This IBM® Redbooks® publication series explains the assessment and implementation of a workload, integrated within IBM Smarter Banking® Showcase, and hosted at IBM Montpellier, France. Intended for decision-makers, consultants, architects, administrators, and specialists, this book is the second volume in a series of two: Assessment: Volume 1 (SG24-8007) describes how to evaluate the requirements of a new Smarter Analytics workload, addressing the user, system resources, and data processing profiles to identify the most optimal configuration by using IBM methodologies, such as fit-for-purpose. Given that the existing showcase is based on the IBM zEnterprise® System, deployment options include IBM z/OS®, Linux on IBM System z®, IBM AIX® running on IBM POWER® processor-based blades within the zEnterprise BladeCenter® Extension (zBX), and Windows Server 2008 running on System x® and BladeCenter blades also within zBX. Implementation: Volume 2 (SG24-8008), which you are reading, describes the setups that are involved in deploying the Smarter Analytics workload within the showcase. With multiple components, including IBM Cognos® BI, IBM Cognos TM1®, Cognos Metric Studio, IBM DB2® for z/OS, and a number of application design tools, the workload spans multiple operating environments. The use of application clustering, setting up performance policies by using Unified Resource Manager, and simulation test execution results are included.

Payment fraud can be defined as an intentional deception or misrepresentation that is designed to result in an unauthorized benefit. Fraud schemes are becoming more complex and difficult to identify. It is estimated that industries lose nearly $1 trillion USD annually because of fraud. The ideal solution is where you avoid making fraudulent payments without slowing down legitimate payments. This solution requires that you adopt a comprehensive fraud business architecture that applies predictive analytics. This IBM® Redbooks® publication begins with the business process flows of several industries, such as banking, property/casualty insurance, and tax revenue, where payment fraud is a significant problem. This book then shows how to incorporate technological advancements that help you move from a post-payment to pre-payment fraud detection architecture. Subsequent chapters describe a solution that is specific to the banking industry that can be easily extrapolated to other industries. This book describes the benefits of doing fraud detection on IBM System z®. This book is intended for financial decisionmakers, consultants, and architects, in addition to IT administrators.

When ricocheting a solution that involves analytics, the mainframe might not be the first platform that comes to mind. However, the IBM® System z® group has developed some innovative solutions that include the well-respected mainframe benefits. This book describes a workshop that demonstrates the use of real-time advanced analytics for enhancing core banking decisions using a loan origination example. The workshop is a live hands-on experience of the entire process from analytics modeling to deployment of real-time scoring services for use on IBM z/OS®. In this IBM Redbooks® publication, we include a facilitator guide chapter as well as a participant guide chapter. The facilitator guide includes information about the preparation, such as the needed material, resources, and steps to set up and run this workshop. The participant guide shows step-by-step the tasks for a successful learning experience. The goal of the first hands-on exercise is to learn how to use IBM SPSS® Modeler for Analytics modeling. This provides the basis for the next exercise "Configuring risk assessment in SPSS Decision Management". In the third exercise, the participant experiences how real-time scoring can be implemented on a System z. This publication is written for consultants, IT architects, and IT administrators who want to become familiar with SPSS and analytics solutions on the System z.

The popularity of the Internet and the affordability of IT hardware and software have resulted in an explosion of applications, architectures, and platforms. Workloads have changed. Many applications, including mission-critical ones, are deployed on a variety of platforms, and the System z® design has adapted to this change. It takes into account a wide range of factors, including compatibility and investment protection, to match the IT requirements of an enterprise. The zEnterprise System consists of the IBM zEnterprise 196 central processor complex, the IBM zEnterprise Unified Resource Manager, and the IBM zEnterprise BladeCenter® Extension. The z196 is designed with improved scalability, performance, security, resiliency, availability, and virtualization. The z196 Model M80 provides up to 1.6 times the total system capacity of the z10TM EC Model E64, and all z196 models provide up to twice the available memory of the z10 EC. The zBX infrastructure works with the z196 to enhance System z virtualization and management through an integrated hardware platform that spans mainframe, POWER7TM, and System x® technologies. Through the Unified Resource Manager, the zEnterprise System is managed as a single pool of resources, integrating system and workload management across the environment. This IBM® Redbooks® publication provides an overview of the zEnterprise System and its functions, features, and associated software support. Greater detail is offered in areas relevant to technical planning. This book is intended for systems engineers, consultants, planners, and anyone wanting to understand the zEnterprise System functions and plan for their usage. It is not intended as an introduction to mainframes. Readers are expected to be generally familiar with existing IBM System z technology and terminology. The changes to this edition are based on the System z hardware announcement dated July 12, 2011.

