Reliable Analytics by Using IBM z13

IBM Redbooks Solution Guide

Published 14 January 2015

Authors: Lydia Parziale

Abstract

Analytics projects mainly draw on mainframe-based transactional data. However, in the last two decades, analytics solutions have been deployed as departmental applications, based on very specific business needs of the requesting department.

This IBM® Redbooks® Solution Guide describes how IBM z13™ can help organizations maximize their current IT investments while adding functionality and improved price and performance with z13 over IBM zEnterprise® EC12 (zEC12. With new z13 features, applications can gain increased throughput for distributed operational business intelligence (BI) and IBM DB2® query workloads, thus saving money in hardware, software, and labor.

Contents

Analytics projects mainly draw on mainframe-based transactional data. However, in the last two decades, analytics solutions have been deployed as departmental applications, based on very specific business needs of the requesting department.

This IBM® Redbooks® Solution Guide describes how IBM z13™ can help organizations maximize their current IT investments while adding functionality and improved price and performance with z13 over IBM zEnterprise® EC12 (zEC12). With new z13 features, applications can gain increased throughput for distributed operational business intelligence (BI) and IBM DB2® query workloads, thus saving money in hardware, software, and labor. The IBM z Systems™ server excels as custodian of the data model, providing an accurate, secure, single copy of information that ensures veracity of the data for reliable analytics and provides centralized control over decision information (see Figure 1).

Figure 1 Centralized control of decision information
Figure 1 Centralized control of decision information
Did you know?

Many new features and functions of IBM z13 can benefit your organization's workloads; here are several:

  • Addition of SIMD-MASS and ATLAS libraries for IBM z/OS® and Linux on z Systems: single-instruction, multiple-data (SIMD), Mathematical Acceleration Subsystem (MASS ), and Automatically Tuned Linear Algebra Software (ATLAS)
  • Allow construction of richer, more complex analytics models from independent software vendors (ISVs) and analytics products from IBM Software Group that exploit SIMD to provide better accuracy of insight
  • Allow Analytics workloads to be ported from IBM Power Systems™ and x86 with ease which can accelerate analytics to provide speedier business insight
  • Increase in programmer productivity of ISV and customer analytics workload development leading to rapid business insight generation for a competitive advantage
  • Simultaneous multithreading (SMT) allows processing of more workloads in the same amount of time, together with IBM z Integrated Information Processor (IBM zIIP) and Integrated Facility for Linux (IFL)
  • Enterprise security (built in, one-of-a-kind cryptographic and encryption functions) maintaining data securely, inside the platform.
  • Large memory support (for z/OS and DB2).


Business value

Data is the most important resource of any organization. The way data is viewed by an organization depends on the organization's needs and falls into three categories:
  • Real-Time View: The operational systems that house the books of record. These data sources are critical to day-to-day business processes (systems of record).
  • Historical View: Data warehouses, marts, and others. These data sources support reporting and predictive model creation.
  • Predictive View: Analytics models and software. These are the tools that deliver actionable insights from data.

Business-critical analytics solutions depend on where source data resides. IBM z Systems servers deliver a single workload-optimized system for both operations and analytics by integrating and managing these real-time, historical, and predictive views of data.

Real-time analytics-based decisions are a top priority for outperforming organizations, and this requires tight integration with operational data. When data resides on disparate and distant servers, certain problems might be encountered:
  • Significant effort is spent for copying and moving data, resulting in veracity and security issues.
  • Business has no access to the most current view (data in systems of record is in constant change).
  • Complicated, bifurcated infrastructure requires multiple skill types.
  • No single point of management exists.
  • Business continuity concerns exist.

With keeping data and analyzing it at the source, several advantages can be identified:
  • Less movement of data results in higher quality and less risk of loss.
  • Integration with core systems delivers the most accurate view to the business.
  • Integrated architecture leverages existing environment.
  • Single view simplifies management.
  • Business continuity is inherited from core systems.

IBM z Systems and, in particular, IBM z13 with its new features and functions enable all of the advantages of improved performance and lowered costs, providing real-time analytics-based decisions.


