Business Intelligence Built on Metrics – Part I.

Business Intelligence (BI) is the process of collecting, analyzing, and presenting business data to help organizations make better decisions. It transforms data into meaningful insights enabling companies to understand their performance, market trends, and competitive position. In this blog post I will explain how you can use BI together with a Business Process Management System.

Most BI tools follow the approach to transform raw data from a database centric business application into aggregated data for analysis. Typically those tools are built on SQL based databases which makes it easy to group data or compute totals across different queries. Of course, this approach requires a well-designed data structure and a deep understanding of the technical relationships between different information domains. Thus, it is usually a collaboration between business analysts and developers to collect this kind of data.

But what if you have a business process management system instead of a ERP software? In such a software system, there are floating and volatile workflows that generate the data to be analyzed. For example, a “complaint management” business process is more likely to look at timings, processing periods, and costs over time. The analysis of such processes in a BI tool is often very difficult to realize with conventional SQL queries. So the question is: what could be the right architecture to process this type of data in a BI platform?

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Imixs-Workflow: A Business-Centric Alternative to Camunda

In today’s rapidly evolving business landscape, organizations need workflow solutions that can adapt quickly to changing requirements while maintaining operational efficiency. While there are several workflow engines available in the market, Imixs-Workflow stands out as a compelling choice, particularly for organizations seeking to put process control directly in the hands of business users. Why can Imixs-Workflow be an alternative to Camunda?

As organizations evaluate workflow engines for their process automation needs, Camunda has established itself as a powerful solution, particularly for development teams implementing complex program logic through BPMN models. However, for organizations seeking a more business-oriented approach, Imixs-Workflow emerges as a compelling alternative that addresses different yet equally important needs in the process automation landscape.

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Why You Shouldn’t Compare Camunda to Imixs Workflow

Today I was asked from customers how to compare Camunda with the Imixs-Workflow engine. This question often comes up when projects try to evaluate and compare workflow engines. My short answer to this question is: You shouldn’t compare these two engines. In the following, I will try to explain this in more detail.

First of all, I would like to make it clear that this is not an evaluation of the two engines, but only to show the different criteria that come into question for an evaluation. So first, let’s look at the similarities between Camunda and Imixs.

Both engines are open source frameworks. Both are implemented in Java and both support the BPMN 2.0 standard. But these are already the only similarities that both frameworks have in common. You could now argue that Camunda is essentially based on Spring and Imixs-Workflow is a Jakarta EE implementation. One could also highlight the different modeling concepts that both frameworks represent (I have talked about this some times ago). But all these are details of architecture and implementation in my opinion. The main difference is quite another one.

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Build your Business App with BPMN 2.0

In this short tutorial I will show how to build a business application with the Business Process Modelling Notation – BPMN. This approach differs from the usual data-centric approach as we focus on process management instead of data processing.

Data Processing vs. Process Management

When we follow the classic approach building a Data-Centric Business Application, we usually first design a data schema. The data schema defines what kind of data can be managed. The application allows us to create new data sets, edit existing data and of course search for data.

In a Process-Centric Business Application we instead first try to answer the question how data should be processed to give each actor the best access to information to reach a specific business goal. And this kind of question becomes more and more important in our today’s rapidly evolving business landscape. BPMN offers the perfect approach to model a workflow with its business goals from the beginning to the end. BPMN models can be created with various tools like for example the Open Source BPMN designer Open-BPMN.

The big advantage of BPMN is that it does not only give all stake holders a clear understanding about the process, a BPMN 2.0 Model can also be executed by a suitable process engine. This “low-code” or “model-driven” approach leads to a much more flexible way to implement business applications. Of course, data still plays an important role and workflow engines allow us to manage business data in various ways. So let’s see how this works…

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Data Processing vs. Process Management?

In today’s data-driven business landscape, managing data effectively is crucial for achieving organizational goals. While data processing systems play a vital role in collecting and organizing data, it is often overlooked that data should not be managed solely for its own sake. True value lies in understanding how data can be leveraged to achieve business objectives, which is where the concept of process management comes into play.

Today we live in a world where data is everywhere and every enterprise knows about the value of data. But how do we handle data? How do we create, collect analyze it? This is the area of data processing software. And we all use databases, spread sheets and data management systems to manage all kind of data. Many software systems are build around specific data domains and we use this software to create and maintain the data.

But in this context, however, it is often overlooked that data should not be managed for its own sake. The reason why we need data in companies is that we want to achieve certain business goals. And in this context, we come to the question of how corporate goals can be achieved at all? This is the area of process management.

