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AIOps-Foundation Latest Exam Questions | AIOps-Foundation Pdf Demo Download

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Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q40-Q45):

NEW QUESTION # 40
At which stage does the data pipeline deduplicate data?

A. Extraction/collection
B. Cleaning/integration
C. Enrichment/filtering
D. Storage

Answer: B

Explanation:
In a data pipeline, deduplication occurs during the cleaning and integration stage. This process involves identifying and removing duplicate records to ensure data quality and accuracy. By eliminating redundancies, organizations can maintain a single source of truth, leading to morereliable analytics and decision-making.
The DevOps Institute's AIOps Foundation course underscores the importance of data cleaning and integration in preparing data for effective analysis and operational use.

NEW QUESTION # 41
Which definition BEST describes Big Data?

A. Data sets that are so large they can only be interrogated using Al
B. Data sets that are "too large" or diverse causing traditional data processing techniques to be ineffective
C. Data sets thatlive in data warehouses or lakes
D. Data sets of structured data that have grown over time

Answer: B

Explanation:
Big Data refers to data sets that are so large, fast, or complex that traditional data processing methods are inadequate to handle them. This concept is characterized by the Five V's:
* Volume: The sheer amount of data generated.
* Velocity: The speed at which new data is produced and needs to be processed.
* Variety: The different types of data (structured, unstructured, semi-structured).
* Veracity: The quality and accuracy of the data.
* Value: The usefulness of the data for decision-making.
In the context of AIOps, understanding Big Data is crucial as it involves combining big data analytics with machine learning algorithms to enhance IT operations.

NEW QUESTION # 42
Discovering unexpected changes in system behavior or performance is satisfied by this use case:

A. Root cause analysis
B. Event correlation
C. Anomaly detection
D. Alert noise reduction

Answer: C

Explanation:
Anomaly detectionrefers to identifying unexpected changes or deviations in system behavior or performance.
This use case is essential for proactively detecting issues that may not have predefined patterns or signatures, enabling faster incident resolution.
The DevOps Institute's AIOps Foundation materials describe anomaly detection as a key feature of AIOps platforms to enhance monitoring capabilities.

NEW QUESTION # 43
What is the meaning of Digital Transformation?

A. Adoption of digital technologies for accelerated Innovation and improved customer experience
B. Replacing all human operators with artificial Intelligence
C. Replacing all analog systems with digital equivalents
D. Refactoring all software to a newer technology stack

Answer: A

Explanation:
Digital Transformation refers to the strategic adoption of digital technologies to fundamentally change how organizations operate, deliver value to customers, and foster innovation.
It is not about simply replacing analog systems or eliminating human operators but integrating technology to improve efficiency, decision-making, and customer satisfaction.
DevOps Institute defines it as leveraging tools, automation, and cultural shifts to enable faster and more effective innovation cycles.
References highlight improved agility, scalability, and customer-focused outcomes as key objectives of Digital Transformation.

NEW QUESTION # 44
The effectiveness of an AlOps implementation is dependent on what performances?

A. System complexity
B. Machine Learning Model Performance
C. Number of data sources
D. In-houseAl skills

Answer: B

Explanation:
The effectiveness of an AIOps implementation is significantly influenced by the performance of its machine learning (ML) models. These models are central to analyzing vast amounts of data, identifying patterns, and making predictions that enhance IT operations. Key factors include:
* Accuracy: The precision of the ML model in identifying and predicting issues directly impacts the reliability of the AIOps system.
* Training Data Quality: High-quality, relevant data is essential for training effective ML models.
* Model Adaptability: The ability of the model to adapt to new data and evolving system behaviors ensures sustained effectiveness.
Therefore, optimizing machine learning model performance is crucial for a successful AIOps deployment.

NEW QUESTION # 45
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