Solution overview

z Systems analytics enables organizations to improve performance and lower cost by bringing the analytic processing to where the data resides (see Figure 5-6). Organizations can maximize their current IT investments while adding functionality and improved price and performance with z13 over zEC12. With new z13 features, applications can gain increased throughput for distributed operational business intelligence (operational BI), DB2 query workloads, thus saving money (hardware, software, labor).
Businesses today need to make better, faster decisions based on reality rather than on assumptions; that means taking control of enormous volumes of data. The combination of DB2 Analytics Accelerator, IBM Cognos® BI, and IBM SPSS® on the z13 platform gives that control and opens a whole different way of doing things (see Figure 2).

Figure 2 IBM z13 and control of large volumes of data
Figure 2 IBM z13 and control of large volumes of data

The main strengths of the z Systems platform (virtualization, scalability, elasticity, security, and resiliency) provide a robust infrastructure, capable of managing enormous volumes of data. In this solution, because core data stays on z13, less movement of data occurs, resulting in higher quality and less risk of loss.


Solution architecture

Using a mobile application as an example (Figure 3), when the user signs on, the transaction flows through an IBM MobileFirst Platform Server running on Linux on z Systems to an LDAP server on z/OS to validate the user’s signon credentials. After successful validation, the transaction then proceeds through the z/OS transaction environment where all of the data resides in DB2 z/OS. IBM CICS® transactions are also processed in the same z Systems environment and all of the analysis is performed without moving any data, resulting in extremely fast performance.

Figure 3 Example z13 solution architecture for a mobile application
Figure 3 Example z13 solution architecture for a mobile application


Usage scenarios

Using Figure 3 as an example, we describe a banking scenario that shows how z Systems can optimally integrate transactions and analytics through the use of real-time fraud detection.
A banking user sets up mobile access to multiple accounts, some of which are the user’s own, some of which the user has access to but are owned by others. This user is travelling abroad on business and wants to initiate some funds transfers through a personal mobile device. The user has two accounts and wants to transfer money from one account to the other. The entire transaction is extremely fast; all operational analytics reside on the z Systems and can take place at banking transaction speeds.


Integration

Also, Figure 3 shows how z Systems can optimally integrate transactions and analytics through the use of real-time fraud detection, using IBM z13, a Linux on z Systems IBM MobileFirst Platform Server, CICS, SPSS Predictive Analytics Enterprise software, DB2 for z/OS, and the IBM Business Process Manager.

In the usage scenario, when the user signs on, the transaction flows through an IBM MobileFirst Platform Server running on Linux on z Systems to an LDAP server on z/OS to validate the user’s signon credentials. After successful user login, the z/OS banking transaction is initiated and the data for input to the three predictive models is prepared. These predictive models are run and the current transaction pattern is evaluated. The demonstration models determine if the current transaction is aligned with previous patterns for this user with respect to transfer amounts, accounts used, failed login attempts, and so on. The models are run within the DB2 z/OS environment simply as SQL calls with no movement of data.

Next, the input to the business rule is prepared, and the business rule is invoked. All of the data resides in DB2 z/OS, and all of the analysis is performed without moving any data, resulting in extremely fast performance. If the fraud risk is determined to be “low,” then two CICS banking transactions run to complete the transfer. If the fraud risk is determined as "high," then the transaction does not complete and a message is returned to the user indicating a reason for the incompletion. All of this happens in real-time.


Supported platforms

The following products mentioned in this solution guide run on IBM z13:
  • DB2 for z/OS
  • CICS
  • IBM MobileFirst Platform Server (supported on IBM WebSphere® Application Server installed on Linux on z Systems only)
  • IBM SPSS Predictive Analytics Enterprise
  • IBM Business Process Manager Advanced for z/OS


Ordering information

Contact your IBM representative for IBM z13 ordering information.


Related information

For more information, see the following documents:


Special Notices

This material has not been submitted to any formal IBM test and is published AS IS. It has not been the subject of rigorous review. IBM assumes no responsibility for its accuracy or completeness. The use of this information or the implementation of any of these techniques is a client responsibility and depends upon the client's ability to evaluate and integrate them into the client's operational environment.

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