Celonis brings process intelligence to Microsoft Fabric
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The latest news in process intelligence and process mining including research, appointments, software developments and partnerships.
This week features:
- Celonis adds process intelligence to Microsoft Fabric
- Supreme Court of Virginia agrees to hear Appian petition to reinstate verdict against Pegasystems
- Process mining enables continuous improvement in RPA
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Celonis adds process intelligence to Microsoft Fabric
Celonis is expanding its strategic collaboration with Microsoft with multiple deep integrations including introducing Celonis Process Intelligence as a workload in Microsoft Fabric. This will enable Microsoft users to seamlessly embed process intelligence into any solution they’re building, such as a Microsoft Power BI dashboard or AI agent in Microsoft Copilot Studio, according to a press release.
Celonis’ integration with Fabric enhances data sharing from Microsoft OneLake, removing the need for any data transfer outside of Fabric. This eliminates data silos and ensures a single source of truth, reducing storage and transfer costs, limiting data errors and simplifying data governance to support these modern enterprise IT priorities. The integration also enables use cases that require instant data synchronization.
“Thanks to the collaboration between Celonis and Microsoft, companies can access Celonis’ unique process data and context in the most commonly deployed enterprise platform,” said Daniel Brown, chief product officer at Celonis. “This new integration gives Microsoft customers a process-centric data foundation for the solutions they’re building.”
The zero-copy integration with Microsoft OneLake and the introduction of a Celonis workload within Microsoft Fabric enables customers to use process intelligence directly within existing analytics and artificial intelligence (AI) workflows, added Dipti Borkar, VP and GM Fabric OneLake and Fabric ISVs, Microsoft Azure. “Together, we are making AI more relevant and effective for the enterprise.”
Celonis also announced the appointment of Kaushik Mitra as VP and head of India go-to-market (GTM) to lead expansion in the fast-growing Indian market by driving strategic growth initiatives, deepening customer and partner relationships and scaling business operations.
Watch Madison Lundquist, principal research lead, process and performance management at APQC, discuss the state of process strategy
Supreme Court of Virginia agrees to hear Appian petition to reinstate verdict against Pegasystems
Process mining provider Appian announced that the Supreme Court of Virginia agreed to hear its petition seeking to reinstate the $2.036 billion judgment against Pegasystems, Inc. The petition, which raised four different errors made by the Court of Appeals, seeks to restore the jury’s verdict of willful and malicious trade secret misappropriation. The petition was granted on each of the four issues.
Appian originally brought the case to trial to ensure the protection of its intellectual property, including its trade secrets. The unanimous verdict from the jury was based on seven weeks of testimony from dozens of witnesses and thousands of pages of evidence introduced to show that Pegasystems employed a “spy” to analyze the inner workings of Appian’s software, improve its own product and generate billions of dollars in revenue based on its misappropriation.
“We are encouraged that the Supreme Court of Virginia has agreed to review our case,” commented Christopher Winters, general counsel of Appian. “We look forward to being heard by the highest court in Virginia and remain hopeful the Court will reinstate the jury’s verdict and corresponding damages, which were in line with the scope of wrongdoing found in this case and which we believe is the correct legal outcome.”
The Supreme Court also agreed to hear Pega’s cross-appeal issues, which presented arguments regarding the sufficiency of the evidence of trade secret misappropriation. The petition will be subject to further briefing and argument in front of the Supreme Court of Virginia.
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Process mining enables continuous improvement in RPA
Process mining can be a key contributor to continuous improvement in robotic process automation (RPA), according to a new study. Process mining technology was applied to analyze the current workflow in an organization’s RPA function. The implemented process mining application used two common techniques: process discovery and conformance checking. Process discovery modelled the process and gave an overview of the work items, their throughput times, and their routes. Conformance checking revealed several deviations, with the longest throughput times occurring in cases that looped back to an earlier stage.
It found several areas for improvement based on process mining analysis and satisfaction surveys. These include more testing in the early piloting stage of the development process, increased focus on optimizing business processes before they are automated and conducting more thorough analyses to assess automation suitability to maximize the benefits of RPA.
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