What makes a bunch of data a good Dataset?
Data Certification: (In progress)
I know I haven't put my certification link, it is because I am learning at my own pace to assess the knowledge well and not actually just sprint the courses and learn nothing in the end. Thank you.
A good Dataset's Metrics
A clean dataset is like a tidy workspace—it’s consistent, accurate, complete, and relevant. Consistency means everything follows a predictable pattern, like dates all using the same format or numbers having the same decimal places. Accuracy is about getting the facts right—no typos, incorrect entries, or outdated values. Completeness makes sure there are no crucial gaps, while relevance means keeping what matters and leaving out what doesn’t.
If you skip cleaning, it’s like trying to solve a puzzle with missing pieces or mismatched colors—it’s confusing and often leads to errors. In my e-commerce project, we ran into trouble when product prices came in mixed currencies—some listed as USD and others in local currency. Without proper cleaning and standardization, our revenue projections were way off, creating a domino effect of incorrect business decisions. Only after aligning and converting everything properly did our analysis give us real insight. So, data cleaning isn’t just a chore; it’s essential for getting results that actually make sense.