Regarding online transaction processing (OLTP) workloads, IBM® z Systems™ 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 archived if most of the data already resides on z Systems platforms, although adding external data (like from social sources) poses no problem at all.

If you want only an overview of enabling real-time analytics on IBM z Systems platforms and how it might fit into your organization, read Chapter 1, “Executive overview” on page 1.

This book was produced by a team of specialists from around the world working at the International Technical Support Organization, Poughkeepsie Center.

Lydia Parziale is a Project Leader for the ITSO team in Poughkeepsie, New York, with domestic and international experience in technology management including software development, project leadership, and strategic planning. Her areas of expertise include business development and database management technologies. Lydia is a certified PMP and an IBM Certified IT Specialist with an MBA in Technology Management and has been employed by IBM for over 25 years in various technology areas.

Oliver Benke is a Software Engineer at the IBM Laboratory in Boeblingen, Germany where for 17 years he has worked on various projects. In the last several years, he has developed prototypes for SPSS Modeler Scoring Adapter for z Systems, DB2 Analytics Accelerator accelerator-only tables and IBM Netezza® Analytics integration for in-database modeling, including related performance work, evaluations, and early customer validation.

Willie Favero was an IBM Senior Certified IT Software Specialist and subject matter expert (SME) on DB2 for z/OS with the IBM Silicon Valley Lab z Systems Analytics SWAT Team. He has 40 years of experience working with databases, including 31 years working with DB2. Willie is a highly sought-after speaker for international conferences and user groups. He also publishes articles and white papers, contributes to numerous IBM Redbooks publications, and has a top technical (DB2) blog on the Internet.

Ravi Kumar is a Senior Managing Consultant at IBM (Analytics Platform, North American Lab Services). Ravi is a Distinguished IT Specialist (Open Group certified) with more than 23 years of IT experience. He has a Master’s in Business Administration (MBA) degree from University of Nebraska, Lincoln. He has contributed to seven other Redbooks publications, in the areas of Database, Analytics Accelerator, and Information Management tools.

Steven LaFalce started his career at IBM in 2002 working on design, testing, and qualification of z Systems memory subsystems. He later joined z Systems Hardware Product Engineering working on the central electronic complex subsystem. In his current role, he is working in z Systems Field Technical Enablement on business analytics projects.

Thanks to the following people for their contributions to this project:

Here’s an opportunity to spotlight your skills, grow your career, and become a published author—all at the same time! Join an ITSO residency project and help write a book in your area of expertise, while honing your experience using leading-edge technologies. Your efforts will help to increase product acceptance and customer satisfaction, as you expand your network of technical contacts and relationships. Residencies run from two to six weeks in length, and you can participate either in person or as a remote resident working from your home base.

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