Pass the Exin EPI IT Management CITM Questions and answers with CertsForce

Alessons learned reportin project management is designed to document both positive and negative experiences from a project to improve future projects. According to theProject Management Institute (PMI)and frameworks like PMBOK, the purpose is to capture insights, successes, challenges, and recommendations to enhance processes, avoid repeating mistakes, and replicate successes in future initiatives.

Option A focuses only on reporting achievements, which is too narrow. Option B emphasizes accountability for mistakes, which is not the primary goal, as the report aims to improve rather thanblame. Option C is incorrect because identifying risks is part of risk management, not the primary focus of lessons learned. Option D correctly captures the intent to benefit future projects by analyzing both positive and negative aspects.

The customer’s focus on incorporatingfuture functional requirementsindicates a need forperfective maintenance(B). Inapplication management, perfective maintenance involves enhancing software to add new features or improve functionality to meet evolving business needs, such as adding new modules or capabilities.

Preventive maintenance (A):Focuses on preventing issues by optimizing performance or addressing potential problems, not adding new features.

Corrective maintenance (C):Involves fixing bugs or errors, not incorporating new functionality.

Adaptive maintenance (D):Adapts software to environmental changes (e.g., new operating systems), not specifically for new functional requirements.

Perfective maintenance aligns with theSDLC’s maintenance phase, ensuring the software evolves to support future business requirements.

To reduce the risk of fraud in large financial transactions, the security principle ofintegrity(C) requires the highest attention.Integrity, as perISO/IEC 27001’s CIA triad (Confidentiality, Integrity, Availability), ensures that data is accurate, complete, and unaltered. Fraud often involves manipulating transaction data, so controls like data validation, checksums, or audit trails are critical to maintain integrity and prevent unauthorized changes.

Confidentiality (A):Protects data from unauthorized access, less directly related to fraud prevention.

Availability (B):Ensures system access, not the primary concern for fraud.

Reliability (D):Not a standard CIA triad principle; may relate to system performance but not fraud.

Aparallel test(A) in business continuity planning involves running systems at both the primary and alternate sites simultaneously to compare data and ensure the alternate site can handle operations effectively. This test verifies data replication and system functionality without interrupting normal operations, aligning with the managers’ desire to compare data before a full interruption test.

Simulation test (B):This involves simulating a disaster scenario to test response procedures without activating the alternate site, so it doesn’t focus on data comparison.

Structured walk-through test (C):This is a tabletop exercise where team members discuss and review the plan without executing systems or comparing data.

Checklist test (D):This involves reviewing the business continuity plan against a checklist to ensure completeness, not comparing data between sites.

According toISO 22301orbusiness continuity managementframeworks, a parallel test is used to validate recovery capabilities while maintaining operations at the primary site, making it ideal for the scenario described.

AnSLA’s section onestimated system response timesfocuses on ensuring the system meets performance expectations. Key factors for successful delivery include:

Technical specifications of the system (A):Defines the system’s capabilities (e.g., processing power, architecture) critical for response times.

Skills and knowledge of staff (C):Ensures the IT team can manage and optimize the system for performance.

Technical specifications of the IT infrastructure (D):Includes network, servers, and storage, which directly impact response times.

Price for the IT service (B)is not a direct factor in achieving system response times, as it relates to cost negotiation rather than technical performance. While budget may influence resource allocation, it’s not a key factor in delivering the SLA’s performance metrics.

In theSoftware Development Life Cycle (SDLC), thedevelopment phasetypically includescode writing(A),testing(B), anddocumenting(C) to build and verify the software.Implementation(D) is part of thedeployment phase, where the software is installed and made operational in the production environment, not part of development.

Requests for password resets from unknown individuals suggestsocial engineeringattacks, such as phishing or impersonation, where attackers manipulate users to gain unauthorized access. An information security awareness program should focus on educating staff about social engineering tactics to recognize and prevent such incidents.

E-mail usage (A), instant messaging (B), and internet usage (C) may be vectors for attacks, but the core issue is social engineering, which encompasses tactics used across these channels.

Inrisk management, theAnnual Loss Expectancy (ALE)is calculated as:

ALE = Single Loss Expectancy (SLE) × Annualized Rate of Occurrence (ARO), whereSLE = Asset Value × Exposure Factor (EF).

Given:

Asset Value = $200,000

Exposure Factor (EF) = 25% = 0.25

ALE = $100,000

Calculate SLE:

SLE = Asset Value × EF = $200,000 × 0.25 = $50,000

Calculate ARO:

ALE = SLE × ARO

$100,000 = $50,000 × ARO

ARO = $100,000 ÷ $50,000 = 2

Thus, theAnnualized Rate of Occurrence (ARO)is2(C), meaning the incident is expected to occur twice per year.

0.4 (A):Incorrect; implies a lower frequency (0.4 times per year).

1 (B):Incorrect; would yield an ALE of $50,000, not $100,000.

The scenario describes a social media platform generating alarge volume of raw data(e.g., user interactions, multimedia content) and a need foradvanced analysisby the marketing department.Big Data Analysis(D) is the best technology, as it handles large, unstructured datasets and uses advanced techniques (e.g., machine learning, predictive analytics) to derive insights, such as user behavior or campaign effectiveness.

Master Data Management (MDM) (A):Focuses on managing core business data (e.g., customer records) for consistency, not analyzing large raw datasets.

Digital Asset Management (DAM) (B):Manages multimedia assets (e.g., images, videos) for storage and retrieval, not advanced analysis.

Online Analytical Processing (OLAP) (C):Supports multidimensional analysis of structured data but is less suited for unstructured, large-scale social media data compared to big data tools.

Big Data Analysis aligns withIT strategyfor leveraging large datasets to drive business value, as per modern data management frameworks.

Given the constraints oflittle to no budgetandlimited time,internet job boardsare the ideal sourcing method. They are cost-effective (often free or low-cost), allow quick posting of job openings, and reach a wide pool of candidates, enabling rapid hiring.

Word of mouth (A) is informal and may not yield qualified candidates quickly. Internal IT staff based on SWOT analysis (B) is not a standard recruitment method and takes time to analyze. Recruitment agencies (D) are expensive and slower due to their processes, making them unsuitable for low-budget, urgent hiring.