Please put together proposal for database that you want to build.  Although the proposal I have put in files doesn't actually indicate where the data is coming from it did indicate they were going to get considerable amount of information from Yelp!  In this case the person who put together proposal actually had been keeping information on restaurants they had visited and ones they wanted to visit for years.  So they actual used a bunch of web resources including reviews from Yelp! and Google! to add to their own information. There are many free sources for information including Kaggle, Google, et. Just put into google "free datasets on the web" and you will get back a long list of places to look for datasets.  Remember the job is to build a database with a number of tables. But at the moment its coming up with information you would like to store in a database you want to build and worry about detailed information about all the tables later.
 

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When reflecting upon what data to use for the Database Management Systems class project the thought instantly flew into our minds to create a database utilizing information pertaining to the incredibly large number of restaurants within New York City. There are tens of thousands of restaurants in New York City so it is obvious that in order to use this data for the project some sort of parameter needs to be put in place. Even when limiting the area to the borough in which we live (Brooklyn), it is revealed through local business search engine Yelp that there are roughly 20,000 different restaurants to choose from. Only a two-mile search radius from my apartment was needed to yield roughly 1,400 restaurant results. Using Yelp, I then sorted these restaurants by "Highest Rated" and selected the top 500 to be our dataset for the project. A great thing about New York and my neighborhood of Bushwick in particular is that there is a high variety of restaurants just within a two-mile radius, thus the data is varied with no large repetition of any one singular type of restaurant. Our restaurant database will include information on the restaurant itself, such as establishment name and telephone number. There will be a table specifically relating to location which will include the street address and neighborhood location (Bushwick, Ridgewood, etc.). A table listing the style/genre of restaurant (Mexican, Japanese, Coffee/Tea, etc.). A table for rating using data from Yelp that includes number of patron reviews as well as an aggregated score out of five stars. Alongside this, there will be a table storing information pertaining to the restaurant price range (data that also can be readily pulled from local business search engine Yelp). We love exploring new restaurants so I believe having some sort of method to parse the incredibly large volume of choice will have actual benefit to us outside of class. While Yelp is certainly a useful tool I am interested in the personalization that comes with designing and implementing an individualized database that makes sense of data we actually interact with on a regular basis. When reflecting upon what data to use for the Database Management Systems class project the thought instantly flew into our minds to create a database utilizing information pertaining to the incredibly large number of restaurants within New York City. There are tens of thousands of restaurants in New York City so it is obvious that in order to use this data for the project some sort of parameter needs to be put in place. Even when limiting the area to the borough in which we live (Brooklyn), it is revealed through local business search engine Yelp that there are roughly 20,000 different restaurants to choose from. Only a two-mile search radius from my apartment was needed to yield roughly 1,400 restaurant results. Using Yelp, I then sorted these restaurants by "Highest Rated" and selected the top 500 to be our dataset for the project. A great thing about New York and my neighborhood of Bushwick in particular is that there is a high variety of restaurants just within a two-mile radius, thus the data is varied with no large repetition of any one singular type of restaurant. Our restaurant database will include information on the restaurant itself, such as establishment name and telephone number. There will be a table specifically relating to location which will include the street address and neighborhood location (Bushwick, Ridgewood, etc.). A table listing the style/genre of restaurant (Mexican, Japanese, Coffee/Tea, etc.). A table for rating using data from Yelp that includes number of patron reviews as well as an aggregated score out of five stars. Alongside this, there will be a table storing information pertaining to the restaurant price range (data that also can be readily pulled from local business search engine Yelp). We love exploring new restaurants so I believe having some sort of method to parse the incredibly large volume of choice will have actual benefit to us outside of class. While Yelp is certainly a useful tool I am interested in the personalization that comes with designing and implementing an individualized database that makes sense of data we actually interact with on a regular basis.