Informatica PowerCenter Repository BackUp and Restore

Informatica PowerCenter Repository BackUp and Restore

Informatica PowerCenter administrators regularly backup the repository contents to prevent any data loose due to hardware or software problems. When the repository contents is backed up, it saves all the contents as a binary file which includes all the repository objects such as mapping, sessions, workflows etc. These binary files can be used to restore the contents if in case of any failure. In this article lets discuss the step by step process to backup and restore a PowerCenter Repository.

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SCD Type 3 Implementation using Informatica PowerCenter

SCD Type 3 Implementation using Informatica PowerCenter

Unlike SCD Type 2, Slowly Changing Dimension Type 3 preserves only few history versions of data, most of the time 'Current' and Previous' versions. The 'Previous' version value will be stored into the  additional columns with in the same dimension record.  In this article lets discuss the step by step implementation of SCD Type 3 using Informatica PowerCenter.

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Informatica PowerCenter Installation Known Issues and Solution

Informatica PowerCenter Installation Known Issues and Solution

Since we published the article on informatica installation and configuration, we have been getting questions on different installation issues. So here we thought of writing an article with a consolidated list of issues faced during the installation.  This will be a live article and will be updated as and when we get new issues from the readers.

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Change Data Capture (CDC) Implementation Using CHECKSUM Number

Change Data Capture (CDC) Implementation Using CHECKSUM Number

Typically we use a date column or a flag column to identify the change record for change data capture implementation. But there can be scenarios where you source do not have any columns to identify the changed records, especially when working with legacy systems. Today in this article lets see how to implement Change Data Capture or CDC for such scenarios using checksum number.

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Data Cleansing and Standardization Using Regular Expression

Data Cleansing and Standardization Using Regular Expression

Data Quality is one of the major priorities of any data warehouse or any data integration project. We use different tools for data quality and data standardization implementation. But tools may not be the right solution for small projects which involve couple of data feeds. Regular Expression is an alternative approach for such small projects. In this article lets discuss about data quality implementation using Regular Expression or RegEx in Informatica PowerCenter.

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