Data Sufficiency
Information should fill data gaps, and be adequate to address the research issue - more may not be good and result in loss of relevance. Some of the measurable parameters are sample size, level of detail or aggregation and time horizon. Redundancy checks are to be done to ensure no overlaps, and optimal utilization of data resources
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