CITM Exam Dumps - EXIN EPI Certified Information Technology Manager

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.

In corporate hiring protocols,additional screeningtypically refers to background checks beyond basic qualifications, such as verifying a candidate’scriminal record. This is critical for IT roles, where employees may have access to sensitive systems and data, ensuring trustworthiness and compliance with security policies.

Salary demands (A) are negotiated during the hiring process, not screened. Number of years of experience (B) and educational level (D) are verified through resumes and standard checks, not typically classified as “additional screening,” which focuses on security-related checks like criminal records.

Concerns about future price increases can be addressed byincluding contractual terms(B) in the agreement to limit or regulate price escalations (e.g., fixed pricing, escalation clauses, or review mechanisms). This approach balances the business units’ insistence on proceeding with the selected vendor (based on a thorough evaluation) while mitigating financial risks. According tovendor management best practices, contracts should include clear terms to protect against unforeseen cost increases, ensuring alignment with business objectives.

Ignore the business units and change vendor (A):Contradicts the evaluation process and business units’ decision, risking misalignment.

Sign the contract (C):Ignores the price increase concern, potentially exposing the organization to financial risk.

Re-tender the project (D):Unnecessary, as the vendor was selected through evaluation; contractual terms can address the concern without restarting the process.

To predict future customer purchases, the marketing department requiresadvanced analytics(B), which involves sophisticated data analysis techniques, such as predictive modeling, machine learning, and data mining. These technologies enable the department to analyze customer behavior, identify patterns, and forecast purchasing trends, supporting targeted advertising campaigns.

Records Management System (RMS) (A):Focuses on managing and storing records, not predictive analysis.

Ad hoc analysis (C):Allows for on-demand, one-off queries but lacks the predictive capabilities of advanced analytics.

Business Intelligence (BI) (D):Provides reporting and historical data analysis but is less focused on predictive modeling compared to advanced analytics.

Advanced analytics aligns withIT strategygoals of leveraging data for competitive advantage, as it supports predictive insights critical for marketing decisions.

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.

InITIL’s problem management process,poor registration of problems(A) is the most likely cause of low-quality problem resolution. Effective problem management requires accurate logging of incidents and problems, including detailed descriptions, to enable proper root cause analysis and resolution. If problems are poorly registered (e.g., incomplete or inaccurate data), it hinders diagnosis and resolution, leading to customer dissatisfaction.

Wrong allocation of problems (B):Incorrect assignment to teams can delay resolution but is less fundamental than poor registration, which affects the entire process.

Errors in priority (C):Incorrect prioritization may delay urgent issues, but poor registration impacts resolution quality more directly.

Lack of budget (D):May limit resources, but the scenario points to process quality, not resource constraints.

For amission-critical applicationin a financial institution requiring data to beinstantly available at two locations,synchronous replication(B) is recommended. Synchronous replication ensures that data is written to both the primary and secondary locations simultaneously, guaranteeing no data loss and immediate availability at both sites. This is critical for financial applications where data integrity and zero recovery point objective (RPO) are essential, as perbusiness continuityanddisaster recoveryframeworks likeISO 22301.

Instant replication (A):Not a standard term in replication strategies; likely a distractor.

Asynchronous replication (C):Data is replicated with a delay, risking data loss in case of failure, unsuitable for instant availability.

Semi-synchronous replication (D):A compromise where the primary site continues after the secondary acknowledges receipt, but it may not guarantee instant availability.

Synchronous replication ensures real-time data consistency, critical for financial systems.