I evaluate each dataset's credibility, context, and source to favor clarity in conflicting data. Cross-referencing and pattern-finding reveal basic facts. I use ambiguity to gain insight and hypothesize until I find a solution reconciling the differences.

"Clarity comes from understanding the story behind the data." When faced with conflicting data sources, start by validating the credibility of each source. Check for differences in data collection methods, time frames, or reporting standards that may cause inconsistencies. Be sure to review the process that supports the data is aligned with what you are defining the problem. Identify key metrics that align with your problem solving goals, prioritizing data most relevant to the issue at hand. Use statistical techniques like outlier detection or trend analysis to uncover context and insights that numbers alone can't reveal. Resolving ambiguity requires combing data validation with informed interpretation to drive accurate decisions.