Question 1

File organization basics: Each data file includes a defined structure that specifies how the data is stored within the file. What is this description called?

Accepted Answer

Introduction / Context: Data files are not just raw bytes; they follow a scheme that dictates how information is segmented and interpreted. This question targets the terminology for that scheme. Given Data / Assumptions: A file consists of records, which are composed of fields. The arrangement, sizes, and encodings are predefined. Applications rely on that definition to parse and validate the file's contents. Concept / Approach: The file structure (sometimes called record layout or file format) declares the organization of records and fields, their order, sizes, delimiters, and data types. Without it, consumers of the file cannot reliably read or write the data. Step-by-Step Solution: Identify that the prompt asks for the ‘‘description’’ of storage organization.Differentiate entities (records/fields) from the overarching description.Select ‘‘File structure’’ as the correct term. Verification / Alternative check: Standards like CSV, JSON, and fixed-length record formats are examples of file structures that tools parse systematically. Why Other Options Are Wrong: Database: broader system managing multiple files and relations. Records/Fields: components, not the descriptive scheme. None of the above: incorrect because ‘‘File structure’’ fits precisely. Common Pitfalls: Mixing the names of components with the specification that defines them. Final Answer: File structure

Question 2

Network database model: Which statement correctly describes a key property of the CODASYL network data structure?

Accepted Answer

Introduction / Context: Early database models included hierarchical and network (CODASYL) structures before the rise of relational systems. This question checks understanding of the core capability that distinguished the network model. Given Data / Assumptions: Network databases represent data via sets (owner–member relationships). Navigation proceeds by following pointers between records. Many-to-many relationships are naturally modeled via multiple sets. Concept / Approach: The network model supports flexible connections among record types, enabling many-to-many associations by joining through intersection sets or by multiple membership. This is a logical model with explicit navigational access, not merely a physical byte layout. Step-by-Step Solution: Isolate the unique advantage: direct modeling of complex relationships.Confirm that many-to-many relations are straightforward via sets.Choose the statement that reflects this capability. Verification / Alternative check: Compared with hierarchical models (one-to-many), network structures better represent peer-to-peer linkages without excessive duplication. Why Other Options Are Wrong: Conceptually simple: network navigation can be complex for developers. Physical representation: confuses logical model with storage details. Dominant future: the relational model became the mainstream standard. None of the above: incorrect because many-to-many capability is correct. Common Pitfalls: Assuming ‘‘network’’ refers to computer networking; here it is a database model type. Final Answer: It allows a many-to-many relationship through owner–member sets

Question 3

Logical database structures: Which of the following is not recognized as a standard logical data model?

Accepted Answer

Introduction / Context: Logical data models describe how data is conceptually organized and related, independent of physical storage. Classic models include hierarchical (tree), network (CODASYL), and relational models. This question asks you to spot the odd term out. Given Data / Assumptions: Tree, network, and relational are well-established logical models. ‘‘Chain’’ is not a standard logical model in database theory. Terminology should be historically and academically grounded. Concept / Approach: Evaluate each option for its presence in database literature. Tree, network, and relational appear consistently in textbooks and standards. ‘‘Chain’’ lacks definition as a logical model and does not denote a widely accepted schema organization. Step-by-Step Solution: List known logical models.Compare with the options.Identify ‘‘Chain’’ as the non-standard, thus choose it. Verification / Alternative check: Relational dominance in practice and the historical presence of hierarchical and network models confirm the standard trio; ‘‘Chain’’ does not appear as a recognized model. Why Other Options Are Wrong: Tree, relational, network: all canonical logical models. All of the above: false because three are valid logical models. Common Pitfalls: Confusing physical data chains or linked lists with an abstract database model. Final Answer: Chain model

Question 4

File hierarchy reminder: In secondary storage, a typical file hierarchy is bits → characters → fields → records → files. A single record most directly contains which elements?