The popularity of the Internet and the affordability of IT hardware and software have resulted in an explosion of applications, architectures, and platforms. Workloads have changed. Many applications, including mission-critical ones, are deployed on a variety of platforms, and the System z® design has adapted to this change. It takes into account a wide range of factors, including compatibility and investment protection, to match the IT requirements of an enterprise. This IBM® Redbooks® publication discusses the IBM zEnterprise System, an IBM scalable mainframe server. IBM is taking a revolutionary approach by integrating separate platforms under the well-proven System z hardware management capabilities, while extending System z qualities of service to those platforms. The zEnterprise System consists of the IBM zEnterprise 114 central processor complex, the IBM zEnterprise Unified Resource Manager, and the IBM zEnterprise BladeCenter® Extension. The z114 is designed with improved scalability, performance, security, resiliency, availability, and virtualization. The z114 provides up to 18% improvement in uniprocessor speed and up to a 12% increase in total system capacity for z/OS®, z/VM®, and Linux on System z over the z10TM Business Class (BC). The zBX infrastructure works with the z114 to enhance System z virtualization and management through an integrated hardware platform that spans mainframe, POWER7TM, and System x technologies. The federated capacity from multiple architectures of the zEnterprise System is managed as a single pool of resources, integrating system and workload management across the environment through the Unified Resource Manager. This book provides an overview of the zEnterprise System and its functions, features, and associated software support. Greater detail is offered in areas relevant to technical planning. This book is intended for systems engineers, consultants, planners, and anyone wanting to understand the zEnterprise System functions and plan for their usage. It is not intended as an introduction to mainframes. Readers are expected to be generally familiar with existing IBM System z technology and terminology.

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.

The popularity of the Internet and the affordability of IT hardware and software have resulted in an explosion of applications, architectures, and platforms. Workloads have changed. Many applications, including mission-critical ones, are deployed on various platforms, and the IBM® System z® design has adapted to this change. It takes into account a wide range of factors, including compatibility and investment protection, to match the IT requirements of an enterprise. This IBM Redbooks® publication addresses the new IBM zEnterprise® System. This system consists of the IBM zEnterprise EC12 (zEC12), an updated IBM zEnterprise Unified Resource Manager, and the IBM zEnterprise BladeCenter® Extension (zBX) Model 003. The zEC12 is designed with improved scalability, performance, security, resiliency, availability, and virtualization. The superscalar design allows the zEC12 to deliver a record level of capacity over the prior System z servers. It is powered by 120 of the world's most powerful microprocessors. These microprocessors run at 5.5 GHz and are capable of running more than 75,000 millions of instructions per second (MIPS). The zEC12 Model HA1 is estimated to provide up to 50% more total system capacity than the IBM zEnterprise 196 (z196) Model M80. The zBX Model 003 infrastructure works with the zEC12 to enhance System z virtualization and management. It does so through an integrated hardware platform that spans mainframe, IBM POWER7®, and IBM System x® technologies. Through the Unified Resource Manager, the zEnterprise System is managed as a single pool of resources, integrating system and workload management across the environment. This book provides information about the zEnterprise System and its functions, features, and associated software support. Greater detail is offered in areas relevant to technical planning. It is intended for systems engineers, consultants, planners, and anyone who wants to understand the zEnterprise System functions and plan for their usage. It is not intended as an introduction to mainframes. Readers are expected to be generally familiar with existing IBM System z® technology and terminology.

