While a traditional data warehouse stores data in files or folders, a data lake uses a flat architecture to store data.
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Q44: A data lake is a storage repository
Q45: Many organizations find themselves in the position
Q46: Many firms complete data quality audits to
Q47: Source data identifies the primary location where
Q48: Competitive monitoring can compare two or more
Q50: In a data warehouse, information cleansing occurs
Q51: Duplicate data, inaccurate data, misleading data, and
Q52: Dirty data is erroneous or flawed data.
Q53: ETL stands for extraction, transformation, and loading.
Q54: Comparative analysis can help managers with competitive
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