Q. What is the "clean as you go" approach to data cleansing in the context of a data warehouse?

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Q. What is one of the drawbacks of the "clean as you go" approach to data cleansing?

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Q. What principle should be applied when determining the extent of data cleansing for a data warehouse?

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Q. What fundamental question must be answered when deciding which data to cleanse?

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Q. Where in the data flow process can data cleansing be applied?

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Q. What is a drawback of cleansing data in the staging area?

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Q. Why is cleansing data in the source systems a complex task?

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Q. What factors should you consider when deciding whether to use vendor tools, integrate cleansing toolkits with ETL tools, or use in-house programming for data cleansing?

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Q. What is the first step in assessing the extent of data pollution before applying data cleansing techniques?

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Q. How can you detect the presence and extent of data pollution in your environment?

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Q. What is the purpose of a data quality framework?

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Q. Who should be responsible for data quality in source systems?

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Q. What is the main challenge in operational systems regarding data quality responsibilities?

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Q. What is the role of a steering committee in data quality initiatives?

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Q. What responsibilities does a Data Expert have in the data quality framework?

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Q. What is the role of a Data Correction Authority in the data quality framework?

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Q. What factors should determine how much data to cleanse in a data warehouse?

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Q. How should you prioritize data elements for cleansing in the data warehouse?

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Q. How should you handle external data obtained for the data warehouse in terms of data quality?

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Q. What is the first step in the overall data purification process?

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