118Data RedundancyExists when the same data is stored unnecessarily at different places.
  119. 119Data IntegrityIn a Relational Database, a condition in which the data in the database complies with all entity and referential integrity constraints.
  120. 120Data AnomalyA data abnormality in which inconsistent changes have been made to a database. For example, an employee moves, but the address change is not corrected in all files in the database.
  121. 121Database SystemAn organization of components that defines and regulates the collection, storage, management, and use of data in a database environment
  122. 122Data DictionaryA DBMS component that stores metadata - data about data.
    The data dictionary contains data definitions as well as data characteristics and relationships. May also include data that is external to the DBMS.
  123. 123Performance TuningActivities that make a database perform more efficiently in terms of storage and access speed.
  124. 124Query LanguageA nonprocedural language that is used by a DBMS to manipulate its data.
    An example of a query language is SQL.
  125. 125Structured Query Language (SQL)A powerful and flexible relational database language composed of commands that enable users to create database and table structures, perform various type of data manipulation and data administration and query the database to extract useful information.
  126. 126ENTITY RELATIONSHIP MODEL(ER) model defines the conceptual view of a database
    An entity (table) is represented in the ER Diagram by a rectangle, also known as an entity box.
    Each entity consists of a set of attributes that describes particular characteristics of the entity.    ENTITY RELATIONSHIP MODEL
  127. 127ENTITY RELATIONSHIP MODEL Entity BoxAn entity (table) is represented in the ER Diagram by a rectangle, also known as an entity box. Each entity consists of a set of attributes that describes particular characteristics of the entity.ENTITY RELATIONSHIP MODEL Entity Box
  128. 128ENTITY-RELATIONSHIP MODEL RelationshipsRelationships describe associations among entities. Most relationships describe associations between two entities.
    Here we have a one-to-many (1:M) relationship. In other words one Person can own many vehicles.
    This example tells us that there is a link between two tables, and that a Vehicle has one Owner and that a Person may own many vehicles.    ENTITY-RELATIONSHIP MODEL Relationships
  129. 129ENTITY-RELATIONSHIP MODEL Entity Relationship Diagrams (ERD)ENTITY-RELATIONSHIP MODEL Entity Relationship Diagrams (ERD)
  130. 130ENTITY RELATIONSHIP MODEL Entity Relationship Diagram ExampleENTITY RELATIONSHIP MODEL Entity Relationship Diagram Example
  131. 131ENTITY-RELATIONSHIP MODEL ConnectivityThe ER model uses the term connectivity to label the relationship types.
    The name of the relationship is usually an active or passive verb.
    For example, a PAINTER paints many PAINTINGS, an EMPLOYEE learns many SKILLS, and an EMPLOYEE manages a STORE.
  132. 132ENTITY-RELATIONSHIP MODEL Entity Relationship Diagram (ERD)A diagram that depicts an entity relationship model’s;
    Entities, Attributes and Relations.
  133. 133SQL Syntax Diagram for Creating TABLESSQL Syntax Diagram for Creating TABLES
  134. 134SQL Statement Derived from Syntax DiagramAbove, we’ve specified that we are creating a new table called “users”, with three columns: id, name, and address. We’ve also specified that id is a decimal type, and is the primary key. Name and address are both VARCHARs, and can’t be null (can’t be empty).SQL Statement Derived from Syntax Diagram
  135. 135SQL INSERT into a TABLESQL INSERT into a TABLE
  136. 136SQL INSERT into TABLESQL INSERT into TABLE
  137. 137SQL SELECT from TABLESQL SELECT from TABLE
  138. 138SQL SELECT from TABLE, WHERESQL SELECT from TABLE, WHERE
  139. 139Data ModelingThe process of creating a specific data model for a determined problem domain.
  140. 140Data ModelA representation, usually graphic, of a complex "real-world" data structure.
    Data models are used in the database design phase of the
    DATABASE LIFE CYCLE.
  141. 141EntityA person, place, thing, concept, or event for which data can be stored.
  142. 142ConstraintA restriction placed on data, usually expressed in the form of rules.
    Example: "A student's GPA must be between 0.00 and 4.00"
    Constraints are important because they help to ensure DATA INTEGRITY.
  143. 143Business RuleA description of a policy, procedure, or principle within an organization.
    Example: A pilot cannot be on duty for more than 10 hours during a 24-hr period.
