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How to Implement a Robust Data Quality Solution

Apr 25, 2016 1:53:51 PM   Nancy Couture

Topics: Data Quality, Blog

Data quality is becoming a key concern for companies who rely on data on a daily basis. Without a purposeful data quality program, information becomes inconsistent and unreliable.


This first series of articles describe foundational steps that enable agile data warehouse development. My prior articles published thus far describe how to:

The next focus for setting yourself up for a best in class agile data warehouse environment is to develop a robust data quality solution.

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Data Profiling: What, Why and How?

Apr 25, 2016 1:52:21 PM   Jason Hover

Topics: Data Profiling, Data Quality

Like it or not, many of the assumptions you have about your data are probably not accurate. Despite our best efforts, gremlins inevitably find their way into our systems. The end result – poor data quality – has a host of negative consequences. This brief article will provide an introduction to data quality concepts, and illustrate how data profiling can be used to improve data quality.

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Informatica Data Quality Standards: Tips

Apr 25, 2016 1:35:00 PM   Sally McCormack

Topics: Informatica Data Quality, Data Quality, Blog



When designing rules in Informatica Data Quality, the developers and data stewards will see the same rules. Therefore, it is important to develop consistent naming and coding standards. For example, both the data steward and the developer will understand what “rule_” means while not everyone will understand what “mplt_” means. Therefore, mapplets should be named rule_ if they are used in both the Analyst and Developer tools.


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