Tuesday, June 23, 2020

Word of the Day: process mining software

 
Word of the Day WhatIs.com
Daily updates on the latest technology terms | June 23, 2020
process mining software

Process mining software is a type of programming that analyzes data in enterprise application event logs in order to learn how business processes are actually working. Process mining software provides the transparency administrators need to identify bottlenecks and other areas of inefficiency so they can be improved.

When the software is used to analyze the transaction or audit logs of a workflow management system, data visualization components in the software can show administrators what processes are running at any given time. Some process mining apps also allow users to drill down to view the individual documents associated with a process.

If a process model doesn't already exist, the software will perform business process discovery to create one automatically, sometimes with the aid of artificial intelligence and machine learning. If there already is a model, the process mining software will compare it to the event log to identify discrepancies and their possible causes. Continue reading about process mining software...

Quote of the Day

 

"Process mining reveals performance and compliance problems. By making these transparent, processes can be improved by reducing costs, improving quality and removing delays." - George Lawton

Learning Center

 

Why CIOs need to adopt a process mining initiative
The father of process mining Wil van der Aalst weighs in on the future and explains why it's crucial for organizations to start process mining on a larger scale today.

6 ways AI and automation could improve process mining
Creating a digital twin of your enterprise, identifying automation candidates like RPA and connecting isolated tasks into processes are a few ways CIOs can advance process discovery.

Value stream mapping vs. process mapping to drive process innovation
What's the difference between value stream mapping vs. process mapping? One is focused on making an existing process more efficient, while the other dissects the value of each step.

Data visualization in machine learning boosts data scientist analytics
Data scientists offer practical insights into the role of visualization tools in building, exploring, deploying and monitoring their machine learning models.

4 powerful digital transformation examples
Four organizations succeeded in their digital transformation efforts. Here's a look at what goals they had, problems they faced and rewards they reaped.

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