What is the Data State characteristic associated with a traditional Data Warehouse context in biopharma?
Answer
Processed, Cleaned, Aggregated
A fundamental distinction between a data lake and a data warehouse lies in the state of the data stored within them. Data warehouses are designed to hold data that has already undergone significant transformation. This means the data has been processed, filtered, cleaned, and aggregated to fit a predefined model, making it suitable for standardized business reporting. For instance, in a biopharma setting, a data warehouse typically houses finalized results from clinical trials that have already passed stringent quality checks, ensuring the data is highly reliable for reporting but lacks the raw fidelity needed for deep exploratory research.
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