1.The Vendor column contains the names of the vendors from which the purchases were made. Use a fuzzy matching algorithm to find any vendors with similar names. Do you suspect any purchases were made from phantom vendors?
2. Find any vendors who are charging too much for their product compared with other vendors. In addition to average prices for each product and vendor, do you see any increasing trends that might indicate kickbacks?
3.Calculate the average product price paid by purchaser. For example, calculate the average price paid for All Purpose Wipers when Jose, Sally, and Daniel are purchasing. Compare these average prices. Do you see any issues to search further?
4.Verify that all purchases are included in the data set. If a purchase was left out, its ID would be removed from the sequential list of IDs. Compare each ID and ensure the column increases by one in each record.
5.Verify the values in the Quantity and Total columns. Are any missing or abnormal values present?
6.Analyze the Product Price column from each company using Benfords Law. Analyze only the first digit of the column. On average, do any of the vendors stand out? In other words, are the transactions from any vendor not matching Benfords Law?
