Download DATA MANAGEMENT FOUNDATIONS 2026 COMPLETE STUDY GUIDE and more Exams Relational Database Management Systems (RDBMS) in PDF only on Docsity!
DATA MANAGEMENT FOUNDATIONS 2026
COMPLETE STUDY GUIDE
◉ Define: Referential Integrity. Answer: Requires that ALL foreign key values must either be fully NULL or match some primary key value. ◉ 4 Ways Referential Integrity can be violated. Answer: 1. Primary key is updated 2. Foreign key is updated 3. Row containing primary key is DELETED 4. Row containing foreign key is INSERTED. ◉ Actions to Correct Referential Integrity Violation. Answer: 1. RESTRICT - rejects an insert, update, or delete 2. SET NULL - sets invalid foreign keys to null 3. SET DEFAULT - sets invalid foreign keys to a default primary value 4. CASCADE - propagates primary key changes to foreign keys. ◉ What is an Important aspect of Referential Integrity. Answer: Reference to data in one relation is based on values in another relation. ◉ What is Broad definition of data. Answer: Raw facts captured on printed or digital media.
◉ What Data. Answer: Facts that are collected and stored in a database system. ◉ Determining characteristic of unstructured data. Answer: It does not follow a data model. ◉ Flat files. Answer: They contain no internal hierarchical organization. ◉ Data retrieval before database management systems. Answer: Sequentially from simple files. ◉ Primary Key. Answer: An attribute or group of attributes that uniquely identify a tuple in a relation. ◉ Foreign Key matching. Answer: A domain of values is necessary for a primary key in one relation of a database to match with its corresponding foreign key in another relation of the same database. ◉ Alternate Key. Answer: What uniquely identifies each entity in a collection of entities but is not the primary key.
◉ Rules/Appearance of Third Normal Form. Answer: - All non-key columns depend ONLY on the primary key - Tables are totally free of data redundancy. ◉ Differences between operational and analytical databases. Answer: - Volatility - Detail - Scope - History. ◉ Volatility. Answer: Database updates in real time. Operational Data is Volatile. Analytical Data is NOT Volatile. ◉ Detail in databases. Answer: - A database that keeps record of individual transactions; line items - Operational: Detailed - Analytical: Detailed. ◉ Scope in databases. Answer: - How far a database can reach - Operational: incompatible - Analytical: Enterprise-Wide/Summary. ◉ History in databases. Answer: - Whether DB is current or tracks all data - Operational: Current only - Analytical: Tracks trends. ◉ Data warehouse refresh process. Answer: 1. Extraction 2. Cleanse
- Integrate 4. Restructure 5. Load.
◉ Extraction in ETL. Answer: Data extracted and put into staging area. ◉ Cleanse in ETL. Answer: Errors are eliminated from data; standard abbreviations applied. ◉ Integrate in ETL. Answer: Data is put into a uniform structure; Data converted to uniform structure. ◉ Restructure in ETL. Answer: Data is structured in a design that is optimal for analysis. ◉ Load in ETL. Answer: Data is loaded to the data warehouse. ◉ Issue focused on 'Load' component of ETL. Answer: Monitor refreshing volume and frequency. ◉ Step in ETL Process where raw data is aggregated. Answer: Transformation steps. ◉ Data mining activities. Answer: 1. Clustering & Segmentation 2. Classification 3. Estimation 4. Prediction 5. Affinity Grouping 6. Description.
◉ ORDER BY clause. Answer: Modifies presentation of data results. ◉ Heap file. Answer: A file where records can be placed anywhere in the memory. ◉ Hash file. Answer: A file that uses Hash function computation on some fields of the records, and the result of that computation determines where the record is stored. ◉ Major Joins. Answer: - LEFT JOIN - RIGHT JOIN - INNER JOIN - FULL JOIN. ◉ Joins. Answer: Joins usually compare the foreign key of one table to the primary key of another table (but can join any columns) - joining together data from two tables into one table. ◉ LEFT JOIN. Answer: Selects all the rows from the left table, and only matching rows from the right table. ◉ RIGHT JOIN. Answer: Selects all the rows from the right table, and only matching rows from the left table.
