These best practices papers present advice on ways you can leverage IBM® InfoSphere™ Information Server to satisfy key business requirements for your information integration solutions. These articles are authored by leading experts in IBM's InfoSphere development and services teams.

Each best practice paper is designed to provide practical guidance for common InfoSphere implementation scenarios. By applying these recommendations, you may improve the value of your InfoSphere solution and align yourself with IBM's technical direction for InfoSphere.

Additional best practices articles are in development and will be published as they become available.

• Leverage a ripple-down rules framework in InfoSphere QualityStage standardization rule set development (April 2012)
  by Rachit Arora and Hima Karanam
  
  

  Learn how improving data quality is a major challenge for many organizations. IBM InfoSphere DataStage and QualityStage help organizations with the process of cleansing enterprise databases. This article looks at address standardization and shows how you can use the advantages of a ripple-down rules (RDR) framework in QualityStage rule set development, lowering the manual effort required to rewrite or migrate rules from one data source to another. You'll find that RDR makes the creation, management, and maintenance of QualityStage rule sets a lot easier.

• Integrate InfoSphere MDM Server for PIM with InfoSphere QualityStage to standardize product data (April 2012)
  by Amit Malla and Manasa Rao
  
  

  Learn how you can ensure data quality by implementing validation rules for product data at various levels (such as attribute, item, or category) in IBM InfoSphere Master Data Management Server for Product Information Management (MDM Server for PIM). However, rules incur processing overhead during large imports or during the data reconciliation process. InfoSphere QualityStage, on the other hand, is a component of IBM InfoSphere Information Server that can profile and standardize data, eliminate duplicates from data sources, and ensure survival of the best-of-breed records from a duplicate set. This article looks at a real-time integration between MDM Server for PIM and QualityStage to ensure quality of product data through standardization processes implemented in QualityStage.

• Optimize InfoSphere DataStage jobs with Netezza Connector using InfoSphere DataStage Balanced Optimization (April 2012)
  by Ritika Maheshwari
  
  

  Learn how to use a DataStage extension called IBM InfoSphere DataStage Balanced Optimization to rewrite a DataStage job to enhance performance by sharing or redistributing the processing load among InfoSphere DataStage and the source and target databases. Special emphasis has been given to features unique to Netezza Connector, including Action Column, Unique Key Column for update support, and Temporary Work Table. The article also discusses additional features available in the InfoSphere Information Server V8.7 release, including the Filter stage, and multiple output links of Copy, Filter, and Transformer stages.

• InfoSphere best practices: Performance guidelines for IBM InfoSphere DataStage jobs containing sort operations on Intel Xeon servers (April 2012)
  
  

  Learn the best practices for tuning IBM InfoSphere DataStage jobs on Intel Xeon servers. Sort operations are I/O-intensive operations and can cause significant I/O load on the temporary or scratch file system. This article provides recommendations that will reduce the bandwidth demand placed on the scratch storage I/O system by sort operations. These I/O reductions result in improved performance that can be quite significant for systems where the scratch I/O storage system is significantly undersized in comparison to the compute capability of the processors.

• Best practices and performance guidelines for IBM InfoSphere Information Server running on Intel Xeon servers providing connectivity to IBM Netezza Data Warehouse servers (March 2012)
  by Garrett Drysdale, Sriram Padmanabhan, Branislav Barnak, Brian Caufield, Tony Curcio, Jon Deng, David Qiang Li, Lu Liang, Mi Wan Shum, John Skier, and Samuel Wong
  
  

  Learn about comprehensive integration that is now available between IBM InfoSphere Information Server and IBM Netezza data warehouse appliance. The authors summarize the results of benchmarking tests focused on load and unload performance when using the InfoSphere Information Server connector for IBM Netezza. One of a series of papers that provide IBM InfoSphere Information Server customers with helpful performance tuning guidelines for deployment on Intel Xeon processors, the article shows how to best utilize the IBM Netezza connector to optimize performance between IBM Netezza appliances and Information Server.

• Using pre-built rule definitions with IBM InfoSphere Information Analyzer (December 2011)
  by Harald Smith
  

  A key challenge in assessing and monitoring information quality is starting the process to validate key business requirements. Rather than start off with a blank slate, this article includes and shows how to use pre-built rule definitions to get underway. Learn how to understand the available content, how to use that information to address common data quality conditions, and how to then import it into your Information Analyzer environment to accelerate rule development and assessment.

• Designing a topology for InfoSphere Information Server (October 2010)
  by Martin Breining, Thomas Cherel, and Jean-Claude Mamou
  

  This article provides a blueprint on how to design a topology for InfoSphere Information Server based on a set of available resources (such as hardware and skills) and a set of functional requirements (such as high availability, scalability, and simplicity). Each of these variables represents different dimensions of a topology. A change in any of these dimensions can greatly impact the resulting topology, so identifying and quantifying these dimensions is important. After these dimensions are defined, a particular topology, or perhaps a family of topologies, will emerge when you follow the guidelines outlined in this article.

• Asset interchange in InfoSphere Information Server (October 2010)
  by Cassio dos Santos
  

  InfoSphere Information Server is a suite of components that together provide a single unified platform that enables companies to understand, cleanse, transform, and deliver information. Different kinds of metadata assets are created by the various Information Server components and are shared through the metadata repository, for example DataStage® jobs and Information Analyzer projects. Asset interchange refers to the functionality that moves metadata between different metadata repositories, across enviroments such as development, test, and production. In this article, you'll learn how to effectively use the Information Server asset interchange tools.

• Using InfoSphere Information Analyzer data quality rules in a productive environment (October 2010)
  by Yannick Saillet
  

  This article describes tips and tricks you can use to increase your productivity when developing InfoSphere Information Analyzer data quality rules. It shows you how to use various options that are available to move a data quality project or individual data rules to a different environment, and how to create reusable project templates that you can then easily deploy, how to archive data rule definitions in a source control repository, and how to trigger the execution of data rules from a third-party environment.

• Understand the resource usage of data quality rules in IBM InfoSphere Information Analyzer (October 2010)
  by Yannick Saillet
  

  This article helps you understand the execution of data quality rules in IBM InfoSphere Information Analyzer with a focus on performance. You'll get an overview of how using various types of tests, functions, and options that are available for data rules affects performance and disk usage. Finally, the author provides recommendations on how to optimize the resource usage of data rules.

• Use InfoSphere Information Analyzer data classification to understand the quality of your data (October 2010)
  by Ed Foley
  

  Learn how to use data classification in InfoSphere Information Analyzer. This article describes data classification schemes, classification categories, system capabilities, and how you can effectively control the data classification results. The article also explains how to use data classification to determine subsequent analysis requirements and to support your overall data quality assessment.

• Use CSV and XML import methods to populate, update, and enhance your InfoSphere Busniess Glossary content (October 2010)
  by Shlomit Becker and Yair Rinot
  

  InfoSphere Business Glossary enables you to use a controlled vocabulary to create, manage, and share standard definitions of business and organization concepts. Version 8.1.1 of the product introduced new CSV and XML import and export methods for populating a business glossary. This tutorial provides technical instructions, tips, and examples to help you implement these new features to efficiently create a business glossary.

Back to top