Initial History Building Algorithm for Slowly Changing Dimensions

Initial History Building Algorithm for Slowly Changing Dimensions

Building initial history for a Data Warehouse is a complex and time consuming task. It involve taking into account of all the date intervals from different source tables during which the source system’s representation of data in any of the tables feeding into the Dimension Tables. So we can imagine the history building complexity and the need of a reusable algorithm.

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Sequence Generator Transformation for Unique Key Generation

Sequence Generator Transformation for Unique Key Generation

The Sequence Generator transformation generates numeric values in a sequential order. Use the Sequence Generator to create unique primary key values, replace missing primary keys, or cycle through a sequential range of numbers. In this tutorial lets see a practical implementation of Sequence Generator transformation.

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5 Restartability Design Pattern for Different Type ETL Loads

5 Restartability Design Pattern for Different Type ETL Loads

Restartable ETL jobs are very crucial to job failure recovery, supportability and data quality of any ETL System.  So you need to build your ETL system around the ability to recover from abnormal ending of a job and restart. So a well designed ETL system should have a good restartable mechanism. In this article lets discuss  ETL restartability approaches to support different type of ETL Jobs such as Dimension loads, Fact Loads etc...

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Informatica Source, Target Command Makes File Processing Easier than Before

Informatica Source, Target Command Makes File Processing Easier than Before

Most of the time when we process flat files in Informatica PowerCenter, we do some kind of file pre or post processing, such as unzip the source file, create a custom header or footer for the target file etc. Such processing is normally done using Unix or Windows scripts, which is called using pre or post  session script. Now Informatica PowerCenter has provided Source, Target Commands to make such processing easy than before.

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Working with Router Transformation and Aggregator Transformation

Working with Router Transformation and Aggregator Transformation

This tutorial shows the process of creating an Informatica PowerCenter mapping and workflow which pulls data from multiple data sources and use Aggregator and Router Transformation. Router transformation can be used to split the data into different groups. And aggregator can be used to summarize data.

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