The Dynamic Host Configuration Protocol (DHCP) is a network management protocol used on TCP/IP networks to automate the assignment of IP addresses and other communication parameters to devices. A DHCP server maintains a pool of IP addresses and leases them to clients as they join the network. This process includes assigning an address, managing the lease duration, and reclaiming the address for reuse once the lease expires or the client disconnects. This functionality precisely matches the requirements of assigning, managing, and reclaiming IP addresses as stated in the question.

A. DNS: The Domain Name System (DNS) translates human-readable domain names (e.g., www.example.com) into machine-readable IP addresses but does not assign or manage the IP addresses for host configuration.

C. LDAP: The Lightweight Directory Access Protocol (LDAP) is an application protocol for accessing and maintaining distributed directory information services, typically used for user authentication and authorization, not IP address allocation.

D. ISMTP: This is not a recognized standard protocol. The standard protocol for email is SMTP (Simple Mail Transfer Protocol), which is responsible for sending and receiving email, not IP address management.

---

1. Droms

R. (1997). RFC 2131: Dynamic Host Configuration Protocol. Internet Engineering Task Force (IETF). In Section 1

"Introduction

" the document states

"The Dynamic Host Configuration Protocol (DHCP) provides a framework for passing configuration information to hosts on a TCP/IP network. DHCP is based on the Bootstrap Protocol (BOOTP)

adding the capability of automatic allocation of reusable network addresses and additional configuration options." Available at: https://doi.org/10.17487/RFC2131

2. Stallings

W. (2016). Foundations of Modern Networking: SDN

NFV

and Cloud Computing. Pearson Education. In Chapter 5

Section 5.2 "The Internet Protocol

" the text describes DHCP's role: "DHCP automates the assignment of IP addresses

saving network administrators the effort of manual configuration... The protocol also provides for on-demand assignment of IP addresses and the automatic return of an address to the pool for reuse."

3. University of California

Berkeley

EECS 122 Course Materials. "Lecture 15: IP Addressing (CIDR

NAT

DHCP)." The lecture notes explain that DHCP is the standard mechanism for a host to automatically obtain an IP address

subnet mask

and default gateway from a server.

4. Mockapetris

P. (1987). RFC 1034: Domain Names - Concepts and Facilities. Internet Engineering Task Force (IETF). Section 2.1

"Name space

" defines the purpose of DNS as a hierarchical naming system

which is distinct from IP address assignment. Available at: https://doi.org/10.17487/RFC1034

The most reliable and direct method for a database administrator to verify that scheduled backups are occurring as planned is to review the server logs. Backup utilities and database management systems generate detailed log entries for each operation. These logs record the exact start and end times, the success or failure status of the job, and any errors or warnings encountered. This information directly confirms whether the backups are running daily and at the scheduled times, fulfilling the administrator's requirement.

A. Query the database to observe entries.

This action verifies data activity within the database but does not confirm that an external backup operation has been successfully performed.

B. Check the database schema.

The schema defines the logical structure of the database (tables, columns, etc.) and contains no information about operational tasks like backups.

C. Review the backup media.

While this can confirm the existence of backup files, it is less direct than logs and may not provide crucial details about job success, completion time, or errors.

1. Microsoft SQL Server Documentation: In SQL Server

the status of scheduled backup jobs is recorded in the SQL Server Agent job history. The official documentation states

"You can monitor SQL Server Agent jobs from the Job Activity Monitor... You can also view the history for an individual job." This history is a form of server log.

Source: Microsoft Docs

"Monitor Job Activity". Section: "To view the history for an individual job".

2. Oracle Database Documentation: Oracle's Recovery Manager (RMAN) is the standard tool for backups. Its operations are logged. The documentation advises

"The primary sources of information about RMAN jobs are the RMAN output and the V$RMANBACKUPJOBDETAILS view... RMAN also records its actions in the control file of the target database." The database alert log also records the start and completion of RMAN jobs.

Source: Oracle Database Backup and Recovery User's Guide

19c. Chapter 14

"Monitoring RMAN Jobs and Sessions".

