Database Sales Data Structuring
Budget: ₹100 – ₹400 INR
I have a collection of sales records sitting in our databases that I need transformed into clear, well-formatted spreadsheets. Your job is to pull the data directly from the database tables, filter for the sales-related fields, and lay everything out so it reads instantly at a glance.
The spreadsheets must focus on the customer details attached to each sale—names, contact information, and any other customer-level data stored alongside the transactions—so our marketing team can slice and segment the information without further cleanup. Beyond the required customer columns, feel free to arrange supplementary fields (dates, product SKUs, totals, etc.) where they make logical sense, but the priority is a tidy, analysis-ready sheet that follows consistent column naming, date formatting, and no blank rows.
Deliverables
• Export/query scripts (SQL or the tool of your choice) so we can reproduce the pull
• One master spreadsheet and separate tab(s) or file(s) if the data logically splits (e.g., region, channel)
• Basic data validation rules built in (drop-downs for states, email format checks, etc.)
• Quick read-me summarising the extraction steps and any transformation logic
I’ll provide you with database credentials and a sample ER diagram once we start. If you have experience automating future refreshes—using SQL views, Power Query, or Python—that’s a welcome plus. Let me know how you plan to tackle the extraction and formatting, and roughly how long you’ll need once access is granted.
The spreadsheets must focus on the customer details attached to each sale—names, contact information, and any other customer-level data stored alongside the transactions—so our marketing team can slice and segment the information without further cleanup. Beyond the required customer columns, feel free to arrange supplementary fields (dates, product SKUs, totals, etc.) where they make logical sense, but the priority is a tidy, analysis-ready sheet that follows consistent column naming, date formatting, and no blank rows.
Deliverables
• Export/query scripts (SQL or the tool of your choice) so we can reproduce the pull
• One master spreadsheet and separate tab(s) or file(s) if the data logically splits (e.g., region, channel)
• Basic data validation rules built in (drop-downs for states, email format checks, etc.)
• Quick read-me summarising the extraction steps and any transformation logic
I’ll provide you with database credentials and a sample ER diagram once we start. If you have experience automating future refreshes—using SQL views, Power Query, or Python—that’s a welcome plus. Let me know how you plan to tackle the extraction and formatting, and roughly how long you’ll need once access is granted.