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How One Analyst Cleaned Messy Vehicle Sales Data to Build a Power BI Dashboard

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A data analyst undertook a project for JCARS Logistics to transform a raw vehicle sales dataset into a functional Power BI management dashboard. The original dataset contained 276 transaction records across 32 columns, covering customers, vehicles, payments, deliveries, and revenue, but was riddled with data-quality issues. Problems identified included duplicate order IDs, inconsistent category labels, invalid ages, mixed date formats, multiple currencies, and text values inside numerical fields. Using Power Query and DAX, the analyst systematically standardized entries — correcting vehicle name spellings, unifying customer type labels, and converting ambiguous unit values — while retaining genuinely uncertain anomalies rather than guessing at corrections. The project highlighted that effective data cleaning requires justification for every change, not just surface-level consistency.

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How One Analyst Cleaned Messy Vehicle Sales Data to Build a Power BI Dashboard · ShortSingh