3. PostgreSQL Documentation: For PostgreSQL

backups are often performed using external scripts (e.g.

running pgdump) scheduled with a utility like cron. The standard practice is to log the output of these scripts. The PostgreSQL documentation on server administration notes the importance of logging: "There are many situations in which it is desirable to log server activity... This information can be invaluable for auditing and forensic analysis." This principle applies directly to auditing backup job execution.

Source: PostgreSQL 14 Documentation. Chapter 20

"Server Setup and Operation"

Section 20.8

"Error Reporting and Logging".

The SQL statement in option B, Select EmpId where EmpId=90030 and DeptId=34, contains a syntax error. A valid SELECT statement that retrieves data from a table must include a FROM clause to specify the source table. This statement is missing the FROM clause, making it syntactically incorrect and unexecutable by any standard SQL database management system. The basic structure of a query requires specifying what to select (SELECT), from where to select it (FROM), and optionally, the conditions for selection (WHERE).

A. This is a valid SQL query. It correctly uses the SELECT, FROM, and WHERE clauses to retrieve a specific employee's ID from the employee table.

C. This is a valid SQL query. The asterisk () is a wildcard that correctly selects all columns from the employee table for the specified EmpId.

D. This is a valid SQL query. It correctly uses the SELECT and FROM clauses to retrieve all values from the EmpId column in the employee table.

1. Ullman

J. D.

& Widom

J. (n.d.). CS145 Introduction to Databases

Class Notes on SQL. Stanford University. Retrieved from https://infolab.stanford.edu/~ullman/fcdb/slides/slides-sql1.pdf. On page 4

the basic form of an SQL query is defined as SELECT FROM WHERE

explicitly showing the FROM clause as a required component.

2. PostgreSQL Documentation. (n.d.). 7.1. Overview. In PostgreSQL 16 Documentation. Retrieved from https://www.postgresql.org/docs/current/tutorial-select.html. The introductory example SELECT FROM weather; and subsequent explanations establish the FROM clause as fundamental for specifying the target table.

3. Stonebraker

M.

& Hellerstein

J. (2005). 8. Relational Algebra and SQL. In 6.830 Database Systems

Fall 2005. Massachusetts Institute of Technology: MIT OpenCourseWare. Retrieved from https://ocw.mit.edu/courses/6-830-database-systems-fall-2005/resources/lec8/. Slide 20 presents the canonical SELECT-FROM-WHERE statement

reinforcing the necessity of the FROM clause.

Protecting physical database appliances from damage within a server room primarily involves mitigating environmental threats. Overheating is a significant risk to electronic components, and cooling systems (e.g., HVAC, CRAC units) are essential for maintaining an optimal operating temperature, thereby preventing thermal damage and ensuring hardware longevity. Fire is another catastrophic threat; fire suppression systems (such as clean agent or pre-action sprinkler systems) are designed to extinguish fires quickly without damaging the electronic equipment, directly protecting the appliances from destruction.

A. Biometric access systems: This is a physical access control measure to prevent unauthorized personnel entry, not to protect against environmental damage like fire or heat.

B. Database control systems: These are software-based tools for managing database access and operations (logical security), which do not protect the physical hardware appliance.

D. Camera systems: Cameras are a detective and deterrent control for surveillance purposes; they record events but do not actively prevent physical damage from environmental hazards.

E. Key card systems: Like biometrics, this is a physical access control mechanism that restricts entry but offers no protection against environmental threats such as overheating.

1. National Institute of Standards and Technology (NIST). (2020). Security and Privacy Controls for Information Systems and Organizations (Special Publication 800-53

Revision 5).

Control PE-13 (Fire Protection): This control explicitly details the requirement for fire protection measures

including detection and suppression systems

to "prevent and mitigate damage to the system and facility." (Page 298).

Control PE-14 (Temperature and Humidity Controls): This control mandates maintaining temperature and humidity levels "within acceptable levels for the system" to prevent physical damage from environmental conditions. (Page 299).

DOI: https://doi.org/10.6028/NIST.SP.800-53r5

2. Massachusetts Institute of Technology (MIT) Information Systems and Technology (IS&T). (n.d.). Secure Hosting Environment.