So what’s the difference between data processing and processes management?

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How to Run Containers with GPU Support

In this short tutorial I will explain how to run a Docker container with GPU support. This becomes important if you want to run AI applications such as the Imixs-AI project within a local Docker environment or in a Kubernetes Cluster. This short tutorial is based on Debian 12 (Bookworm) and the usage of a NVIDA graphic card. I assume that you already have installed Debian and the Docker engine. Read the official install guide about how to install the Docker engine on Debian.

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BPMN 2.0 and Jakarta EE – A Powerful Alliance

A BPMN Workflow engine based on the Jakarta EE Framework forms a powerful and effective combination for developing enterprise applications with a focus on business process management. Both, Jakarta EE and BPMN 2.0 are standardized and widely supported. The scalability of Jakarta EE provides a secure foundation for building enterprise applications with robust business process management capabilities. This enables developers to leverage the strengths of both technologies to create efficient, interoperable, and maintainable BPM solutions. In the following I will explain the aspects in more detail.

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Compare Workflow Engines

The term “workflow engine” is not clearly defined in software development and therefore we would like to give a brief overview of different aspects and types of workflow engines in the following blog post.

If you take a look at the Github page awesome-workflow-engines, you will find an impressive number of open source workflow engines. But not all of these engines solve the same problem. The idea behind the term ‘workflow’ can be very different and so the functionality of a workflow engine. In general a workflow is a series of tasks or activities that are required to complete a specific process. Such a process can involve multiple people, teams, microservices or even other IT systems. Thus, it becomes clear that when comparing Workflow Engines, various aspects must be taken into account.

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Why AWS & Azure Are Not Kubernetes

When you hear about Kubernetes for the first time these days, you might get the impression that Kubernetes has a lot to do with AWS or Azure. If you read blogs or tutorials about Kubernetes or even if you join conferences, AWS and Azure is everywhere. It seems like a stupid idea not to believe that Kubernetes is based on these Internet platforms and can exist outside them.

But Kubernetes is far away from being a product or internet service that is only offered by Amazon or Microsoft. Rather, Kubernetes is an open source platform which is supported and developed by the Linux Foundation. Many people are working on the concepts for this open platform on a daily basis. And the goal of Kubernetes is to provide an open and powerful platform for operating container-based applications and Microservices.

It was never a walk in the park to setup and operate a stable and highly available cloud environment consisting of many servers. With Kubernetes companies and organizations should be enabled to run a server infrastructure for container-based applications by there own. Google has published his own experiences in this area and handed it over to the Linux Foundation in order to share that knowledge with others. And it was never the goal to make a product or put organizations in a dependent situation. On the other hand, it is a big business for companies like Microsoft and Amazon to offer their services based on the concepts of Kubernetes. Binding customers to their platforms is the new way of licencing. And they do a lot of marketing to succeed.

Build Your Own Cluster

Believe it or not, you can set up your own Kubernetes cluster and run it successfully in just a few hours. The concepts of Kubernetes provide many solutions for the problems that normally arise when operating large server environments. The result will be a stable and sustainable cloud infrastructure that you can control yourself.

Of course, Kubernetes is a complex system of many different building blocks. It takes time to get used to it. But today there are also a lot of concepts available to achieve success quickly. So don’t hesitate and take control of your personal cloud platform.

If you like, you can take a look at our open source project ‘Imixs-Cloud‘, which shows a simple and stable approach for the operation of a Kubernetes cluster.

Stream Analytics with Imixs-Workflow

The real-time processing of a continuous stream of business data and events is becoming increasingly important in modern IT architectures. This type of architecture, in which events are building the centre of data processing, is also known as a Reactive Streaming Architecture. In the following we will show how to solve some of the related challenges with the help of a workflow technology.

Let’s take a closer look at this type of architecture first. Basically, the event-based processing of data is not new and has actually been developed for decades in various specialized domains such as the financial sector. But since the last few years, new standards for processing data streams have emerged. Technologies like Apache Kafka, Storm, Flink or Spark are gaining popularity and pushing a new hype.

From industrial production systems to multiplayer computer games, so-called Streaming Architectures are used more and more frequently in order to be able to process big data in real time. Streaming architectures have developed into a central architectural element of modern technology companies. In many companies real-time streams have become the core system in their architecture.

The goal is to be able to integrate new system solutions more quickly and to connect any kind of data streams. The streaming architecture is not only found at technology giants such as Ebay, Netflix or Amazon, but today in every modern technology company that is working on the digitization of its business processes. So what are the main challenges in building such an architecture?

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