◉ OUTER JOIN. Answer: Any join that selects unmatched rows; LEFT, RIGHT, or FULL JOINS. ◉ INNER JOIN. Answer: Joins together only rows that match from both tables - contains no unmatched rows. ◉ FULL JOIN. Answer: Fully joins two tables together, even unmatched rows - places a NULL in any cell that does not match the other table. ◉ Signed vs. Unsigned data. Answer: - SIGNED: a number that may be negative - UNSIGNED: a number that can NOT be negative. ◉ CHAR vs. VARCHAR. Answer: - CHAR: Fixed number of characters
- VARCHAR: Variable length of characters. ◉ Record. Answer: A set of one or more fields. ◉ VARCHAR. Answer: Variable length of characters ◉ CHAR. Answer: Fixed number of characters
◉ Business Intelligence System. Answer: Expected to increase profitability, throughput, and visibility while decreasing workloads and improving satisfaction ◉ Relational Model. Answer: A database model based on mathematical principles ◉ Domain. Answer: Set of values = 'Data Type' ◉ Tuple. Answer: Finite sequence of values pulled from a fixed domain = 'Row' ◉ Relation. Answer: A named set of tuples, all from the same domain = 'Table' ◉ Attribute. Answer: A tuple position ◉ Cardinality. Answer: Refers to the MAXIMUM number of times an instance in one entity can be associated with an instance of another entity ◉ Unary Relationship. Answer: One entity involved in a relationship (one box, one line)
◉ Binary Relationship. Answer: Two entities involved in a relationship (two boxes combined by one line) ◉ Mandatory Entity. Answer: Depicted in an ER diagram with a single vertical line through the relationship line ◉ Mandatory. Answer: 'M' shown on an entity in an ER diagram ◉ Primary Identifier. Answer: 'PI' shown on an entity in an ER diagram, used for attribute(s) that uniquely identify the whole entity ◉ Maxima and Minima. Answer: Depicted in an ER diagram as the first letter/number shown (maxima) and the letter next to it in parentheses (minima) ◉ Singular Attribute. Answer: Each entity instance has at most ONE attribute instance ◉ Plural Attribute. Answer: Each entity instance can have MANY attribute instances ◉ Unique Attribute. Answer: Each attribute instance describes only ONE entity instance
◉ Common Attribute. Answer: Defines how a table can be logically connected to another table ◉ Superkey. Answer: An attribute (or group of attributes) that uniquely identifies each entity in a table ◉ Foreign Key. Answer: Must match a primary key in a related table ◉ Entity Relationship Diagram (ERD). Answer: Graphically represents the conceptual database model ◉ Derived Attribute. Answer: Need not be physically stored within the database ◉ Atomic Attribute. Answer: An attribute that cannot be subdivided ◉ Existence-Independent. Answer: An entity that can exist apart from one or more related entities ◉ Partial Dependencies. Answer: Dependencies based on only a part of a composite key
◉ LIKE Operator. Answer: A special operator used to check for similar character strings ◉ INSERT Command. Answer: SQL command that lets you insert data into a table, one row at a time ◉ UPDATE Command. Answer: SQL command that enables you to make changes in the data ◉ data integrity problems. Answer: Issues that affect the accuracy and consistency of data. ◉ Normalization. Answer: A process that works through a series of normal forms. ◉ partial dependencies. Answer: Dependencies based on only a part of a composite primary key. ◉ 1NF relationship. Answer: A table that has all key attributes defined, no repeating groups, and all its attributes are dependent on the primary key. ◉ INSERT. Answer: The SQL command that lets you insert data into a table, one row at a time.
◉ Transformation. Answer: The step in the ETL process where raw data sets are aggregated. ◉ data extraction. Answer: Extract or copy raw data from multiple sources and store it in a staging area. ◉ data transformation. Answer: Transform and consolidate the raw data in the staging area to prepare it for the target data warehouse. ◉ data loading. Answer: Moves the transformed data from the staging area into the target data storage or warehouse. ◉ unnormalized forms. Answer: Tables that have repeating groups, contain multi-valued fields, or fields that contain multiple values. ◉ affinity grouping. Answer: The process of evaluating relationships between data elements to demonstrate an affinity or link between objects. ◉ Prediction. Answer: Classifies objects according to an expected future behavior.
◉ Load. Answer: The step of the ETL process focused on moving transformed data into the data warehouse. ◉ Data warehouse. Answer: The primary source of information that feeds analytical processing for an organization's data analysis. ◉ Increased profitability and increased throughput. Answer: The set of results a company should expect from implementing a business intelligence system. ◉ Data Mart. Answer: A subject-oriented data repository smaller than a data warehouse, normally for a smaller or specific group within an organization. ◉ OLAP vs OLTP. Answer: OLAP is for analysis, and OLTP is for transaction processing. ◉ Staging Area. Answer: The infrastructure where raw data sets are aggregated. ◉ Directed Knowledge Discovery. Answer: Knowledge where you have already identified the problem you want to resolve.
◉ query result set. Answer: The response of the DBMS to a query. ◉ good decision making. Answer: Accurate, relevant, and timely information is the key to. ◉ data dictionary. Answer: The DBMS uses the data dictionary to look up the required data component structures and relationships, thus relieving programmers from having to code such complex relationships in each program. ◉ database management system. Answer: A(n) database management system is a collection of programs that manages the database structure and controls access to the data stored in the database. ◉ field. Answer: A field is a character or group of characters that has a specific meaning. ◉ operational databases. Answer: Data warehouse contains historical data obtained from the operational databases. ◉ collection of files. Answer: The database structure in a DBMS is stored as a collection of files.
◉ Data inconsistency. Answer: Data inconsistency exists when different versions of the same data appear in different places. ◉ application. Answer: A(n) application might be written by a programmer or it might be created through a DBMS utility program. ◉ Knowledge. Answer: Knowledge is the body of information and facts about a specific subject. ◉ semistructured. Answer: An XML database supports the storage and management of semistructured XML data. ◉ True. Answer: The only way to access the data in a database is through the DBMS. ◉ multiuser. Answer: A workgroup database is a(n) multiuser database. ◉ the data always yields consistent results.. Answer: Data is said to be verifiable if the data always yields consistent results. ◉ single-user. Answer: A desktop database is a single-user database.
