Author: Bert Swope

Why Use Materialized Views?

If we consider Materialized Views (MV) in their simplest form, as a point in time stored query result, then materialized views serve two primary purposes Performance Optimization and Semantics Simplification. Performance Optimization There are several ways in which materialized views can improve performance: Reduce Database Workloads: materialized views can reduce

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IBM InfoSphere DataStage Type Conversion Functions

I have started to find type conversion functions, which I searched for and are not included in the IBM list of type conversion function.  So, I’m supplementing the existing IBM list with functions omitted from their list, as I find them, on this page. Notes: Use the type conversion functions

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Where do data models fit in the Software Development Life Cycle (SDLC) Process?

In the classic Software Development Life Cycle (SDLC) process, Data Models are typically initiated, by model type, at key process steps and are maintained as data model detail is added and refinement occurs. The Concept Data Model (CDM) is, usually, created in the Planning phase.   However,  creation the Concept

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IBM InfoSphere DataStage – Parallel Environment Variables

Most of this list of Parallel Environment Variables can be found in the IBM InfoSphere DataStage, Version 11.5 documentation.  However, I have started to find variables,  which I use and are not included in the IBM list.  So, for simplicity, I will make additions and clarifications to the IBM list,

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DataStage Large VARCHAR Performance

To the IBM Infosphere Information Server Parallel Environment Variables, I would add APT_COMPRESS_BOUNDED_FIELDS variable under “Reading and Writing Files” or, perhaps, create a new category called “Performance” for VARCHAR handling.  Using this parameter can help with the overall performance of jobs having a significant number of Varchar fields, especially, large

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