Accepted Answer

Introduction / Context: Understanding file organization helps with parsing, validation, and storage design. The question asks where a ‘‘record’’ sits in the hierarchy and what directly composes it. Given Data / Assumptions: Hierarchy: bits → characters → fields → records → files. A record groups related fields (e.g., CustomerID, Name, Balance). Schema defines layouts but is not contained in each record instance. Concept / Approach: A record is the logical aggregation of fields. While characters and bits are building blocks, they are lower-level constituents of fields. The schema or record layout describes structure but is metadata separate from each data instance. Step-by-Step Solution: Recall the standard hierarchy.Map ‘‘record’’ to its immediate components: fields.Select ‘‘Fields (a collection of data items)’’ as correct. Verification / Alternative check: Common file formats (CSV, fixed-length) define records as rows and fields as columns; a record equals a set of fields. Why Other Options Are Wrong: Characters/Bits only: too low-level; they compose fields but not directly the logical unit. Schema definitions: metadata, not the content of a single record. None of the above: incorrect because fields are correct. Common Pitfalls: Conflating physical byte layout with logical composition; a record’s immediate components are fields. Final Answer: Fields (a collection of data items)

Question 5

Operational data files: In large information systems, which file is maintained on an ongoing basis and updated continually with transaction activity (i.e., a perpetual file)?

Accepted Answer

Introduction / Context: Enterprises manage multiple file types: master, transaction (update), and logs. The question tests whether you can identify the file that is persistently maintained to reflect the current state of key entities (customers, inventory, accounts). Given Data / Assumptions: A perpetual file is continuously current. Transactions modify balances, statuses, or counts over time. The system aims to present up-to-date records for operations and reporting. Concept / Approach: The master file stores the authoritative, current values for entities. Transaction (update) files capture events to be applied; log files record activity for auditing and recovery. After processing, the master file remains the ongoing, perpetual record. Step-by-Step Solution: Differentiate file roles: master vs. transaction vs. log.Identify the one that persists as the canonical, updated state: master file.Choose ‘‘Master file’’ as correct. Verification / Alternative check: Batch and online systems apply transaction files to master files; logs help reconstruct or audit, but the master is the perpetual source of truth. Why Other Options Are Wrong: Update file: transient inputs, not the enduring state. Log file: audit trail, not the operational record. Specialized file: purpose-specific, not the general perpetual ledger. Common Pitfalls: Confusing the flow of data (transaction → master update) with the identity of the ongoing file. Final Answer: Master file

Question 6

Data entry design: In an information system, a ‘‘form’’ primarily defines which aspects of how data is captured on screen?

Accepted Answer

Introduction / Context: Forms are the user-facing artifacts for entering and reviewing data. Good form design ensures consistent capture, readable layout, and constrained inputs. This question focuses on two core responsibilities of forms: placement and field sizing. Given Data / Assumptions: Forms specify visual layout: labels, fields, grouping. Forms define field dimensions or limits (e.g., width, max length). Other constraints (validation rules) may exist but are beyond the two items explicitly listed. Concept / Approach: A form controls where users see and input information and how much they can enter into each field (width/length). These two aspects are foundational to consistency and data quality during entry, whether on paper or on-screen. Step-by-Step Solution: Identify responsibilities listed: placement and width.Recognize both are integral to form design.Select ‘‘Both (a) and (b)’’. Verification / Alternative check: GUI builders and form designers always manage layout grids and field properties such as lengths and masks, confirming the role described. Why Other Options Are Wrong: (a) only or (b) only: incomplete; forms manage both. All of the above: inappropriate when only two concrete aspects are offered. None of the above: contradicted by standard UI practice. Common Pitfalls: Assuming ‘‘All of the above’’ is always safest; evaluate exactly what is listed. Final Answer: Both (a) and (b)

Question 7

When working with a database management system (DBMS) on a microcomputer, what is the very first action you must perform before creating databases or manipulating records?

Accepted Answer

Introduction / Context: Before any meaningful data work can begin, a database management system (DBMS) must be running so that it can interpret Structured Query Language (SQL) statements, manage files, and enforce constraints. This question checks the logical order of operations when starting database tasks on a personal computer or workstation. Given Data / Assumptions: You are using a standalone microcomputer with DBMS software installed. Typical DBMS tasks include creating databases, designing tables, and running queries. Tools like text editors or removable media may exist but are not substitutes for the DBMS runtime. Concept / Approach: A DBMS provides the engine for database creation and access. Without loading (starting) the DBMS, commands such as CREATE DATABASE, CREATE TABLE, or INSERT cannot be executed, because no database engine is available to parse and run them. Only after the DBMS is active should you proceed to create database files or connect to existing ones. Step-by-Step Solution: Start the DBMS application so the database engine is running.Connect or authenticate if required by the DBMS.Create or open a database file using DBMS commands/GUI.Define schema (tables, keys) and then enter or import data. Verification / Alternative check: Attempting to run SQL commands without a running DBMS results in errors or no action; starting the DBMS enables database creation and management features. Why Other Options Are Wrong: Create a new database file immediately: Impossible without the DBMS engine loaded. Activate a generic file editor: Editors do not enforce schemas or process SQL. Keep a floppy disk ready: Media readiness is irrelevant to the logical first step. None: Incorrect because loading the DBMS is required. Common Pitfalls: Assuming file editors or OS utilities can substitute for DBMS functions; they cannot handle transactions, constraints, or SQL parsing. Final Answer: Load the DBMS software into the microcomputer and start it

