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Purpose of Work • We have rough address and company name data and we need to clean it. Unfortunately, this is largely a manual process • To the extent the information is available have: 1) cleaned Company name; 2) Contact name (relatively rare); and 3) Address (all in one column) • The nature of the work—using judgment regarding names and addresses makes only some of this work capable of being automated Requirements to do the work: • Strong familiarity of US addresses • Excellent english • Strong knowledge and comfort with working in Excel • Knowledge of basic Excel short-cuts (cut, paste, etc.) • Ability to work at least 10 hours per week What needs to be done Company Name (column E in yellow) • The company name is currently composed of the website url with the “www” and “.com” truncated. As a result, there are no spaces, when there often should be. •The Logic: o If the address info in column G also has a company name replace the contents of what is in the Company name field with that o If there is company name in the address field, look at the truncated company URL and if appropriate apply spaces and capitalize if necessary (note: you can use the “proper” function in excel to automate capitalizing) Address (column G in Blue) •The Address info is very rough. Here is the logic to fix it o Columns G, H, I, through column P have potential address. Look at column D (the location of the phone number) to guide the decision of which address to use. o Once the proper address has been identified (if there is one) clean it up by removing non-address related info (such as company names, other text, phone numbers etc.) Contact Name (column F in Green) • This will happen less often, but sometimes an individual’s name will be identified in the address. If this happens, but that name in the contact name column. If selected I will send you a file with 20,000+ Addresses to clean. Please provide a bid for 20 hours worth of data cleaning work.
Project ID: 197375
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Active 18 yrs ago
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