chapter 11 vocab
1-Artificial Intelligence (AI): The simulation of human intelligence in machines programmed to think, learn, and solve problems.
2. Batch Processing: A method of executing tasks or jobs in bulk, typically without user interaction.
3. Binary Large Object (BLOB): A data type used to store large amounts of binary data, such as images or multimedia files.
4. Business Intelligence (BI): Technologies and strategies used by enterprises for analyzing business information to support decision-making.
5. Business Intelligence System: A system that provides tools for analyzing data to help businesses make better decisions.
6. Caption: A label or title that describes the contents of a field or form.
7. Clickstream Data: Data that tracks the paths and clicks made by users as they navigate through a website.
8. Completeness Check: A validation check to ensure that required data is present in a database field.
9. Consistency Check: A check to ensure that data in a database is logically consistent.
10. Data Centralization: The practice of consolidating data from multiple sources into a single location or system.
11. Data Dictionary (Database Schema): A set of metadata that describes the structure, fields, and relationships in a database.
12. Data Inconsistency: When data is not uniform or consistent across different parts of a database or system.
13. Data Integrity: The accuracy and consistency of data within a database.
14. Data Mart: A subset of a data warehouse, usually focused on a specific business area.
15. Data Mining: The process of analyzing large datasets to discover patterns, trends, or relationships.
16. Data Redundancy: The unnecessary duplication of data in a database, which can lead to inconsistencies.
17. Data Staging: A step in the ETL (Extract, Transform, Load) process where data is temporarily stored before being loaded into the data warehouse.
18. Data Type (Field Type): Specifies the type of data that can be stored in a field (e.g., integer, text).
19. Data Warehouse: A large store of data accumulated from various sources, used for analysis and reporting.
20. Database: An organized collection of structured information, typically stored electronically.
21. Database Administrator (DBA) (Database Designer): A professional responsible for managing and maintaining a database system.
22. Database Management System (DBMS): Software that manages databases, providing ways to store, retrieve, and manage data.
23. Decision Support System (DSS): An information system that supports business or organizational decision-making activities.
24. Default Value: A pre-set value that automatically populates a database field unless a user provides a different value.
25. Detail Report: A report that provides a comprehensive list of data, including all fields and records.
26. Enterprise Resource Planning (ERP) System: Software that integrates core business processes such as finance, supply chain, and human resources.
27. Exception Report: A report that highlights data that falls outside of expected or predefined parameters.
28. Expert System: An AI-based system that uses knowledge and inference to solve complex problems or make decisions.
29. Field: A column in a database table that holds a specific type of data (e.g., a customer name).
30. Field Constraint: Rules that define what data is valid for a field, such as field size or data type restrictions.
31. Field Name: The name or label given to a field in a database.
32. Field Properties: Characteristics that define a field, such as data type, size, and constraints.
33. Field Size: The maximum number of characters or amount of data that can be stored in a field.
34. Filter: A tool or query that limits the results of a database search to only records that meet specific criteria.
35. Flat Database: A database that consists of a single table, without relationships between different data sets.
36. Foreign Key: A field in a table that is a primary key in another table, used to link two tables in a relational database.
37. Fuzzy Logic: A form of logic that allows for reasoning about imprecise or uncertain information.
38. Information System: A system that collects, processes, and distributes information, typically consisting of hardware, software, and data.
39. Input Forms: User interfaces that allow data to be entered into a database.
40. Join Query: A SQL query used to combine rows from two or more tables based on a related column.
41. Knowledge-Based System: A computer program that uses knowledge about a domain to provide decision support or solve complex problems.
42. Management Information System (MIS): A system that helps manage and analyze business data to support management decision-making.
43. Many-to-Many Relationship: A database relationship where multiple records in one table are related to multiple records in another table.
44. Metadata: Data that describes other data, providing information about a file, database, or system.
45. Model Management System: Software that manages models used in decision support systems.
46. Multidimensional Database: A database optimized for online analytical processing (OLAP) and designed to manage data in multiple dimensions.
47. Natural Language Processing (NLP) System: A system that enables computers to understand and interpret human language.
48. Normalization: The process of organizing data in a database to reduce redundancy and improve data integrity.
49. NoSQL Database: A type of database designed to handle unstructured data and scalability, often used for big data applications.
50. Numeric Check: A validation check that ensures only numeric data is entered in a field.
51. Object-Oriented Database: A database that represents data in the form of objects, similar to object-oriented programming.
52. Object Query Language (OQL): A query language used to retrieve data from object-oriented databases.
53. One-to-Many Relationship: A database relationship where one record in a table is related to multiple records in another table.
54. One-to-One Relationship: A database relationship where one record in a table corresponds to one record in another table.
55. Online Analytical Processing (OLAP): A tool that enables users to analyze multidimensional data from multiple perspectives.
56. Online Transaction Processing (OLTP): A type of data processing that involves real-time transactions, such as banking or e-commerce.
57. Primary Key Field: A field in a database table that uniquely identifies each record.
58. Query: A request for data or information from a database.
59. Query Language: A programming language used to make queries in a database, such as SQL.
60. Range Check: A validation check that ensures data falls within a specified range.
61. Real-Time Processing: Data processing that occurs instantly or within a short time frame as the data is entered.
62. Record: A row in a database table that contains all the data related to one entity.
63. Referential Integrity: A database concept that ensures relationships between tables remain consistent.
64. Relational Algebra: A set of operations used to manipulate relations (tables) in a relational database.
65. Relational Database: A database structured to recognize relationships among stored data points, typically using tables.
66. Relationship: The connection between tables in a relational database.
67. Select Query: A type of query that retrieves data from one or more tables in a database.
68. Structured (Analytical) Data: Data that is organized into a defined structure, typically in rows and columns.
69. Structured Query Language (SQL): A language used to interact with and manipulate relational databases.
70. Summary Report: A report that provides a condensed overview of data, often aggregating results.
71. Table (File): A collection of related data in a database, organized into rows (records) and columns (fields).
72. Time-Variant Data: Data that is associated with specific time periods, often used in data warehouses.
73. Transaction-Processing System (TPS): A system that handles the collection, storage, and modification of transactions, typically in real-time.
74. Unstructured Data: Data that does not have a predefined structure, such as text, images, or videos.
75. Validation: The process of ensuring that data entered into a system is accurate and meets certain criteria.
76. Validation Rule: A rule that checks data input against predefined criteria to ensure it is correct and usable.