We need to scrape, clean, and organize data.
Most important is location/country.
TO BE DONE
0) Acquire this data, structure in Excel, extract links as separate data fields: https://en.wikipedia.org/wiki/List_of_countries_with_Burger_King_franchises
1) Acquire this data, structure in Excel, extract links as separate data fields i.e. Mcdonalds Denmark.: https://en.wikipedia.org/wiki/List_of_countries_with_McDonald%27s_restaurants
2) For each country, acquire all structured data in the right hand panel i.e. https://en.wikipedia.org/wiki/Gibraltar
3) List of Crossfit affilliates and all data associated: https://maps.crossfit.com/
4) List of Starbucks stores by country: https://en.wikipedia.org/wiki/Starbucks
5) Then add in this data for corporate tax rates into the mcdonald's database: https://en.wikipedia.org/wiki/List_of_countries_by_tax_rates ... Indicate that it is a country with a mcdonald's franchise--and then
6) All data from Inc entrepreneur list but most importantly all structured data inside the pages themselves https://www.entrepreneur.com/article/247038
7) Structure AFewHundredReason17 into an Excel file and then find the URL of the franchise system (you'll do the research) and add it in https://www.dropbox.com/s/ygalaomwvv82jwx/AFewHundredReason17%20%281%29.pdf?dl=0
8) For this exhibitor, we need to find their website URL and linkedin page ID https://www.dropbox.com/s/lc567pmortkhirw/17CONExhibitorList%20%281%29.xlsx?dl=0