Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

docs(process-mining): spelling review #59

Merged
merged 4 commits into from Jul 1, 2019
Merged

docs(process-mining): spelling review #59

Changes from 2 commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
9dc4f32
docs(process-mining): spelling review
csouchet Jun 25, 2019
0a6495a
docs(process-mining): Add missing '-'
csouchet Jun 25, 2019
a587615
Merge remote-tracking branch 'origin/1.0' into ICI-1224_Process_mining
csouchet Jul 1, 2019
4a685cc
docs(process-mining): Remove all "-" from "process-mining"
csouchet Jul 1, 2019
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
6 changes: 3 additions & 3 deletions md/process_mining.md
View file
Open in desktop
@@ -1,20 +1,20 @@
# Process-mining

Process mining is a set of analysis made on any enterprise data log or events, in order to discover processes and
Process-mining is a set of analysis made on any enterprise data logs or events, in order to discover processes and
compute some statistics or business analytic queries. Applied to Bonita platform, we use BPM event logs stored in
Bonita engine database to compute a predictive model.


## General

As an introduction, you can see some of our [webinars](https://www.bonitasoft.com/videos?category=Webinars) for
more information about process mining.
more information about process-mining.

## What is used in BICI v1: Predict chances to finish on time

Analysis done in BICI will replay each process instance using its history and compute the remaining time on each state it went through.

Then percentiles of the remaining time for each of these state will be stored in a *prediction model*.
Then percentiles of the remaining time for each of these states will be stored in a *prediction model*.

The *prediction model* allows to predict the percentage of chance to be within a target duration.

Expand Down