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predictive analytics : predicts the target measure of interest using regression and classification | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
primary key : special unique identifier for each table record | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
query processor : acts as an intermediary between users and the DBMS data engine to communicate query requests including DML compiler, query parser, query rewriter, query optimizer, and query executor | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
query tree : example of data structure representation for the relational algebra expression | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
query-by-example (QBE) : database query language for relational databases based on domain relational calculus | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
redundant array of inexpensive disks (RAID) : stores information across an array of low-cost hard disks | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
reinforcement : machine learning method based on encouraging desired behaviors and removing undesired behaviors | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
relation : mathematical concept based on the ideas of sets | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
relational algebra : query language that uses unary or binary operators to perform queries | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
relational database design (RDD) : models data into a set of tables with rows and columns | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
relational DBMS : data model in which the data are organized into a relational data model, use SQL as a declarative and set-oriented database, the query processor has a strict separation between the logical and internal data model | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
relative organization : when each record is assigned a numeric key to rearrange the order of the records at any time | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
return on investment (ROI) : ratio of net profits divided by the investment of resources | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
sampling : selecting a subset of historical data to build an analytical model | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
security manager : collection of processes used to secure the database from threats | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
semistructured data : data that are not organized in a formatted database but have some organized properties | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
sequential file organization : records are organized in the order stored and any new record is added at the end | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
single-user DBMS : only one user at a time can use the database | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
snowflake schema : data model that normalizes the dimension table | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
spanned record : when all records are classified into blocks and the length of the record can exceed the size of a block | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
star schema : data model with one large fact table connected to smaller tables | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
storage manager : program that is responsible for editing, storing, updating, deleting, and retrieving data in the database such as transaction manager, buffer manager, lock manager, and recovery manager | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
structured data : data that have been organized into a formatted database and have relational keys | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
Structured Query Language (SQL) : programming language used in programming and managing structured data located in an RDBMS | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
synchronous call : when the client sends a request and waits for a response from the service | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
tablespace : where tables are stored physically in the memory | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
theta join : allows merging two tables based on a theta condition | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
thin client variant : where only the presentation logic is handled by the client and applications and database commands are executed on the server; it is common when application logic and database logic are tightly coupled or similar | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
total cost of ownership (TCO) : cost of owning and operating the analytical model over time | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
transaction : set of database operations induced by a single user or application that should be considered as one undividable unit of work | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
transaction management : delineating transactions within the transaction life cycle | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
transfer learning : machine learning method based on reusing the result of a specific task to start a new task | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
translation : process of translating from high-level language to machine language | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
trigger : statement consisting of declarative and/or procedural instructions and stored in the catalog of the RDBMS | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
tuple : one row with a collection of values separated by a comma and enclosed in parenthesis | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
tuple and document store : database that stores data in XML or JSON format with the document name as key and the contents of the document as value | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
uniqueness constraint : specifies that all the tuples must be unique | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
unstructured data : data that are not organized in a formatted database and do not have organized properties | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
value : actual value derived using the total cost of ownership (TCO) and return on investment (ROI) of the data | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
variety : range of data types and sources that are used; data in its many forms | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
velocity : speed at which data comes in and goes out; data in motion | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
veracity : uncertainty of the data; data in doubt | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
vertical fragmentation : subset of columns of data, global view with JOIN query, and useful if only some of a tupleâs attributes are relevant to a node | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
virtual data mart : usually defined as a single SQL view | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
virtual data warehouse : can be built as a set of SQL views directly on the underlying operational data sources as an extra layer on top of a collection of physical independent data marts | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
volume : amount of data; data at rest | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
weak entity : type of entity that cannot be uniquely identified based on its attributes alone and must rely on a strong entity to provide the context necessary for identification | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
XML DBMS : data model in which the data are using the XML data model to store data | https://openstax.org/books/introduction-computer-science/pages/8-key-terms |
To make a decision, data should be formatted and converted to information. Knowledge comes after processing the information. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Metadata are data about data and are stored in catalogs. The catalog provides an important source of information for end users. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Data quality represents the measure of how well the data represents its purpose. A data quality framework categorizes the different dimensions of data quality such as intrinsic, contextual, representation, and access. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Data governance is a set of clear roles, policies, and responsibilities that enables the enterprise to manage and safeguard data quality. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
