PROMPT 1:
We have received an export from an IT MSP's financial reporting system which contains customer invoices over a period of time. The data has some structure, but we need to refine the revenue mapping to enable proper analysis of trends. In essence, we need to turn this transaction data dump into a clean revenue cube. We also need to identify any errors or inconsistencies in the data to ensure that any mapping is done correctly.
I have 4 tasks I’d like you to help me complete before we start the tagging:
1. Tell me about the data - how many unique customers, types of revenue lines that seem to appear, any other important bits of information that is contained in the data that could be useful for an analysis of the business’ performance, etc. From our understanding of the business so far there will likely be revenue related to managed services, license subscriptions, consulting, and hardware.
2. Identify any inconsistencies in the data that we might need to address before starting revenue mapping and categorisation.
3. Identify which column(s) of data we should use as the basis for mapping and categorising the data. How is it structured at the moment? What will we need to change to help us get to some sensible buckets?
4. Tell me what approach you think we should take to fixing inconsistencies found and to the tagging exercise.

PROMPT 2:
Proceed, but please make a new sheet, remove duplicates from the clean data and to log duplicates in a new tab. Make sure to remove any spare rows from the new output table