The documentation for MIT's secure data center environment explicitly lists "Temperature and humidity controlled environment" and "Fire detection and suppression systems" as key features for protecting hosted equipment. This demonstrates the university-level best practice for physical hardware protection. (Section: "Features").

3. Stanford University IT. (n.d.). Data Center Services.

Stanford's description of its data center facilities highlights "Environmental Controls" as a core service

which includes "temperature and humidity monitoring" and "fire suppression systems" to ensure the physical safety and operational integrity of server hardware. (Section: "Features").

Object storage is a data storage architecture that manages data as distinct units called objects. It is designed to be accessed programmatically over a network using HTTP-based protocols. The primary interface for interacting with object storage systems, such as Amazon S3 or Azure Blob Storage, is a RESTful (Representational State Transfer) API. This allows users and applications to perform create, read, update, and delete (CRUD) operations on data objects using standard HTTP verbs (e.g., GET, PUT, POST, DELETE) directed at specific API endpoints, making it ideal for cloud-native applications.

A. Network file: This storage is accessed using network file-sharing protocols like NFS or SMB, which present a hierarchical file system, not a REST API for data retrieval.

C. Ephemeral: This describes the non-persistent nature of storage (it is lost when an instance stops), not its access method. It is typically a form of block storage.

D. iBlock: This refers to block storage, which is presented to an operating system as a raw disk volume and is accessed via protocols like iSCSI, not a REST API.

1. Amazon Web Services (AWS) Documentation: In the Amazon S3 User Guide

the section "How Amazon S3 works" explicitly states

"Amazon S3 is an object storage service... You can access your data through the Amazon S3 console

AWS SDKs

or the Amazon S3 REST API." This confirms that object storage uses a REST API.

Source: Amazon S3 User Guide

"What is Amazon S3? -> How Amazon S3 works".

2. Microsoft Azure Documentation: The documentation for Azure's object storage solution states

"Azure Blob storage is Microsoft's object storage solution for the cloud... Access objects from anywhere in the world via HTTP or HTTPS. Developers can use the Blob storage REST API or an Azure SDK to write code."

Source: Microsoft Azure Docs

"Introduction to Azure Blob storage -> Blob storage resources -> Blob storage REST API".

3. University of California

Berkeley Courseware: In the lecture notes for CS 162: Operating Systems and Systems Programming

the distinction between storage types is made clear. Object stores like S3 are described as having a "put/get/delete interface (REST API)

" contrasting with block storage (like EBS) and file storage (like NFS).

Source: UC Berkeley

EECS

CS 162

Lecture 22: "Cloud Computing"

Slide 34

"Cloud Storage: Object Stores".

4. Armbrust

M.

et al. (2010). A view of cloud computing. Communications of the ACM

53(4)

50-58. This foundational academic paper on cloud computing discusses storage systems

identifying services like Amazon S3 as providing "a bucket-based storage system with a REST API."

DOI: https://doi.org/10.1145/1721654.1721672

Section 3.1

Paragraph 3.

An Entity-Relationship Diagram (ERD) is a graphical representation of a database's logical structure. It illustrates the entities (tables), their attributes (columns), and the relationships between them, including cardinality and keys. When considering denormalization—a process that involves intentionally combining tables to improve query performance—the ERD is the essential document. It provides the clear, high-level structural overview required to analyze existing relationships and identify which tables are suitable candidates for merging. Understanding these inter-entity connections is fundamental to planning any structural modification like denormalization.

A. SOP: A Standard Operating Procedure (SOP) outlines the steps to perform a task; it does not describe the database's architecture or data relationships.

B. Data dictionaries: A data dictionary is a repository of metadata, providing detailed information about data elements like types and constraints, but it lacks the visual, relational overview of an ERD for structural analysis.

C. UML diagrams: While Unified Modeling Language (UML) can be used for data modeling, the ERD is the specific, industry-standard artifact for designing and analyzing relational database structures.

1. Silberschatz

A.

