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Data Garbage In – Data Garbage Out

by Jodee Hale-Schmid

November 10, 2010

Authored by Ashvinder Rana, Data Migration Lead, Utopia, Inc.


“Garbage In – Garbage Out!” I know we have all heard and used this term countless number of times! But are we really able to put the true meaning and implication of the phrase across to various clients/customers that we work with on various ERP implementation projects?

More commonly termed as GIGO, yes, “garbage in – garbage out” is what the result will equate to, if the quality of data is not good. Quite often, on projects we start off on a good note by executing detailed data profiling, generating reports on data quality for the customers. But during the course of a project, the data cleansing activities are not prioritized enough. While, in the hustle bustle of meeting the project timelines and milestones, we manage to execute and implement the data mapping of various business objects to its entirety. However, are we able to deliver 100% accuracy on the credibility and usability of the converted data? A question that we all silently know the answer to!

As data management experts, we should only continue to recommend the best practices for data quality, including data standardization and perhaps even recommending to the customer on planning and budgeting for a pool of resources that are dedicated towards the continuous data cleansing efforts through the duration of an ERP implementation project. This can only add value to the project and business during and after. 


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