    Example: A professor may teach up to four classes during a semester
  144. 144Hierarchical ModelAn early database model whose basic concepts and characteristics formed the basis for subsequent database development. The model is based on an upside-down tree structure in which each record is called a segment. Each segment has a 1:M reationship
  145. 145SegmentIn the hierarchical data model, the equivalent of a file system's record type
  146. 146Network ModelAnearly data model that represented data as a collection of record types in 1:M relationships
  147. 147SchemaA logical grouping of database objects, such as tables, indexes, views and queries, that are related to each other.
  148. 148SubschemaThe portion of the database that interacts with application programs
  149. 149Data Manipulation Language (DML)The set of commands that allows an end-user to manipulate the data in the database.
    Examples: SELECT, INSERT, UPDATE, DELETE, COMMIT, and ROLLBACK
  150. 150Data Definition Language (DDL)The language that allows a database administrator to define the database structure, schema, and subschema.
  151. 151Relational ModelDeveloped by E.F. Codd of IBM in 1970, the RELATIONAL MODEL is based on mathematical set theory and represents data as independent relations. Each relation table is conceptually represented as a two-dimensional structure of intersecting rows and columns. The relations are related to each other through the sharing of common entity characteristics (values in columns).
  152. 152Table (relation)A two-dimensional structure composed of intersecting rows (entities) and columns (attributes) that represents an ENTITY SET in the RELATIONAL MODEL.
  153. 153Tuplein the RELATIONAL MODEL, a table ROW.
  154. 154Relational DiagramA graphical representation of a relational database's entities, the attributes within those entities, and the relationships among the entities.
  155. 155Entity Relationship (ER) Model (ERM)A data model that describes relationships (1:1, 1:M and M:N) among entities at the conceptual level with the help of ER diagrams.
    The model was developed by Peter Chen.
  156. 156Entity Relationship Diagram (ERD)A diagram that depicts an entity relationship model's entities, attributes, and relations.
  157. 157Entity Instance (Entity Occurrence)A row in a relational table
  158. 158Entity SetA collection of like entities
  159. 159ConnectivityThe type of relationship between entities.
    Classifications; 1:1, 1:M and M:N
  160. 160Chen NotationEntity Relationship Model
  161. 161Crow's Foot NotationA representation of the ENTITY RELATIONSHIP DIAGRAM that uses a three-pronged symbol to represent the 'many' sides of the relationship.Crow's Foot Notation
  162. 162Class Diagram NotationThe set of symbols used in the creation of class diagrams
  163. 163UMLUnified Modeling Language
    associated with Class Diagram Notation.
  164. 164OODMObject-Oriented Data Model
    A data model whose basic modeling structure is an object.
  165. 165ObjectAn abstract representation of a real-world entity that has a unique identity, embedded properties, and the ability to interact with other objects and itself.
  166. 166OODBMSObject-Oriented Database Management System
    Data Management software used to manage data in an object-oriented database model
  167. 167Semantic Data ModelThe first of a series of data models that more closely represented the real world, modeling both data and their relationships in a single structure known as an object. The SDM, published in 1981, was developed by M. Hammer and D. McLeod.
  168. 168ClassA collection of similar objects with shared structure (attributes) and behaviour (methods).
    A class encapsulates an object's data representation and a method's implementation.
    Classes are organized in a class heirarchy
  169. 169MethodIn the Object-Oriented Data Model, a named set of instructions to perform an action. Methods represent real-world actions, and are invoked through messages.
  170. 170Class HierarchyThe organization of classes in a hierarchical tree in which each parent class is a superclass and each child class is a subclass. (See also inheritance).
  171. 171InheritanceIn the Object-Oriented Data Model, the ability of an object to inherit the data structure and methods of the classes above it in the class hierarchy.
  172. 172Unified Modeling Language (UML)A language based on object-oriented concepts that provide tools such as diagrams and symbols to graphically model a system.
  173. 173Class DiagramA diagram used to represent data and their relationships in UML object notation.
  174. 174Extended Relational Data Model (ERDM)A model that includes the object-oriented model's best features in an inherently simpler relational database structural environment.
    (see extended entity relationship model - EERM)
  175. 175Object/Relational Database Management System (O/R DBMS)A DBMS based on the extended relational model (ERDM).
    The ERDM, championed by many relational database researchers, constitutes the relational model's response to the OODM. This model includes many of the Object-Oriented model's best features within an inherently simpler relational database structure.
