Business rule engines (BRE) have been around for a long time. Introduced in the early 1990s, BREs have found application in many industries, particularly those that are heavily regulated where compliance and auditability are key concerns. A BRE enables complex rules and regulations to be encoded in a rule language, some of which bear a passing resemblance to English. The BRE can then evaluate the rules against enterprise data to ensure that the business transactions, etc. that the enterprise is performing comply with those rules. Today one of the most popular rule engines is Drools, an open source engine sponsored by Red Hat with a powerful rule language, called DRL, and a highly efficient algorithm that can scale to support hundreds of thousands of rules and terabytes of data.
Rule engines are a great idea. It’s much easier to simply specify all the rules that should apply to a particular transaction than it is to write a program in a traditional language like Java to verify compliance. And it’s much easier to change the rules in a BRE when needed than to modify and test a traditional application. Today’s focus on digital transformation is finding ever wider applications for BREs, from cleansing big data, to fraud detection to identifying patterns in event streams from the Internet of Things.
However, rules engines have had difficulty gaining traction with the business community – the analysts and business experts that understand the rules of the business and would be the logical people to encode them in a rule language. Even though such languages can be tailored for ‘business users’, it is still a steep learning curve fraught with potential pitfalls – conflicts between rules, unseen overlaps, gaps and so on. These difficulties have limited the adoption of BREs to organizations with more complex needs, and with the skills needed to fully utilize the capabilities of a BRE.
Now, however, there is a new approach. In 2015 the Object Management Group published a specification for a graphical decision language designed specifically for business users. Now in its 3rd year and version 1.2, Decision Model and Notation (DMN) manages to combine a straightforward representation of the inputs, outputs and rules that govern a business decision, with the expressiveness needed to encompass the information required to fully automate any decision. At the heart of DMN is an expression language called FEEL, for Friendly Enough Expression Language. FEEL is designed from the outset for use by business people, allowing them to specify business logic with no greater complexity than a typical Excel spreadsheet.
Here at Red Hat we are proud to offer full DMN support with our rule engine – Red Hat Decision Manager. If you would like to learn more about DMN, and how it might help you better automate business decisions, we have joined forces with the IIBA to host a webinar on October 18 at 1pm ET to further explore the topic. I’ll be joined by Denis Gagne at Trisotech for a deeper dive into DMN and the Red Hat engine. If you would like to register you can do so here, and we’ll be delighted to have you join!
This year in Boston, MA you can attend the Red Hat Summit 2017, the event to get your updates on open source technologies and meet with all the experts you follow throughout the year.
It’s taking place from May 2-4 and is full of interesting sessions, keynotes, and labs.
This year I was part of the process of selecting the labs you are going to experience at Red Hat Summit and wanted to share here some to help you plan your JBoss labs experience. These labs are for you to spend time with the experts who will teach you hands-on how to get the most out of your JBoss middleware products.
Each lab is a 2-hour session, so planning is essential to getting the most out of your days at Red Hat Summit.
As you might be struggling to find and plan your sessions together with some lab time, here is an overview of the labs you can find in the session catalog for exact room and times. Each entry includes the lab number, title, abstract, instructors and is linked to the session catalog entry:
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We are excited to announce the release of Red Hat JBoss Data Virtualization 6.3.
Data integration has always been challenging. Modern technology trends like big data and cloud, coupled with the need for more real time data access and analysis, are adding to the complexity facing enterprises today.
JBoss Data Virtualization is a data access and integration solution that offers an alternative to physical data consolidation and data delivery by allowing flexibility and agility in data access. Data virtualization creates a single logical view of data from varied data sources, including transactional systems, relational databases, cloud data stores, and big data stores.
What’s New in JDV 6.3
JBoss Data Virtualization 6.3 adds capabilities to help organizations integrate big data and provide high performance data access in real time. The release notes cover the full features and enhancements for JBoss Data Virtualization 6.3. There are a number of new features to enable expanded connectivity, enhanced security and developer productivity support.
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Database Trends and Applications (DBTA) announced its data solutions winners earlier this August, and one of our middleware products was honored! Red Hat JBoss Data Virtualization won best data virtualization solution.
DBTA’s awards were reader’s choice, meaning that it was the community of data virtualization users who voted for JBoss Data Virtualization. According to DBTA’s announcements, the hallmarks of a winning data virtualization solution include three characteristics:
- Agile development
- A secure virtual data layer
- Real-time data access and provisioning
It’s a combination of security and speed.
Data virtualization provides a layer over existing, separate data sources, which integrates the data in those sources without have to manually copy or convert that data. Data virtualization can support a lot of potential business benefits, including reducing duplicate data, improving data consistency, and reducing architectural complexity. Data virtualizations can provide that comprehensive view and access to data, without having to replace existing applications.
Find out more about Red Hat JBoss Data Virtualization here