We are happy to announce the immediate release of Disco 1.8.0!
This update to Disco adds a number of new functionalities, making your process analysis even more powerful and expressive. Rather than new features, though, the focus of this release is to further improve the performance, stability, and robustness of Disco, and to provide a reliable and even more capable platform for going forward.
Since we have reengineered the native integration of Disco from the ground up, this update cannot be installed automatically. Please go to fluxicon.com/disco and download the updated installer package for your platform in order to install the Disco 1.8.0 update.
If you would like to learn more about the new features in Disco 1.8.0, and the changes we have made under the hood, please keep on reading.
Process Map Animation is one of the most popular features in Disco. If you need to quickly demonstrate the power of process mining to a colleague, your manager, or a client, there is no better way to get their attention than showing them a process map come to life.
But animation is not just a showy demo feature that is nice to look at. It provides a dynamic perspective that makes understanding bottlenecks and process changes much easier. Synchronized animation, a new feature in Disco 1.8.0, adds a new dimension of insight to animation.
Regular animation in Disco replays your event log data on the current model, just as it happened in your data. In contrast, synchronized animation starts to replay all cases in your data at the same time. This allows you analyze at what time into case execution the hot spots and bottlenecks in your process are most prominent, and to compare your process performance over the set of cases in your data.
You can choose between regular and synchronized animation by right-clicking the animation button in Disco’s process map view.
Improved Median Support
In Disco 1.6.0, we introduced support for the median, both in process map duration and in the statistics view. In many situations, the median (also known as the 50th percentile) gives you a much better idea of the typical characteristics of a process than the arithmetic mean, especially for data sets that contain extreme outliers.
While the median is very useful for analysis, it is quite demanding to determine, both in terms of computing power and regarding memory requirements. So far, we have used a very advanced technique to compute medians in Disco, which can estimate the value of the median with a very low error margin, while keeping the memory requirements very low. This is important, because Disco needs to compute a lot of medians at the same time (for example, for a process map, we need to compute the median for each activity, and also for each path between them) and for huge data sets.
However, there are some situations, in which we have very few measurements for a median (for example, when an activity or path occurs only a few dozen times in the data). When those few measurements are very skewed, i.e. if they are very unevenly distributed, the computed median in Disco could differ significantly from the precise median. This is not a bug in the traditional sense, which is to say that the median estimation in Disco works as expected. Rather, this discrepancy reflects the skewed measurement space reflected in the data. Still, it can be confusing to the analyst, and as such we treated it as a bug.
To address this, in Disco 1.8.0, we have completely reengineered the computation of medians. We now use a new algorithm that can compute the precise median all over Disco with significantly reduced memory footprint. When you have a huge or complex data set, and Disco runs low on available memory, it will automatically transition selected medians to a more memory-efficient calculation method. By automatically selecting those medians, where the transition yields the lowest error in the estimated median, Disco ensures that, even when you are memory-constrained, you will get the best results possible for all your data.
All median calculations that have been transitioned to the more memory-efficient calculation method are now highlighted throughout Disco by being prefixed with a tilde. For example, in the image above, the path with the “~ 142 milliseconds” median duration has been estimated, while the other paths (with “3.9 d” and “71.1 mins”) are precise. This makes it easy for the analyst to see which medians are precise and which have been estimated.
Unless you are working with very large data sets, you will probably never see an estimated median in Disco. And even when you do, in all likelihood the estimated median will differ only very slightly from the precise median, or not at all. And for those rare situations when you absolutely do require total precision of all medians in a huge data set, you can simply increase the memory available to Disco in the control center.
This new median calculation system in Disco 1.8.0 provides the best of both worlds. Wherever possible, you get an absolutely precise median with the minimum memory footprint and best system performance. Whenever that is not possible, Disco automatically reduces the precision for those measurement points where it makes the least difference. In that way, you will get nearly precise medians also for very large data sets. And the best part is, since Disco makes all these decisions automatically, you will never need to worry.
Minimum Duration Perspective
Analyzing the performance of a process in a process map is one of the most important and useful functionalities of Disco. For each activity and path, you can either display the total duration over all cases, inspect the typical duration using either the mean or median duration, or you can display the maximum duration observed in your data.
In Disco 1.8.0, we are adding the minimum duration for all activities and paths. This can be useful if you want to see the “best case scenario”, e.g. if you want to know how fast an activity can be completed if all goes well.
On the other hand, the minimum duration can also highlight problems. If, for example, an activity that checks for authorization from a manager has a minimum duration of only 10 milliseconds, you know that you are either dealing with a suspicious situation, such as fraud, or that there are problems recording your log data.
The minimum duration is available either from the drop-down menu in the Performance perspective, or by clicking on an activity or path, in Disco’s map view.
Disco 1.8.0 now completely supports Mac OS X devices with Retina screens. So, if you have a Mac with a retina screen, every part of Disco will now look even better and razor-sharp.
On the Mac, Disco now also uses the latest version of Java, improving the performance, reliability, and security of using Disco on Mac OS X.
The 1.8.0 update also includes a number of other features and bug fixes, which improve the functionality, reliability, and performance of Disco. Please find a list of the most important further changes below.
Improved CSV Import user interface performance and fidelity.
Improved flexibility of timestamp parser when importing CSV data.
Improved table view performance in the user interface.
Improved diagnostics information that can be sent from feedback or error dialogs, for better and faster problem resolution.
Fixed a bug that could prevent certain recipes from being loaded.
Fixed a bug that could prevent loading logs with large numbers of cases and variants.
Redesigned context dialog popovers.
Improved launch process and OS integration for Windows and Mac OS X.
Improved overdrive performance when mining process maps on machines with multiple CPU cores.
Improved performance of creating process map animations on machines with multiple CPU cores.