This is because link analysis is a type of analysis that determines whether the data being analyzed is
connected to other datapoints, such as entities, events, or relationships. Link analysis can be used to
identify and visualize the patterns, networks, or associations among the datapoints, as well as
measure the strength, direction, or frequency of the connections. For example, link analysis can be
used to determine if there is a connection between a customer’s purchase history and their loyalty
program status. The other types of analysis are not the best types of analysis to conduct to
determine whether the data being analyzed is connected to other datapoints. Here is why:
Trend analysis is a type of analysis that determines whether the data being analyzed is changing over
time, such as increasing, decreasing, or fluctuating. Trend analysis can be used to identify and
visualize the patterns, cycles, or movements in the data points, as well as measure the rate,
direction, or magnitude of the changes. For example, trend analysis can be used to determine if
there is a change in a company’s sales revenue over a period of time.
Performance analysis is a type of analysis that determines whether the data being analyzed is
meeting certain goals or objectives, such as targets, benchmarks, or standards. Performance analysis
can be used to identify and visualize the gaps, deviations, or variations in the data points, as well as
measure the efficiency, effectiveness, or quality of the outcomes. For example, performance analysis
can be used to determine if there is a gap between a student’s test score and their expected score
based on their previous performance.
Exploratory analysis is a type of analysis that determines whether there are any insights or
discoveries in the data being analyzed, such as patterns, relationships, or anomalies. Exploratory
analysis can be used to identify and visualize the characteristics, features, or behaviors of the data
points, as well as measure their distribution, frequency, or correlation. For example, exploratory
analysis can be used to determine if there are any outliers or unusual values in a dataset.