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The Flow Histogram is a graph that represents the frequency of different flow values over a given interval. In other words, it indicates how many times a certain flow level was observed during a period or series of events.
In the context of WiveezFlow Analytics Pro, throughput can refer to a metric like the amount of data processed per unit of time, the number of successful transactions or events in a given system. The histogram helps visualize this data by grouping the observed flow values into different "slices".
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Of course ! The concept of Thin-Tailed and Fat-Tailed distributions is often used in risk analysis, statistics and finance to understand and model the impact of rare and extreme events. Here is a description that you could integrate into the Wiveez Flow Analytics Pro user documentation, adapted to explain their principle, their operation and their usefulness in this context.
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Thin-Tailed: A thin-tailed distribution is characterized by a relatively low probability that extreme events (or large deviations from the mean) will occur. In other words, extreme values (very far from the average) are rare. A typical example would be the normal (or Gaussian) distribution, where most of the data concentrates around the mean and extremes are very unlikely.
Fat-Tailed: In contrast, a fat-tailed distribution has a higher probability of extreme events. This means that rare (but very impactful) events are more frequent than would be expected with a thin-tailed distribution. Fat-tailed distributions are used to model phenomena where extreme events have a disproportionate impact, such as stock market crashes or economic crises.
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Detailed ticket analysis
Wiveez Flow Analytics Pro allows the user to analyze the performance of each flow in detail by displaying the list of tickets associated with a column and displaying the details of the Flow Metrics of a ticket.
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Analyze with our AI Alice
Wiveez Flow Analytics Pro provides you with its AI, named Alice, to help you analyze graphs.
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