Question 8

In standard SQL administration, which command is used to enable or disable an existing database trigger cleanly and safely?

Accepted Answer

Introduction / Context: Triggers are database objects that fire automatically in response to data changes. Administrators often need to temporarily disable or later re-enable triggers during bulk loads, maintenance, or troubleshooting. Knowing the correct command to toggle a trigger is a basic operational skill in SQL environments. Given Data / Assumptions: We are working in an SQL-compliant relational database. The trigger already exists and must be enabled or disabled. User-related commands are not typically used to manage triggers. Concept / Approach: The appropriate DDL (Data Definition Language) statement to change properties of an existing trigger is ALTER TRIGGER. Variants across vendors may include clauses like ENABLE or DISABLE, but the canonical operation is performed through the ALTER TRIGGER statement, not through user-modification commands. Step-by-Step Solution: Identify the object to modify: an existing trigger.Choose the DDL verb that alters an object’s state or definition: ALTER TRIGGER.Apply ENABLE or DISABLE as supported by the specific RDBMS.Verify trigger status via system catalogs or SHOW/SELECT metadata queries. Verification / Alternative check: Most major RDBMSs (e.g., SQL Server, Oracle, PostgreSQL via ALTER TABLE ... DISABLE TRIGGER) use ALTER semantics to control trigger state or attachment; user commands do not affect triggers. Why Other Options Are Wrong: CHANGE USER / MODIFY USER: Manage accounts and permissions, not triggers. All of the above: Incorrect because only ALTER TRIGGER is relevant. None: Incorrect since ALTER TRIGGER exists for this purpose in mainstream systems. Common Pitfalls: Confusing trigger state control with user management; mixing vendor syntax without checking the object type. Final Answer: ALTER TRIGGER

Question 9

In many data management environments, after you modify a record's values, which operation are you considered to have performed before issuing a command to save or commit the changes?

Accepted Answer

Introduction / Context: Most database front-ends and DBMS clients distinguish between changing data in memory (or a pending state) and making those changes permanent on disk. This question tests the correct terminology for modifying an existing record's field values before committing the transaction or saving the row. Given Data / Assumptions: You have altered one or more column values of an existing record. The environment may require an explicit save/commit to persist the change. We are not deleting the row or changing physical storage structures like indexes. Concept / Approach: Changing the values of a record is an update. In SQL, this corresponds to the UPDATE statement. Many tools cache the change until the user clicks Save or until a COMMIT is issued; until then it may be pending or uncommitted. The logical operation remains an update, not a delete or indexing action. Step-by-Step Solution: Identify the action performed: field values of an existing row were edited.Map this to the database operation: UPDATE.Recognize that persistence typically requires SAVE or COMMIT.Conclude that the operation is an update followed by a save/commit. Verification / Alternative check: In SQL logs or UI audit trails, the change is recorded as an UPDATE statement; a subsequent COMMIT finalizes it for durability. Why Other Options Are Wrong: Delete: Removes rows rather than changing values. Index / Sort key: Concerned with access paths and ordering, not data modification. None: Incorrect because the correct term is well-established. Common Pitfalls: Assuming autosave always occurs; many systems require explicit commits to avoid losing updates on rollback. Final Answer: Update

Question 10

Across record-management systems, which primitive operations are universally supported for basic data handling and retrieval tasks?

