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.

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.

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.

Many companies have built data warehouses (DWs) and have embraced business intelligence (BI) and analytics solutions. Even as companies have accumulated huge amounts of data, however, it remains difficult to provide trusted information at the right time and in the right place. The amount of data collected and available throughout the enterprise continues to grow even as the complexity and urgency of receiving meaningful information continues to increase. Producing meaningful and trusted information when it is needed can only be achieved by having a proper information architecture in place and a powerful underlying infrastructure. The amounts of data to mine, cleanse, and integrate are becoming so large that increasingly the infrastructure is becoming the bottleneck. This results in low refresh rates of the data in the data warehouse and in not having the information available in time where it is needed. And even before information can become available in a BI dashboard or a report, many preceding steps must take place: the collection of raw data; integration of data from multiple data stores, business units or geographies; transformation of data from one format to another; cubing data into data cubes; and finally, loading changes to data in the data warehouse. Combining the complexity of the information requirements, the growing amounts of data, and multiple layers of the information architecture requires an extremely powerful infrastructure. This IBM® RedguideTM publication explains how you can use IBM System z® as the foundation for your information management architecture. The System z value proposition for information management is fueled by the traditional strengths of the IBM mainframe, the specific strengths of DB2® for z/OS®, and the broad functionality of the IBM information management software portfolio. For decades, System z has proven its ability to manage vast amounts of mission-critical data for many companies throughout the world; your data is safe on System z. The available information management functionality on System z has grown from database management systems to a full stack of solutions including solutions for content management, master data management, information integration, data warehousing, and business intelligence and analytics. The availability of Linux® on System z provides an excellent opportunity to place certain components in an easy-to-manage and scalable virtualized Linux server, while benefitting from the System z hardware strengths. DB2 on z/OS can remain the operational data store and the underlying database for the data warehouse. The next generation of System z is growing into a heterogeneous architecture with which you can take advantage of System z-managed "accelerators" running on IBM System x® or IBM Power Blades. The first of these accelerators is the IBM Smart Analytics Optimizer for DB2 for z/OS V1.1, an "all-in-one" solution in which System z, z/OS, DB2 on z/OS, an IBM BladeCenter®, and IBM storage work together to accelerate certain queries by one to two orders of magnitude. With the IBM Smart Analytics Optimizer, slices of data are periodically offloaded from DB2 on z/OS to the BladeCenter. After a query is launched against that data, it will automatically run against the data kept on the BladeCenter. The BladeCenter will process the query an order of magnitude faster than DB2 on z/OS, because all data is cached in internal memory on the BladeCenter and special compression techniques are used to keep the data footprint small and efficient. As a solid information management architecture ready for the future, System z has it all.

The IBM® DB2® Analytics Accelerator Version 3.1 for IBM z/OS® (simply called Accelerator in this book) is a union of the IBM System z® quality of service and IBM Netezza® technology to accelerate complex queries in a DB2 for z/OS highly secure and available environment. Superior performance and scalability with rapid appliance deployment provide an ideal solution for complex analysis. In this IBM Redbooks® publication, we provide technical decision-makers with a broad understanding of the benefits of Version 3.1 of the Accelerator's major new functions. We describe their installation and the advantages to existing analytical processes as measured in our test environment. We also describe the IBM zEnterprise® Analytics System 9700, a hybrid System z solution offering that is surrounded by a complete set of optional packs to enable customers to custom tailor the system to their unique needs..

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.

The IBM® DB2® Analytics Accelerator Version 2.1 for IBM z/OS® (also called DB2 Analytics Accelerator or Query Accelerator in this book and in DB2 for z/OS documentation) is a marriage of the IBM System z® Quality of Service and Netezza® technology to accelerate complex queries in a DB2 for z/OS highly secure and available environment. Superior performance and scalability with rapid appliance deployment provide an ideal solution for complex analysis. This IBM Redbooks® publication provides technical decision-makers with a broad understanding of the IBM DB2 Analytics Accelerator architecture and its exploitation by documenting the steps for the installation of this solution in an existing DB2 10 for z/OS environment. In this book we define a business analytics scenario, evaluate the potential benefits of the DB2 Analytics Accelerator appliance, describe the installation and integration steps with the DB2 environment, evaluate performance, and show the advantages to existing business intelligence processes.

This IBM® Redbooks® publication helps you install, configure, and maintain the IBM zEnterprise 196 server. The z196 offers new functions that require a comprehensive understanding of the available configuration options. This book presents configuration setup scenarios, and discusses implementation examples in detail. This book is intended for systems engineers, hardware planners, and anyone who needs to understand IBM System z® configuration and implementation. Readers should be generally familiar with current IBM System z technology and terminology. For details about the z196 server, see IBM zEnterprise System Technical Introduction, SG24-7832 and IBM zEnterprise System Technical Guide, SG24-7833.

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.

This IBM® RedpaperTM publication presents the process and steps that were taken to move from an R language forecasting solution to an IBM SPSS® Modeler solution. The paper identifies the key challenges that the team faced and the lessons they learned. It describes the journey from analysis through design to key actions that were taken during development to make the conversion successful. The solution approach is described in detail so that you can learn how the team broke the original R solution architecture into logical components in order to plan for the conversion project. You see key aspects of the conversion from R to IBM SPSS Modeler and how basic parts, such as data preparation, verification, pre-screening, and automating data quality checks, are accomplished. The paper consists of three chapters: Chapter 1 introduces the business background and the problem domain. Chapter 2 explains critical technical challenges that the team confronted and solved. Chapter 3 focuses on lessons that were learned during this process and ideas that might apply to your conversion project. This paper applies to various audiences: Decision makers and IT Architects who focus on the architecture, roadmap, software platform, and total cost of ownership. Solution development team members who are involved in creating statistical/analytics-based solutions and who are familiar with R and IBM SPSS Modeler.