Decide on the data to be used for analysis. Criteria include relevance to the data mining goals, quality and technical constraints such as limits on data volume or data types.
Raise the data quality to the level required by the selected analysis techniques. This may involve selection of clean subsets of the data, the insertion of suitable defaults or more ambitious techniques such as the estimation of missing data by modeling.
Describe the decisions and actions that were taken to address the data quality problems reported during the Verify Data Quality Task. The report should also address what data quality issues are still outstanding.
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