Accepted Answer

Introduction / Context: Whether a system is a legacy file manager or a modern relational DBMS, there are baseline operations that enable users to prepare, find, and present data. Recognizing these core capabilities helps learners map high-level requirements to the correct low-level tools in any environment. Given Data / Assumptions: We consider generic record-management functions, not vendor-specific features. Sorting organizes records for reporting or analysis. Look-up retrieves records matching criteria. Printing or report output renders the data for consumption. Concept / Approach: Core primitives generally include sorting (by keys/fields), look-up (exact match or condition-based retrieval), and print/report generation (formatting results). Even sophisticated systems build complex features atop these fundamentals, such as indexed look-ups, ORDER BY sorts, and reporting services for printed or electronic output. Step-by-Step Solution: List universal tasks: organize, retrieve, and present records.Map to primitives: Sort, Look-up, and Print/Report.Confirm that each appears across diverse systems and interfaces.Select the option including all three primitives. Verification / Alternative check: From early flat-file managers to SQL engines, ORDER BY (sort), SELECT ... WHERE (look-up), and reporting/printing facilities are ubiquitous, confirming the selection. Why Other Options Are Wrong: Choosing only one primitive ignores the broad, minimal toolset needed for practical record handling. None: Incorrect because the listed operations are standard features. Common Pitfalls: Overlooking that printing today includes electronic reports and exports, not just paper hard copies. Final Answer: All of the above

Question 11

Regarding legacy reporting tools, which statement about sort/report generators versus index/report generators is generally correct in terms of resources and workflow?

Accepted Answer

Introduction / Context: Classic reporting pipelines often relied on either pre-sorting data (sort/report) or leveraging indexes (index/report). Understanding their trade-offs clarifies performance tuning and storage planning for reporting workloads, especially in environments with limited resources or batch processing constraints. Given Data / Assumptions: Sort/report workflows create sorted intermediate files prior to formatting output. Index/report workflows read records in indexed order without full re-sorts. Disk I/O and temporary storage are key resource considerations. Concept / Approach: A sort/report generator typically materializes temporary sorted datasets, consuming extra disk space and I/O. Index/report generators can stream records in key order via the index, which reduces temporary storage and can be faster in many cases. Therefore, it is generally true that sort/report generators require more disk space; the claim that they are faster or that they do not need to sort is usually false in comparison to index-driven approaches. Step-by-Step Solution: Compare workflows: sort-first vs. index-ordered retrieval.Note that sort/report writes large temporary runs → more disk space.Observe that index/report may avoid full sorts, streaming directly by key.Select the statement that remains true across typical implementations: more disk required by sort/report. Verification / Alternative check: Batch ETL and mainframe-era documentation consistently describe sort phases generating external files, while indexed scans minimize temporary storage. Why Other Options Are Wrong: Faster than index/report: Usually not; sorts add overhead. No need to sort: Contradicts the very nature of sort/report. Both (a) and (b): Incorrect because (a) is not generally true. Common Pitfalls: Assuming modern in-memory sorts always beat index scans; scale and I/O patterns matter. Final Answer: Sort/report generators require more disk space than index/report generators

Question 12

Which database model enforces a one-to-many hierarchy where each child record type has exactly one parent, although a parent may have one or more children?

Accepted Answer

Introduction / Context: Different logical data models impose different relationship constraints. Recognizing the model from a brief relationship description helps you match data structures to appropriate systems and query methods, especially when migrating from legacy systems to modern relational platforms. Given Data / Assumptions: The relationship is strictly one-to-many. Each child has only one parent (no many-to-many at the child side). A parent can have multiple children. Concept / Approach: The hierarchical model organizes data as a tree. Each child node (record) links to exactly one parent, while parent nodes may have several children. This mirrors file-system-like structures and contrasts with the network model (which permits many-to-many via sets) and the relational model (which expresses relationships via keys without enforcing a single-parent rule). Step-by-Step Solution: Parse the description: single parent per child implies a tree.Map tree-structured data to the hierarchical database model.Exclude network model (many-to-many) and relational (general-purpose via keys).Select ‘‘Hierarchical database’’ as the best fit. Verification / Alternative check: Classic hierarchical systems (e.g., IBM IMS) exemplify single-parent, one-to-many structures, confirming the mapping. Why Other Options Are Wrong: Network database: Allows many-to-many via owner/member sets. Relational database: Does not constrain to one parent; relationships are flexible via keys. Distributed database: Describes deployment topology, not logical model. None: Incorrect because the hierarchical model matches exactly. Common Pitfalls: Confusing logical data model (hierarchical vs network vs relational) with physical distribution (distributed). Final Answer: Hierarchical database

Question 13

In SQL data manipulation, which statement is used to add (append) one or more new rows into an existing table?

