Answer:
However, if the dataset is relatively small, every data point counts. In these situations, a missing data point means loss of valuable information. In any case, generally missing data creates imbalanced observations, cause biased estimates, and in extreme cases, can even lead to invalid conclusions.
It makes data analysis to be more ambiguous and more difficult.
Missing data is simply the same as saying that there are values and information that are unavailable. This could be due to missing files or unavailable information.
A dataset set with missing data means more work for the analyst. There needs to be a transformation in those fields before the dataset can be used.
Generally speaking missing data could lead to bias in the estimation of data.
A data scientist is a data expert who is in charge of data. He performs the job of data extraction, data analysis, data transformation.
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