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Maximizing Performance of IBM DB2 Backups
Analytics

Web Doc, published 21 Oct 2016

This IBM® Redbooks® Analytics Support Web Doc describes how to maximize the performance of IBM DB2® backups. Backing up a database is a critical part of any disaster recovery plan. Making sure that the backup completes in a reasonable time frame means that there is always a valid backup available in case of emergency. This document describes the following elements that are critical to good backup performance:
- The backup process model
- Basic backup performance concepts
- Backup performance considerations
- Monitoring backup performance with the DB2_BAR_STATS ... [more]


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Introduction to R in IBM SPSS Modeler
Analytics

Redpaper, published 14 Oct 2016

This IBM Redpaper™ publication focuses on the integration between IBM® SPSS® Modeler and R. The paper is aimed at people who know IBM SPSS Modeler and have only a very limited knowledge of R. Chapters 2, 3, and 4 provide you with a high level understanding of R integration within SPSS Modeler enabling you to create or recreate some very basic R models within SPSS Modeler, even if you have only a basic knowledge of R. Chapter 5 provides more detailed tips and tricks. This chapter is for the experienced user and consists of items that might help you get up to speed with more detailed ... [more]


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A Guide to Lean Healthcare Workflows
Analytics

Redpaper, published 26 Aug 2015, last updated 11 Oct 2016

Is Lean a fit for your healthcare organization? Various methodologies can be used to help organizations achieve their objectives depending on their criteria: lowest risk of failure, fast to resolution, or lowest cost for deployment. But what every organization should consider is which methodology will have the greatest impact. Lean, a systematic approach to understanding and optimizing processes, may be the fit for your organization. Learn more in this new IBM® Redpaper™ publication, A Guide to Lean Healthcare Workflows, by Jerry Green and Amy Valentini of Phytel (An IBM ... [more]


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IBM Data Server Manager Overview and Performance Analysis
Analytics

Web Doc, published 4 Oct 2016

IBM® Data Server Manager is a web-based, integrated database management tools platform that manages IBM DB2® for Linux, UNIX, Windows, and IBM z/OS® databases. With IBM Data Server Manager, you can monitor, analyze, tune, and administer DB2 databases. This IBM Redbooks® Analytics Support web doc describes ways to do performance analysis that can be used to drill down into SQL performance to understand the underlying issues and take corrective measures to optimize the outcome. This document provides an overview of Data Server Manager and includes information that helps Data Server Manager ... [more]


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Assessing Hardware Failures on IBM PureData System for Analytics N2001, N2002, and N3001
Analytics

Web Doc, published 29 Sep 2016

This IBM Analytics Support Wed Doc describes possible hardware component failures on IBM PureData System for Analytics, their effect on the system, and its criticality and consequences if multiple components fail. This document also describes the architecture of IBM PureData System for Analytics to clarify the relationships between components. It also provides guidance on replacement scenarios. This information is intended to help users correctly respond to failures and open problem management records (PMR) with an accurate level of severity. This document provides information to help you ... [more]


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Changing Physical Disk Storage in IBM DB2 pureScale: A Practical Example
Analytics

Web Doc, published 22 Sep 2016, last updated 26 Sep 2016

IBM® DB2® pureScale® provides continuous availability with multiple active servers that share a common set of disk storage subsystems. DB2 pureScale includes multiple components for high availability (HA), such as IBM Tivoli® System Automation (TSA) and IBM General Parallel File System (IBM GPFS™) for clustered file systems. Like any component in an IT infrastructure, DB2 pureScale eventually might require a migration to meet the demands of upgraded hardware and software. Database administrators, operating system administrators, and system administrators working with DB2 pureScale in ... [more]


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IBM BigInsights Security Implementation: Part 1 Introduction to Security Architecture
Analytics

Web Doc, published 25 Aug 2016

Big data analytics involves processing large amounts of data that cannot be handled by conventional systems. The IBM® BigInsights® platform processes large amounts of data by breaking the computation into smaller tasks that can be distributed onto several nodes. As this platform is shared by users in different roles (developers, analysts, data scientists, and testers), it introduces the challenge of provisioning access and authorization to the cluster and securing the data. Big data platforms are an amalgamation of several individual components that are still evolving, and are based on the ... [more]


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IBM Data Engine for Hadoop and Spark
Power Systems

Redbooks, published 24 Aug 2016

This IBM® Redbooks® publication provides topics to help the technical community take advantage of the resilience, scalability, and performance of the IBM Power Systems™ platform to implement or integrate an IBM Data Engine for Hadoop and Spark solution for analytics solutions to access, manage, and analyze data sets to improve business outcomes. This book documents topics to demonstrate and take advantage of the analytics strengths of the IBM POWER8® platform, the IBM analytics software portfolio, and selected third-party tools to help solve customer's data analytic workload requirements. ... [more]


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Apache Spark Implementation on IBM z/OS
Analytics

Redbooks, published 13 Aug 2016

The term big data refers to extremely large sets of data that are analyzed to reveal insights, such as patterns, trends, and associations. The algorithms that analyze this data to provide these insights must extract value from a wide range of data sources, including business data and live, streaming, social media data. However, the real value of these insights comes from their timeliness. Rapid delivery of insights enables anyone (not only data scientists) to make effective decisions, applying deep intelligence to every enterprise application. Apache Spark is an integrated ... [more]


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Enabling Real-time Analytics on IBM z Systems Platform
Analytics

Redbooks, published 8 Aug 2016

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 ... [more]


The above is a list of IBM Redbooks and Redpapers on Analytics, showing most recently published first. Most of these publications are available in Adobe PDF format and may be viewed online or downloaded for offline viewing and printing. Read our How to buy page for details on how to order a bound hardcopy.



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