Accepted Answer

Introduction / Context: CRUD operations (Create, Read, Update, Delete) are the backbone of relational data work. Knowing which SQL statement adds new tuples (rows) to a table is essential for application development, ETL jobs, and ad hoc data loading tasks across all RDBMS platforms. Given Data / Assumptions: A target table already exists with defined columns. We intend to add one or multiple rows to it. We seek the standard SQL command name, not vendor-specific aliases. Concept / Approach: The SQL statement for adding new rows is INSERT. Syntax variants include INSERT INTO table (col1, col2) VALUES (...), or INSERT INTO table SELECT ... to insert multiple rows from a query. Other verbs like ALTER TABLE modify schema, not data, and APPEND/ADD ROW are not standard SQL keywords even if some tools use similar wording in their GUIs. Step-by-Step Solution: Identify the intended operation: create new row(s) in an existing table.Map to the SQL DML verb: INSERT.Recall syntax for single-row and multi-row inserts.Confirm that other listed verbs alter schema or are non-standard. Verification / Alternative check: All major RDBMS document INSERT as the standard for adding rows, ensuring portability of scripts and applications. Why Other Options Are Wrong: ALTER TABLE: Changes table definition, not content. APPEND / ADD ROW: Not standard SQL keywords. None: Incorrect because INSERT is the correct standard statement. Common Pitfalls: Forgetting to list columns, causing column-order mismatches; neglecting NOT NULL or constraint requirements during INSERT. Final Answer: INSERT

Question 14

In transactional SQL, which command makes permanent all data changes made since the start of the current transaction (or since the last commit/rollback)?

Accepted Answer

Introduction / Context: Transactional control is vital to ensure atomicity, consistency, isolation, and durability (ACID). After issuing DML statements such as INSERT, UPDATE, or DELETE, you must confirm whether to keep or discard those changes. The command that finalizes changes is fundamental across relational databases. Given Data / Assumptions: You have executed one or more DML statements in a transaction. Autocommit may be off, requiring an explicit action. You want to persist changes permanently. Concept / Approach: COMMIT ends the current transaction and makes all its changes durable. If you instead want to undo them, you use ROLLBACK. Non-SQL terms like ZIP or PACK are unrelated to transactional control, and SAVE is not a standard SQL transaction-finalizing keyword (though some tools present a 'save' button that issues COMMIT under the hood). Step-by-Step Solution: Review recent DML operations performed within the transaction.Choose to persist the changes → issue COMMIT.Confirm success through affected row counts or subsequent SELECTs.If needed, use ROLLBACK instead to undo. Verification / Alternative check: DBMS logs and transaction monitors will show a commit record; after COMMIT, changes survive client disconnects or server restarts (subject to durability mechanisms). Why Other Options Are Wrong: SAVE: Not a standard SQL keyword for finalizing transactions. ZIP/PACK: Refer to compression/maintenance concepts, not SQL transactions. None: Incorrect because COMMIT is well-defined in SQL. Common Pitfalls: Relying on autocommit inadvertently; forgetting to commit leaves changes unpersisted and vulnerable to rollback on session end. Final Answer: COMMIT

Question 15

Within the hierarchy of data organization, what is the highest level that logically encompasses files, records, and fields into a coherent, managed collection?

Accepted Answer

Introduction / Context: Information systems often describe data structures in a hierarchy: bits → bytes → fields → records → files → databases. Understanding this hierarchy helps clarify scope, responsibility, and tooling, especially when designing schemas and organizing storage across multiple applications or departments. Given Data / Assumptions: A ‘‘database’’ may contain multiple files/tables and associated metadata. Files contain records, which contain fields. We are choosing the topmost logical container in common usage. Concept / Approach: A database is the managed, integrated collection of data and schema, often including tables, indexes, stored procedures, constraints, and security definitions. It logically sits above files and records, enabling centralized control, integrity, and access through a DBMS. The term ‘‘data bank’’ is nonstandard or obsolete compared to ‘‘database.’’ Step-by-Step Solution: Recall the standard hierarchy culminating in the database level.Recognize that a database aggregates multiple files/tables and related objects.Eliminate lower-level units (record, file) and dated terminology (data bank).Select ‘‘Database’’ as the highest logical level. Verification / Alternative check: DBMS documentation consistently defines a database as the overarching container for tables/files and schema objects used by one or more applications. Why Other Options Are Wrong: Data record / data file: Subcomponents within a database. Data bank: Informal, dated term lacking precise technical meaning. None: Incorrect because ‘‘Database’’ precisely matches the definition. Common Pitfalls: Confusing a single application file with a full database; modern systems extend beyond flat files to relational objects and metadata. Final Answer: Database