  176. 176Extensible Markup Language (XML)A metalanguage used to represent and manipulate data elements. Unlike other markup languages, XML permits the manipulation of a document's data elements. XML facilitates the exchange of structured documents such as orders and invoices over the internet.
  177. 177Big DataA movement to find new and better ways to manage large amounts of web-generated data and derive business insight from it, while simultaneously providing high performance and scalability at a reasonable cost
  178. 1783 VsVolume
    Velocity
    Variety
  179. 179HadoopA Java based, open source, high speed, fault-tolerant distributed storage and computational framework.
    Hadoop uses low-cost hardware to create clusters of thousands of computer nodes to store and process data.
  180. 180HDFSHadoop Distributed File System
    A highly distributed, fault-tolerant file storage system designed to manage large amounts of data at high speeds
  181. 181Name NodeOne of three types of nodes used in the Hadoop Distributed File System (HDFS).
    The NAME NODE stores all the METADATA about the FILE SYSTEM.
    (see also; client node and data node)
  182. 182Data NodeOne of three types of NODES used in the HADOOP DISTRIBUTED FILE SYSTEM (HDFS).
    The DATA NODE stores fixed-size data blocks (that could be replicated to other data nodes)
  183. 183Client NodeOne of three types of NODE used in the HADOOP DISTRIBUTED FILE SYSTEM
    HDFS
    The CLIENT NODE acts as the interface between the user application and the HDFS
    (see also Name Node and Data Node)
  184. 184MapReduceAn open-source application programming interface (API) that provides fast data analytics services; one of the main Big Data technologies that allow organizations to process massive data stores.
  185. 185NoSQLNot Only SQL
    A new generation of database management systems that is not based on the traditional relational database model.
  186. 186Key-ValueA DATA MODEL based on a structure composed of two data elements; a key and a value, in which every key has a corresponding value or set of values. The key-value data model is also called the associative or attribute-value data model.
  187. 187Sparse DataA case in which the number of table attributes is very large but the number of actual data instances is low
  188. 188Eventual ConsistencyA model for database consistency in which updates to the database will propagate through the system so that all data copies will be consistent eventually.
  189. 189ANSIAmerican National Standards Institute
    ANSI
    The group that accepted the DBTG recommendations and augmented database standards in 1975 through its SPARC committee
  190. 190EXTERNAL MODELThe application programmer's view of the data environment. Given its business focus, an external model works with a data subset of the global database schema.
  191. 191EXTERNAL SCHEMAThe specific representation of an external view; the end-user's view of the data environment
  192. 192CONCEPTUAL MODELThe output of the conceptual design process. The conceptual model provides a GLOBAL VIEW of an entire database and describes the main data objects, avoiding details
  193. 193SOFTWARE INDEPENDENCEA property of any model or application that does not depend on the software used to implement it
  194. 194HARDWARE INDEPENDENCEA condition in which a model does not depend on the hardware used in the model's implementation. Therefore, changes in the hardware will have no effect on the database design at the conceptual level.
  195. 195LOGICAL DESIGNA stage in the DESIGN PHASE that matches the conceptual design to the requirements of the selected DBMS and is therefore software-dependent.
    LOGICAL DESIGN is used to translate the conceptual design into the internal model for a selected database management system, such as; DB2, SQL Server, Oracle, IMS, Informix, Access, or Ingress
  196. 196INTERNAL MODELIn DATABASE MODELING, a level of DATA ABSTRACTION that adapts the conceptual model to a specific DBMS model for implementation.
    The INTERNAL MODEL is the representation of a database as 'seen' by the DBMS. In other words, the INTERNAL MODEL requires a designer to match the CONCEPTUAL MODEL'S characteristics and CONSTRAINTS to those of the selected implementation model.
  197. 197INTERNAL SCHEMAA representation of an internal model using the database constructs supported by the chosen database.
  198. 198LOGICAL INDEPENDENCEA condition in which the internal model can be changed without affecting the CONCEPTUAL MODEL.
    (The internal model is hardware independent because it is unaffected by the computer on which the software is installed. Therefore, a change in storage devices or operating systems will not affect the internal model).
  199. 199PHYSICAL MODELA model in which physical characteristics such as location, path and format are described for the data.
    The Physical Model is both hardware and software DEPENDENT.
    (See also Physical Design)
  200. 200PHYSICAL INDEPENDENCEA condition in which the physical model can be changed without affecting the INTERNAL MODEL.

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SIT772 Flashcards on SIT772.1 - Data and Information Retrieval, created by Amber Saxon on 17/11/2019.
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