ChatGPT Prompt for Sales Transaction

Sales transaction data is a critical asset for any business, enabling insights into customer behavior, revenue performance, and operational efficiency. However, raw sales data often contains discrepancies and errors that can significantly skew analysis, reporting, and decision-making. To ensure accuracy and reliability, businesses must regularly identify, assess, and clean sales transaction data.

Best Practices

• Establish data quality KPIs (e.g., error rates, completeness scores).
• Set up automated validations at data entry points.
• Perform regular audits and reconciliations.
• Involve domain experts during cleaning for context-aware decisions.
• Implement a data governance framework to sustain long-term data health.

Sales Data Cleaning – Quick Steps

Log – Track all changes made.

Scan – Check for missing, wrong, or duplicate data.

Validate – Ensure totals and fields make sense.

Deduplicate – Remove repeated entries.

Fix – Fill in or correct errors.

Standardize – Align formats (dates, codes, currency).

Reconcile – Match with other systems (CRM, inventory).

ChatGPT Prompt for Sales Transaction

I have a CSV file [insert CSV file] containing sales transaction data from multiple store locations (columns: TransactionID, StoreID, SaleDate, ProductID, Quantity, and Price). Some rows have missing or incorrect StoreIDs, and some of the prices look off. Please outline a step-by-step approach to identify and handle these discrepancies, and provide sample Python code for cleaning tasks like removing or imputing missing StoreIDs and fixing price outliers.

You can also use the search function to find the best prompts for ChatGPT.