Question 16

In data modeling, what does a network schema allow that a hierarchical schema does not—specifically with respect to relationship cardinalities?

Accepted Answer

Introduction / Context: Logical database models—hierarchical, network, and relational—differ in how they represent relationships. Understanding these differences is crucial when selecting a model for complex domains or when translating legacy schemas into modern relational designs. Given Data / Assumptions: Hierarchical models form strict trees (one parent per child). Network models generalize to graphs using owner/member sets. Relational models represent data in tables with keys and can express many-to-many via junction tables. Concept / Approach: Network schemas (CODASYL model) allow records to participate in multiple sets, enabling many-to-many relationships directly. This contrasts with hierarchical schemas, which restrict child records to a single parent, and with relational schemas that use tables, not sets, to encode relationships. Thus, the salient capability of the network model is direct support for many-to-many via set membership. Step-by-Step Solution: Identify the unique capability: multiple owners/memberships for a record.Map this to the network (CODASYL) model with set constructs.Eliminate hierarchical (one-to-many only) and relational (table-centric) descriptions.Select the option highlighting many-to-many support. Verification / Alternative check: Legacy CODASYL documentation and textbooks describe owner–member sets enabling non-tree relationships, confirming the answer. Why Other Options Are Wrong: Restricts to one-to-many: That is hierarchical, not network. Stores data in tables: That is relational, not network. All of the above / None: Both contradict the specific capability of the network model. Common Pitfalls: Conflating logical models (hierarchical/network/relational) with physical storage or modern SQL implementations. Final Answer: Permits many-to-many relationships via set membership

Question 17

In a relational database for the 'abc' application, if you want to group or organize records meaningfully for reporting and sorting, which attribute could appropriately serve as the sort key (for example, using Jobcode to cluster related rows togeth…

Accepted Answer

Introduction / Context: Data administrators often need to group and order records so that related rows appear together in reports, exports, or user interfaces. Choosing an appropriate sort key (also called a control key or grouping key) ensures that records with the same attribute value naturally cluster. This question uses the example attribute ‘‘Jobcode’’ in the ‘‘abc’’ database to test your understanding of how grouping by a key works in practice. Given Data / Assumptions: You have a table of records that includes a column named Jobcode. The goal is to group related records (for example, by job family or role). We are not modifying or deleting data; we only want to organize output logically. Concept / Approach: In reporting and query operations, the column used to define grouping or ordering is commonly called a sort key. When you sort by Jobcode, rows with the same Jobcode appear consecutively, making subtotals, page breaks, and summaries straightforward. While indexes speed up searching and sorting, the conceptual term for the attribute by which data is grouped in output is ‘‘sort key.’’ Step-by-Step Solution: Identify the attribute that defines logical groupings: Jobcode.Recognize that grouping for display or reporting relies on a key used in ORDER BY or GROUP BY.Name of that organizing attribute: the sort key. Verification / Alternative check: Run queries such as: SELECT Jobcode, COUNT(*) FROM Employees GROUP BY Jobcode ORDER BY Jobcode. The column used to group/order (Jobcode) is functioning as the sort key for meaningful clustering. Why Other Options Are Wrong: Index: an index accelerates access; it is not itself the grouping concept used in reporting. Update: a data modification command, unrelated to grouping. Delete: removes rows, not an organization mechanism. None of the above: incorrect because ‘‘Sort Key’’ is correct. Common Pitfalls: Confusing the physical structure (index) with the logical grouping concept (sort key). Although sorting may use indexes, the term that answers the conceptual question is the sort key. Final Answer: Sort Key

Question 18

In standard SQL administration, which statement is used to enable or disable all triggers on a specific table in one step?

