...
Horizontal axis (x): This axis represents time, generally divided into regular intervals, depending on the chosen observation period.
Vertical axis (y): This axis represents the throughput.
Trend line: This allows you to visualize the evolution of the flow rate over time, whether it is an increase, a decrease or a regular variation.
Key points to observe:
Spikes (high flow values): If the flow suddenly increases, this may indicate a period of high activity or peak demand.
Dips (low throughput values): Sudden drops may signal reduced activity or a performance issue (such as overload or slowdown).
Plateaus: If the flow line is relatively stable, this means that the system is maintaining a constant flow rate, which can be interpreted as a good sign of stability, unless the plateau is at low flow levels, which could indicate a problem.Utilité dans WiveezFlow Analytics Pro
The Throughput Run Chart in Wiveez Flow Analytics Pro allows users to:
Monitor performance in real time: By continuously observing throughput, users can quickly respond to performance variations and adjust resources accordingly.
Diagnose problems: Quickly identifying spikes or dips in throughput helps locate bottlenecks or periods of overload in a system.
Predict future trends: By studying the evolution of flow rates over a long period of time, users can anticipate future resource needs or prepare adjustments to maintain optimal flow.
...
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.
...
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.
...
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.
...
Analyze with our AI Alice
Wiveez Flow Analytics Pro provides you with its AI, named Alice, to help you analyze graphs.
...