Korth

H. F.

& Sudarshan

S. (2020). Database System Concepts (7th ed.). McGraw-Hill.

Chapter 7

Section 7.1

"Overview of the Design Process

" p. 269: "The E-R data model is most relevant to the database-design process. It provides useful concepts that allow a database designer to move from an informal description... to a more detailed

and precise

description that can be implemented... The E-R modeling technique is a graphical one

and E-R diagrams are used to represent the logical structure of a database." This establishes the ERD as the primary tool for representing and analyzing the logical structure.

2. Elmasri

R.

& Navathe

S. B. (2017). Fundamentals of Database Systems (7th ed.). Pearson.

Chapter 7

Section 7.1

"Using High-Level Conceptual Data Models for Database Design

" p. 204: "The ER model is a popular high-level conceptual data model. This model and its variations are frequently used for the conceptual design of database applications

and many database design tools employ its concepts." This confirms the ERD's role as the standard for conceptual design and analysis.

3. Ullman

J. D.

& Widom

J. (2008). A First Course in Database Systems (3rd ed.). Pearson Prentice Hall.

Chapter 4

"The Entity-Relationship Model

" p. 113: "The E/R model is a design tool that is independent of the particular DBMS in which the database will be implemented... The E/R model allows us to draw pictures of the 'real world' that the database will model." This highlights its function as a design and analysis tool for database structure.

A UML (Unified Modeling Language) editor is the best tool for this task. UML is a standardized modeling language used to visualize, specify, construct, and document the artifacts of a system. A database administrator can use a UML editor to create Class Diagrams or Entity-Relationship Diagrams (ERDs). These diagrams provide a clear, visual representation of the database entities (tables), their attributes (columns), and the relationships between them (e.g., one-to-one, one-to-many), including cardinality and constraints. This visual format is highly effective for documenting and explaining complex data structures to both technical and non-technical stakeholders.

A. Text editor: Lacks specialized features for creating visual diagrams or enforcing modeling standards, making it inefficient and error-prone for documenting complex data relationships.

C. Word processor: While it can embed diagrams, it is not a primary tool for creating or managing the underlying structure of data models and their relationships.

D. SQL query: Interacts with and defines the database schema but does not produce the high-level, visual, and explanatory documentation required to explain relationships effectively.

1. Object Management Group (OMG). OMG Unified Modeling Language (OMG UML)

Version 2.5.1. (2017). Section 11.4

"Classifiers

" and Section 11.5

"Associations

" describe the components of Class Diagrams

which are standard for modeling entities

their attributes

and the relationships between them

directly mapping to database schema concepts.

2. Elmasri

R.

& Navathe

S. B. Fundamentals of Database Systems

7th Edition. (2016). Pearson. Appendix A

"Alternative Diagrammatic Notations

" discusses the use of UML class diagrams for database schema design

noting their suitability for representing entities (as classes) and relationships (as associations).

3. Blaha

M. "UML for Database Design." In UML for the IT Business Analyst (2nd ed.

pp. 111-132). (2016). Technics Publications. This chapter details the practical application of UML class models for designing and documenting relational databases

highlighting its superiority over less formal methods. (DOI: 10.1201/b10861-8)

The Recovery Point Objective (RPO) is a business continuity metric that defines the maximum acceptable age of data that must be recovered for normal operations to resume after a disaster. It essentially answers the question, "What is the maximum amount of data, measured in time, that we can afford to lose?" For example, an RPO of one hour means that in the event of a disaster, the system must be restorable to a point in time no more than one hour before the incident occurred. This directly corresponds to the "age requirement for data."

A. MTBF: Mean Time Between Failures (MTBF) is a reliability metric predicting the average time a repairable system will operate before a failure occurs. It does not relate to data recovery age.

B. RTO: Recovery Time Objective (RTO) specifies the maximum tolerable duration of downtime for a system or service. It is about how quickly to recover, not the age of the recovered data.

C. MTTF: Mean Time To Failure (MTTF) is a reliability metric for non-repairable components, indicating their average lifespan. It is not a disaster recovery data requirement.

1. National Institute of Standards and Technology (NIST). (2010). Special Publication 800-34 Rev. 1

Contingency Planning Guide for Federal Information Systems. Page G-4

Appendix G.

