Intelligent Business Process Management Suites (iBPMS) – The Next-Generation BPM for a Big Data World

In August 2014, I had an interesting talk at ECSA 2014 in Vienna about iBPMS called The Next-Generation BPM for a Big Data World: Intelligent Business Process Management Suites (iBPMS). iBPMS is a term introduced by Gartner some time ago: Magic Quadrant for Intelligent Business Process Management Suites.

I want to share the slides with you. As always, I appreciate every comment or feedback…

Abstract: iBPMS / iBPM

Here is the abstract of my session about iBPMS:

Business Process Management (BPM) is established, tools are stable, and many companies use it successfully. However, today’s business processes are based just on “dumb” data from relational databases or web services. Humans make decisions based on this information. Instead, the value of big data analytics should be integrated into business processes, too. Besides, user interfaces are inflexible. Modern concepts such as mobile devices or social media are not integrated into business processes. That is status quo. Companies miss a huge opportunity here!
This session explains the idea behind next-generation BPM (also called Intelligent Business Process Management, iBPMS, iBPM), which includes big data analytics, social media, and mobile device support. The talk will focus on real world use cases. The audience will learn how to realize intelligent business processes technically by combining BPM, integration, big data and analytics.

Use Case: TIBCO AMX BPM + BusinessWorks + StreamBase + Tibbr

The content of the slides is vendor-independent. It will help you to understand the concepts of iBPMS and how different parts such as BPM, Big Data Analytics or Integration are related. It does not matter if you want to / have to use IBM, Oracle, TIBCO, or any other software for realizing iBPMS.

To demonstrate the implementation of a real world sue case, the slides also include an example of how to implement iBPMS with the TIBCO middleware stack. The solution uses:

  • TIBCO ActiveMatrix BPM for business process management to combine human interaction and automatic tasks
  • TIBCO ActiveMatrix BusinessWorks – an Enterprise Service Bus (ESB) – for integration  of applications (SAP, Salesforce, Mainframe, EDI, etc.) and technologies (SOAP Web Services, REST APIs, JMS, TCP, etc.)
  • TIBCO StreamBase for stream processing (fast data processing and streaming analytics)
  • TIBCO Tibbr as social enterprise network for work distribution to occasional users

A huge benefit of the TIBCO stack is that the products are loosely coupled, but integrated. Thus, it is easy to implement iBPMS.

Slides: iBPMS at ECSA 2014

Here are the slides:

Click on the button to load the content from www.slideshare.net.

Load content

Kai Waehner

bridging the gap between technical innovation and business value for real-time data streaming, processing and analytics

Recent Posts

How Penske Logistics Transforms Fleet Intelligence with Data Streaming and AI

Real-time visibility has become essential in logistics. As supply chains grow more complex, providers must…

1 day ago

Data Streaming Meets the SAP Ecosystem and Databricks – Insights from SAP Sapphire Madrid

SAP Sapphire 2025 in Madrid brought together global SAP users, partners, and technology leaders to…

6 days ago

Agentic AI with the Agent2Agent Protocol (A2A) and MCP using Apache Kafka as Event Broker

Agentic AI is emerging as a powerful pattern for building autonomous, intelligent, and collaborative systems.…

1 week ago

Powering Fantasy Sports at Scale: How Dream11 Uses Apache Kafka for Real-Time Gaming

Fantasy sports has evolved into a data-driven, real-time digital industry with high stakes and massive…

2 weeks ago

Databricks and Confluent Leading Data and AI Architectures – What About Snowflake, BigQuery, and Friends?

Confluent, Databricks, and Snowflake are trusted by thousands of enterprises to power critical workloads—each with…

3 weeks ago

Databricks and Confluent in the World of Enterprise Software (with SAP as Example)

Enterprise data lives in complex ecosystems—SAP, Oracle, Salesforce, ServiceNow, IBM Mainframes, and more. This article…

3 weeks ago