Accepted Answer

Introduction / Context: Database triggers can enforce business rules and maintain audit trails. Administrators sometimes need to enable or disable all triggers on a table—for example, during bulk loads or maintenance. This question checks the correct SQL statement typically used for that task. Given Data / Assumptions: A relational database with tables that may have multiple triggers. The intention is to enable or disable all triggers on one table in a single statement. Vendor syntax varies, but the widely recognized form uses ALTER TABLE. Concept / Approach: Common implementations (e.g., Oracle) use statements such as: ALTER TABLE table_name DISABLE ALL TRIGGERS or ALTER TABLE table_name ENABLE ALL TRIGGERS. The controlling verb is ALTER TABLE, not a separate ‘‘ALTER TRIGGERS’’ object. Step-by-Step Solution: Identify the administrative goal: enable/disable triggers.Recall standard DDL control for table-level trigger state.Select ‘‘ALTER TABLE’’ as the correct statement family. Verification / Alternative check: Database documentation typically shows ENABLE/DISABLE trigger operations under ALTER TABLE semantics; there is no general SQL standard ‘‘ALTER TRIGGERS’’ statement operating at table scope. Why Other Options Are Wrong: ALTER TRIGGERS: not a standard DDL command for batch-enabling/disabling at table scope. MODIFY TRIGGERS IN TABLE: not valid SQL syntax. All of the above: false because only ALTER TABLE is correct. None of the above: incorrect, since ALTER TABLE is correct. Common Pitfalls: Assuming a non-standard verb exists; in practice, manage trigger state through ALTER TABLE with vendor-specific clauses. Final Answer: ALTER TABLE

Question 19

What is the term for a database management system designed to manage full-text, image, audio, and video—beyond strictly structured numeric/text fields?

Accepted Answer

Introduction / Context: Modern applications often store and query rich content—documents, images, audio, and video—rather than only simple rows of numbers and short strings. Database systems that support these formats are referred to as multimedia database management systems. Given Data / Assumptions: Storage and retrieval targets include full text, images, and streams (audio/video). Queries may involve metadata, content-based retrieval (e.g., by tags), and large object storage. The question seeks the common umbrella term for such systems. Concept / Approach: A ‘‘multimedia’’ DBMS supports BLOB/CLOB types, indexing on media metadata, and sometimes content-aware search (thumbnails, waveforms, transcripts). While ‘‘hypertext’’ refers to linked documents, and ‘‘graphics media’’ is too narrow, ‘‘multimedia’’ captures the full range of rich data types. Step-by-Step Solution: Recognize the multimodal data types (text, image, audio, video).Identify the industry term for DBMS handling these: multimedia.Choose ‘‘Multimedia’’ from the options. Verification / Alternative check: Vendor documentation typically labels support for BLOBs, media streaming, and media indexing under multimedia capabilities. Why Other Options Are Wrong: Hypertext: focuses on linking documents via anchors/URLs. Graphics media: implies images/graphics only. Full media: not a standard term. None of the above: incorrect because ‘‘Multimedia’’ is correct. Common Pitfalls: Confusing document-linking technologies (hypertext) with comprehensive media storage and retrieval. Final Answer: Multimedia

Question 20

In file organization terminology, a collection of related records that is treated as one unit is called what?

Accepted Answer

Introduction / Context: Classic file systems and many data-processing workflows use a hierarchy: fields form records, and records are grouped into files. Understanding these terms is foundational to database and storage concepts. Given Data / Assumptions: A ‘‘record’’ is a set of fields describing one entity instance (e.g., one customer). Many records combine to form a single higher-level container. The question asks for the name of that container unit. Concept / Approach: The standard term for a group of related records treated as one unit is a file. Files are named containers used for storage, backup, transfer, and processing steps. Step-by-Step Solution: Recall the hierarchy: fields → records → files.Identify the unit that holds multiple records: file.Select ‘‘File’’ as the correct term. Verification / Alternative check: Operating systems and ETL tools operate on files (not individual records) as the basic unit for moving and processing large sets of data. Why Other Options Are Wrong: Batch: usually a set of jobs or a processing mode, not the data container itself. Field: a component within a record, too granular. Data (generic): not a specific container term. Common Pitfalls: Equating ‘‘batch’’ (job control concept) with the data grouping; here the precise data container is a file. Final Answer: File

Database Systems Questions