300-445 Question 174
Single answerAn enterprise network operations team is tasked with analyzing network performance data to identify trends and potential bottlenecks. They decide to use machine learning-based analytics tools to process the data collected from multiple sources such as SNMP, Syslog, and NetFlow. Which of the following types of data analysis would be most appropriate for identifying patterns and predicting future network congestion?
- A
Descriptive analysis
- B
Prescriptive analysis
- C
Diagnostic analysis
- D
Predictive analysis
Show answer and explanation
Correct answer: D
Explanation
Predictive analysis is the most appropriate method for identifying patterns and predicting future events such as network congestion. It leverages machine learning models and historical data to forecast potential issues, which is essential for proactive network assurance in enterprise environments.
- A. Incorrect.
Descriptive analysis focuses on summarizing historical data and providing insights into past events, but it does not identify patterns or predict future outcomes.
- B. Incorrect.
Prescriptive analysis provides recommendations for actions based on data, but it is not specifically designed to identify patterns or predict future trends.
- C. Incorrect.
Diagnostic analysis focuses on identifying the root cause of past issues, but it does not help in predicting future network performance or congestion.
- D. Correct.
Predictive analysis uses historical data and machine learning to identify patterns and trends, enabling the prediction of future events such as network congestion.