Currently I am working on a data migration project. I would like to know "What are the aspects that need to be considered during Testing? Also, what are the aspects that need to be addressed in data verification?"
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Our Data Quality team has access to the data (considering that Data Quality, Data Security and Data Governance are all belong to Data Management team): Security matrix for Data Quality team: One of the Data Quality processes is to ensure the security of the data. At the same time Data Governance...
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One of my known acquaintance asked a question to help him with an estimator to logically estimate person hours required for data profiling and cleansing. His company is assuming their data quality will be bad. Now that there is a necessity to check and cleanse data, how to arrive at the man hours...
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How does data quality need to be configured in MDM and what is the relation between them why DQ is used in MDM or can we use powercenter instead of DQ? Kindly somebody explain in detail. Thanks.
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David Loshin has outlined his five steps to an improved data quality assurance plan. Do his five steps cover everything needed? What would be your five (or more) steps?
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Data Quality is a big issue in our firm as we have a lot of applications and inputs into our production databases. Is Microsoft doing anything to help us with data quality, especially on existing data?
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I am tasked with a data integration project and client are asking about a modeling language called JUMP. I found some information on web and on sourceforge for a Jumper project. Has anyone used this or heard of this? Please advise
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