Regarding online transaction processing (OLTP) workloads, IBM® z SystemsTM platform, with IBM DB2®, data sharing, Workload Manager (WLM), geoplex, and other high-end features, is the widely acknowledged leader. Most customers now integrate business analytics with OLTP by running, for example, scoring functions from transactional context for real-time analytics or by applying machine-learning algorithms on enterprise data that is kept on the mainframe. As a result, IBM adds investment so clients can keep the complete lifecycle for data analysis, modeling, and scoring on z Systems control in a cost-efficient way, keeping the qualities of services in availability, security, reliability that z Systems solutions offer. Because of the changed architecture and tighter integration, IBM has shown, in a customer proof-of-concept, that a particular client was able to achieve an orders-of-magnitude improvement in performance, allowing that client's data scientist to investigate the data in a more interactive process. Open technologies, such as Predictive Model Markup Language (PMML) can help customers update single components instead of being forced to replace everything at once. As a result, you have the possibility to combine your preferred tool for model generation (such as SAS Enterprise Miner or IBM SPSS® Modeler) with a different technology for model scoring (such as Zementis, a company focused on PMML scoring). IBM SPSS Modeler is a leading data mining workbench that can apply various algorithms in data preparation, cleansing, statistics, visualization, machine learning, and predictive analytics. It has over 20 years of experience and continued development, and is integrated with z Systems. With IBM DB2 Analytics Accelerator 5.1 and SPSS Modeler 17.1, the possibility exists to do the complete predictive model creation including data transformation within DB2 Analytics Accelerator. So, instead of moving the data to a distributed environment, algorithms can be pushed to the data, using cost-efficient DB2 Accelerator for the required resource-intensive operations. This IBM Redbooks® publication explains the overall z Systems architecture, how the components can be installed and customized, how the new IBM DB2 Analytics Accelerator loader can help efficient data loading for z Systems data and external data, how in-database transformation, in-database modeling, and in-transactional real-time scoring can be used, and what other related technologies are available. This book is intended for technical specialists and architects, and data scientists who want to use the technology on the z Systems platform. Most of the technologies described in this book require IBM DB2 for z/OS®. For acceleration of the data investigation, data transformation, and data modeling process, DB2 Analytics Accelerator is required. Most value can be achieved if most of the data already resides on z Systems platforms, although adding external data (like from social sources) poses no problem at all.

Today, organizations face tremendous challenges with data explosion and information governance. InfoSphereTM OptimTM solutions solve the data growth problem at the source by managing the enterprise application data. The Optim Data Growth solutions are consistent, scalable solutions that include comprehensive capabilities for managing enterprise application data across applications, databases, operating systems, and hardware platforms. You can align the management of your enterprise application data with your business objectives to improve application service levels, lower costs, and mitigate risk. In this IBM® Redbooks® publication, we describe the IBM InfoSphere Optim Data Growth solutions and a methodology that provides implementation guidance from requirements analysis through deployment and administration planning. We also discuss various implementation topics including system architecture design, sizing, scalability, security, performance, and automation. This book is intended to provide various systems development professionals, Data Solution Architects, Data Administrators, Modelers, Data Analysts, Data Integrators, or anyone who has to analyze or integrate data structures, a broad understanding about IBM InfoSphere Optim Data Growth solutions. By being used in conjunction with the product manuals and online help, this book provides guidance about implementing an optimal solution for managing your enterprise application data.

This IBM® Redpaper Redbooks® publication provides a broad explanation of data protection through encryption and IBM Z® pervasive encryption with a focus on IBM z/OS® data set encryption. It describes how the various hardware and software components interact in a z/OS data set encryption environment. In addition, this book concentrates on the planning and preparing of the environment and offers implementation, configuration, and operational examples that can be used in z/OS data set encryption environments. This publication is intended for IT architects, system programmer, and security administrators who plan for, deploy, and manage security on the Z platform. The reader is expected to have a basic understanding of IBM Z security concepts.