The launch of Rialto Process is a fact.
On top of the Rialto foundation platform now a Rialto extensions exist for Process Mining.
Rialto Process is an embedded data and process analytics platform supporting a mix of tasks (acquisition, filtering, data mining, text mining, data and process visualization, …) and modeling (predictive, prescriptive, sentiment, …). Our vision from analytics to operations becomes reality.
Connect to and blend a range of very big, big, smart or small datasources and ultimately deliver an analytics based monitoring app that can be encapsulated in your companies operations monitoring and management systems. Industrial Analytics enabled
The process analytics modules are:
- Process Data Management with Acquisition (OpenXES 2.0 –eXtensible Event Stream) , Enrichment (Anonymisation, Add Start and End events, Missing Value addition), Blending of separate data sets based in ‘connect’ fields, Time and Rule Bases Filtering/Trimming, Complex Rule based Tagging, Data Quality Analyses, Export,…
- Activity based analyses/analytics (Process Mining) with Event Log Play-In, Process Statistics and Process Flow Visual Analyses, Performance-Conformance-Process Variant Analytics, Time Drift and Concept Drift Analyses, …
- Resource based analyses/Analytics (Social Mining) with Event Log Play-In with automatic discovery and visualisation of the work-handover process model, Work Hand-Over Variations with impact statistics tables and interactive charts
- Blended Analytics (Examples)
Process and Data analytics. Use of Machine learning modules (decision tree) to determine (predict) the resource that will end the case in the shortest possible time.
Process and Text Analytics. Text mining of a filelist to extract the last document change date or e-mail correspondance exchange file with the extraction of the from->to and return mail datestamp, to determine start and end time of a particular activity.
The full feature – function list exeura.eu