Flexible Decision Management With Business Rules On Ibm Z Systems

The IBM® Operational Decision Manager product family provides value to organizations that want to improve the responsiveness and precision of automated decisions. This decision management platform on IBM z/OS® provides comprehensive automation and governance of operational decisions that are made within mainframe applications. These decisions can be shared with other cross-platform applications, providing true enterprise decision management. This IBM Redbooks® publication makes the case for using Operational Decision Manager for z/OS and provides an overview of its components. It is aimed at IT architects, enterprise architects, and development managers looking to build rule-based solutions. Step-by-step guidance is provided about getting started with business rules by using a scenario-based approach. This book provides detailed guidelines for testing and simulation and describes advanced options for decision authoring. Finally, it describes and documents multiple runtime configuration options. This third edition, SG24-8014-02, of this IBM Redbooks publication updated the information presented in this book to reflect function available in IBM Operational Decision Manager for z/OS Version 8.7.1.

Systems of record (SORs) are engines that generates value for your business. Systems of engagement (SOE) are always evolving and generating new customer-centric experiences and new opportunities to capitalize on the value in the systems of record. The highest value is gained when systems of record and systems of engagement are brought together to deliver insight. Systems of insight (SOI) monitor and analyze what is going on with various behaviors in the systems of engagement and information being stored or transacted in the systems of record. SOIs seek new opportunities, risks, and operational behavior that needs to be reported or have action taken to optimize business outcomes. Systems of insight are at the core of the Digital Experience, which tries to derive insights from the enormous amount of data generated by automated processes and customer interactions. Systems of Insight can also provide the ability to apply analytics and rules to real-time data as it flows within, throughout, and beyond the enterprise (applications, databases, mobile, social, Internet of Things) to gain the wanted insight. Deriving this insight is a key step toward being able to make the best decisions and take the most appropriate actions. Examples of such actions are to improve the number of satisfied clients, identify clients at risk of leaving and incentivize them to stay loyal, identify patterns of risk or fraudulent behavior and take action to minimize it as early as possible, and detect patterns of behavior in operational systems and transportation that lead to failures, delays, and maintenance and take early action to minimize risks and costs. IBM® Operational Decision Manager is a decision management platform that provides capabilities that support both event-driven insight patterns, and business-rule-driven scenarios. It also can easily be used in combination with other IBM Analytics solutions, as the detailed examples will show. IBM Operational Decision Manager Advanced, along with complementary IBM software offerings that also provide capability for systems of insight, provides a way to deliver the greatest value to your customers and your business. IBM Operational Decision Manager Advanced brings together data from different sources to recognize meaningful trends and patterns. It empowers business users to define, manage, and automate repeatable operational decisions. As a result, organizations can create and shape customer-centric business moments. This IBM Redbooks® publication explains the key concepts of systems of insight and how to implement a system of insight solution with examples. It is intended for IT architects and professionals who are responsible for implementing a systems of insights solution requiring event-based context pattern detection and deterministic decision services to enhance other analytics solution components with IBM Operational Decision Manager Advanced.

This IBM® Redbooks® publication introduces operational decision governance and describes in detail how to implement it using the IBM Operational Decision Manager (ODM) platform. ODM allows businesses to automate and manage day-to-day operational decisions. It provides an integrated repository and management components for line-of-business, subject-matter experts to directly participate in the definition and governance of rules-based decision logic, organized in decision services. Governance of changes to decision services is of particular importance and value. This book describes how organizations can choose between the built-in ODM decision governance framework or a custom governance based on manually managed branches. Related topics, such as access control, permissions and user management, are covered and give a full view on decision service governance. You will find this book valuable if you are using or considering the usage of an operational decision management system in your organization, either with ODM on-premises or ODM on Cloud offerings. This book was written to help assist the following target audience in applying Decision Management technology successfully: IT Project Managers need to understand how decision governance differs from IT Governance, and how ODM straddles both worlds to facilitate agile change. IT Technical Architects need to understand how to architect ODM to sit inside both the IT and business worlds. Business Analysts need to understand the processes for changing business policies using ODM Decision Center. Business Rule Development Teams need to understand the best way to structure rule projects for scalability and maintainability.

This Redpaper introduces the integration between two IBM products that you might like to consider when implementing a modern agile solution on your Z systems. The document briefly introduces Operational Decision Manager on z/OS and Machine learning on z/OS. In the case of Machine Learning we focus on the aspect of real-time scoring models and how these can be used with Business Rules to give better decisions. Note: Important changes since this document was written: This document was written for an older release of Operational Decision Manager for z/OS (ODM for z/OS). ODM for z/OS 8.9.1 required the writing of custom Java code to access a Watson Machine Learning for z/OS Scoring Service (this can be seen in ). Since that time ODM for z/OS version 8.10.1 has been released and much improves the integration experience. Integrating the two products no longer requires custom Java code. Using ODM for z/OS 8.10.1 or later you can use an automated wizard in the ODM tooling to: Browse and select a model from Watson Machine Learning Import the Machine Learning data model into your rule project Automatically generate a template rule that integrates a call to the Watson Machine Learning scoring service Download and read this document for: Individual introductions to ODM for z/OS and Machine learning Discussions on the benefits of using the two technologies together Information on integrating if you have not yet updated to ODM for z/OS 8.10.1 For information about the machine learning integration in ODM for z/OS 8.10.1 see IBM Watson Machine Learning for z/OS integration topic in the ODM for z/OS 8.10.x Knowledge Center

Mainframe computers play a central role in the daily operations of many of the world's largest corporations, and batch processing is a fundamental part of the workloads that run on the mainframe. A large portion of the workload on IBM® z/OS® systems is processed in batch mode. Although several IBM Redbooks® publications discuss application modernization on the IBM z/OS platform, this book specifically addresses batch processing in detail. Many different technologies are available in a batch environment on z/OS systems. This book demonstrates these technologies and shows how the z/OS system offers a sophisticated environment for batch. In this practical book, we discuss a variety of themes that are of importance for batch workloads on z/OS systems and offer examples that you can try on your own system. The audience for this book includes IT architects and application developers, with a focus on batch processing on the z/OS platform.

Decision management is emerging as an important capability for delivering agile business solutions. Decision management is not a solution in its own right, but must be integrated into the solutions or business processes that it supports. In this IBM® RedpapersTM publication, we describe the recommended best practices and integration concepts that use the business events, business rules, and other capabilities of IBM WebSphere® Operational Decision Management V7.5 (WebSphere ODM) to provide better decision making in those solutions and business processes.

In this IBM® Redbooks® publication, we describe the role Cognos® plays in an Information On Demand (IOD) solution for IBM System z® and detail the functions of IBM Cognos 8 BI for Linux® on System z in current deployment scenarios. We show typical deployment architectures that show how to access disparate data sources both on and off the System z platform and show how the functions of the Cognos family of products provides a way to consolidate different BI solutions on System z. We provide examples of Cognos functions for resolving business requirements using reporting and OLAP capabilities as well as general deployment considerations of IBM Cognos 8 BI for Linux on System z. This publication is meant to help the Cognos Business Intelligence professional understand the strong points of System z architecture and the database specialist appreciate the Cognos family of products.