The document defines RPO as: "The point in time to which data must be recovered after an outage." It defines RTO as: "The maximum amount of time that a system can be down before it needs to be restored."

2. Microsoft Corporation. (2023). Business continuity and disaster recovery (BCDR): Azure Paired Regions. Microsoft Azure Documentation.

Under the section "BCDR terminology

" it states: "Recovery Point Objective (RPO) is the maximum duration of data loss that is tolerable." This directly links RPO to the age and potential loss of data.

3. University of California

Berkeley. (n.d.). Disaster Recovery and Business Continuity. Information Security Office.

In its glossary

the university defines RPO as: "The maximum acceptable amount of data loss after an unplanned incident

expressed as an amount of time." This confirms RPO as the metric for data age requirements.

A unique index is a database constraint that ensures all values in the indexed column or columns are distinct. When a unique index is applied to a table, the database management system (DBMS) automatically rejects any INSERT or UPDATE operation that would create a duplicate value in the specified column(s). This directly enforces the developer's requirement to prevent repeated values, thereby maintaining data integrity.

B. Single column: This describes an index based on one column, which can be either unique or non-unique. It does not inherently prevent duplicates.

C. Implicit: This refers to an index created automatically by the DBMS, typically for a primary key or unique constraint, not the type of constraint itself.

D. Composite: This describes an index that includes multiple columns. A composite index can be unique, but its primary definition is its multi-column structure, not its uniqueness property.

1. Oracle Database Concepts

21c

Chapter 4: Schema Objects

Section: "Unique and Nonunique Indexes". The documentation states

"A unique index guarantees that no two rows of a table have duplicate values in the key column or columns."

2. PostgreSQL 16 Documentation

Chapter 11: Indexes

Section 11.7: "Unique Indexes". The documentation specifies

"Indexes can also be used to enforce uniqueness of column values... A unique index prevents duplicate values from being entered into the table."

3. Microsoft SQL Server Documentation

"Create Unique Indexes". The guide states

"A unique index ensures that the index key contains no duplicate values and therefore every row in the table is in some way unique."

4. Ramakrishnan

R.

& Gehrke

J. (2003). Database Management Systems (3rd ed.). In Chapter 8

"Storage and Indexing

" the concept of unique indexes is introduced as a mechanism to enforce uniqueness constraints efficiently. (This is a standard university textbook for database courses).

A data retention policy is a set of established rules that dictates how long specific types of information must be kept and the procedures for its eventual disposal. The scenario describes a classic example of such a policy: court files (a type of data) must be stored for a specific period (ten years) and then follow a disposition process (be discarded). This policy ensures compliance with legal, regulatory, or business requirements for record-keeping. The scanning for permanent reference and the defined storage duration are core components of managing the data lifecycle according to a retention policy.

A. Data loss prevention: This focuses on preventing the unauthorized exfiltration, destruction, or leakage of data, not on defining the required storage duration for compliance or business needs.

C. Data classification: This is the process of categorizing data based on its sensitivity (e.g., public, confidential). While classification informs retention rules, it is not the policy that defines the storage timeline itself.

D. Global regulations: While regulations (which may or may not be global) often mandate retention periods, the concept that directly applies to the implementation of these rules within an organization is the data retention policy.

1. ISO 15489-1:2016

Information and documentation — Records management — Part 1: Concepts and principles. Section 9.2

"Retention and disposition

" specifies that processes should be established to determine the length of time records are to be kept to meet business

legal

and other requirements. This directly describes the function of a data retention policy.

2. National Institute of Standards and Technology (NIST) Special Publication 800-88 Rev. 1

Guidelines for Media Sanitization. Section 2.2

"Data Disposition

" states

"The decision to dispose of information is based on the organization’s records retention schedule... A records retention schedule details how long information should be retained based on a classification scheme and identifies the final disposition of the information (e.g.

transfer or destruction)."

3. Cornell University

University Policy 5.4.2

Data Retention. The policy states

"University data must be retained for specific periods of time to comply with legal

audit

and other university requirements... At the end of the required retention period

the data must be disposed of in a secure manner." This university policy document exemplifies the concept in practice.