There are various data management roles: information architect, database designer, data owner, data steward, database administrator, computer scientist, and data scientist. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
The data management road map has multiple steps, starting from collecting and storing the data to having a final product or decision. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
To store, retrieve, edit, and maintain the related data in the database, we need a system that is adatabase management system (DBMS). | https://openstax.org/books/introduction-computer-science/pages/8-summary |
A database can be defined as a collection of related data items within a specific business process or problem setting. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
A DBMS is the software package used to define, create, use, and maintain a database while considering appropriate security measures. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
There are many characteristics for DBMSs such as loose coupling, efficiency, consistency, and maintenance. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
A DBMS includes various components such as DBMS interface, connection manager, security manager, DDL compiler, query processor, storage manager and DBMS utilities. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Logical data model categories include hierarchical DBMSs, network DBMSs, relational DBMSs, object-oriented DBMSs, XML DBMSs, and NoSQL DBMSs. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
DBMS users may be divided into actors on the scene and workers behind the scene. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
There are various types of database architectures such as centralized DBMS architecture, client server DBMS architecture, n-tier DBMS architecture, cloud DBMS architecture, federated DBMS, and in-memory DBMS. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
The relational model of data is based on the mathematical concept of a relation. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Relational database management systems (RDBMSs) are one type of DBMS that stores related data elements in a row-based table structure. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
SQL is a language used in programming and managing structures data located in a RDBMS. SQL is based on relational algebra with many extensions. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Relational algebra is a query language that uses operators to perform queries. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
The logical design is designing a database based on a specific data model but independent of physical details. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Database normalization is the process of structuring a relational database to reduce data redundancy and improve data integrity. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Relational database design (RDD) models data into a set of tables with rows and columns. Each row represents a record, and each column represents an attribute. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Database tables are stored in a disk storage such as hard disks, flash memory, magnetic disks, optical disks, and tapes. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
File organization and indexing are used to minimize the number of block accesses for frequent queries, and the most popular are sequential, relative, and indexed organization. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
API technologies represent database-related entities in an OO way. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Concurrency control is the coordination of transactions that execute simultaneously on the same data so that they do not cause inconsistencies due to mutual interference. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Data replication is the storage of data in more than one site to improve the data availability and retrieval performance. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Database recovery is the activity of setting the database in a consistent state without any data loss in the event of a failure or when a problem occurs. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Database security uses a set of controls to secure data and guarantee a high level of confidentiality. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
A nonrelational database is a database that does not use traditional ways for storing data. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Flat file databases and multifile relational databases are the two main legacy DBMS. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
A hierarchical model is a model in which data are stored in the form of records and organized into a tree structure. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Non-first normal form (NFNF) is a database data model that does not meet any of the conditions of database normalization defined by the relational model. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Object persistence appears when an object is not deleted until a need emerges to remove it from the memory. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Persistence independence means that an object is independent of how a program manipulates it. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
The relational model has a flat structure, and expensive joins are needed to defragment the data before it can be successfully used, which increases the complexity of the objects due to the normalization. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
An XML database is a data persistence system in which the data are specified and stored in XML format. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Mapping strategies to map XML data into relational databases are table-based mapping, schema-oblivious mapping, and schema-aware mapping. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Unstructured data are managed by key-value stores, tuple and document stores, column-oriented databases, graph-based databases, and other NoSQL databases. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
DaaS is a data management strategy that includes many of technologies such as information life cycle solutions, data modeling, replication, and content management. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
A data warehouse is a relational database that stores processed data that are optimized for gathering business insights to support decision-making process. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
In designing a data warehouse, many schemas can be adopted such as star schema, snowflake schema, and fact constellation. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
ETL is the data extraction, transformation, and loading process. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
A data mart is a scaled-down version of a data warehouse aimed at meeting the information needs of a homogeneous small group of end users. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Virtualization uses middleware to create a logical or virtual data warehouse. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
An operational data store (ODS) is a staging area that provides query facilities. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Data lakes are large data repository that store raw data and can be set up without having to first define the data structure and schema. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Business intelligence (BI) is the set of activities, techniques, and tools aimed at understanding patterns in past data to predict the future. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Data integration aims to provide a unified view and/or unified access over heterogeneous, and possibly distributed, data sources. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Big data encompasses both structured and highly unstructured forms of data. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
The scope of big data has five Vs: Volume, Velocity, Variety, Veracity, and Value. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Data virtualization is a technique that hides the physical location of the data and uses data integration patterns to produce a unified data view. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
Data quality involves various criteria to assess the quality of a dataset. | https://openstax.org/books/introduction-computer-science/pages/8-summary |
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