How Power BI Transformed Messy Sales Data for a Kenyan Vehicle Logistics Firm

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JCars Logistics, a Kenyan vehicle sales and logistics company with a main yard in Nairobi and seven branches, undertook a data analytics project using Power BI to extract actionable insights from its sales records. The dataset, sourced from a file called Jcars_data.csv, contained 32 columns with one row per order, covering customer details, vehicle specifications, pricing, and delivery information. A thorough data quality audit revealed several issues including missing headers, blank values in multiple columns, inconsistent date and currency formats, and duplicate categories such as varying spellings of 'Government' across customer type entries. The cleaning process involved setting correct headers, standardising text to proper case, replacing inconsistent category values with uniform labels, and using Trim and Clean functions to remove extra spaces and non-printable characters. A potential outlier — a customer recorded as 121 years old — was also flagged during the audit as part of the broader effort to ensure data integrity before analysis.

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