Parse and compare Excel data in different files and show differences -- Use Perl, Python or any scripting language -- Needs to run on Linux or Windows

RULES: Do NOT ask us what our budget is. Bid exactly what you will charge us. Your feedback MUST be greater than 5. Your completion rate MUST be better than 65%. DO NOT waste our time if you do not meet the above criteria. If you do, we will flame you as a result. Respect our rules and we will respect you. BRIEF: I have numerous Excel files that contain about 65,000 rows of customer data each. Here are the column names: State txtRentalOrderId txtCreationDate txtCustomerName txtContactName txtTerm txtFromDate txtSalesperson txtToDate txtStatus txtAssetList txtOrderTotal Each file: a) is saved in the format of: "Orders - June 7 [login to view URL]" (where the date part changes with each save and depends on the date the file is saved; right now I am trying to generate a new file 3 times a week). b) contains details of client orders. The Unique ID for each order can be generated by merging column "State" & "txtRentalOrderid" using the concatenate function. c) is a representation/snapshot of all orders at a given point in time. Each older file (i.e "Orders - June 1 [login to view URL]" contains data that is a subset of the file after it, i.e. "Orders - June 7 [login to view URL]". Each newer file contains all data from the previous file PLUS all data that has been generated since. SOLUTIONS I AM SEEKING: 1) Determine which order ("txtRentalOrderId") has changed the sales exec ("txtSalesperson") associated with it over time. For example, a particular client has had an open order in the system with Mike. Mike quits the company and assigns all his orders to Jack. I now need to track which orders changed hands and who they were assigned to. This is particularly important as Mike and Jack were good friends at work. So by assigning all his likely bookings to Jack, Mike is giving Jack an unfair advantage over the rest of the team. 2) Determine which order ("txtRentalOrderId") had its client ID changed ("txtCustomerName"). For example, "txtCustomerName" was "Lenovo" to start with. Then, the sales exec who was dealing with Lenovo was told by its rep that they will not proceed with their booking due to a change in requirements. Now, if the sales exec closes the quote as LOST, it will affect their conversion (one of the KPIs). So instead of marking the booking as LOST, the sales exec just changes the "txtCustomerName" to a different client (i.e. HP) when a new quote request comes through from HP (instead of creating a totally new quote in the name of HP). That way, the sales exec can keep on changing the "txtCustomerName" until some client agrees to the quote and the quote is closed as WON. Such behaviour manipulates the conversion rate of the sales exec in question and makes it seem that they are winning a lot more quotes. 3) Determine which order ("txtRentalOrderId") had its start date changed ("txtFromDate"). Sales execs should only be allowed to change the start date of a quote once. For example, a client initially indicates that they want to start their event on July 20. So the entry in the "txtFromDate" column becomes "July 20". However, closer to the date, the client decides to change the start date to August 20. The sales exec then changes the "txtFromDate" to August 20. However, closer to the date, the client once again is undecided and changes the date to October 20. At this point, the sales exec should close the quote as LOST and move on. However, what I am seeing is that the sales exec keeps on pushing the date forward endlessly. This protects their conversion rate as the quote is not marked as LOST by August 20. INPUT Any number of Excel files OUTPUT Show the results of the comparisons between any files compared. So if we are parsing 20 files, we need to see what changes had occurred over time. (For example, if a particular client had changed hands between 4 different sales people, the output file would show such a change 3 times). START DATE ASAP DEADLINE 1 week MILESTONE RELEASES Released within 24 hours of successful UAT completion. Good luck!