Suppose a MOVIE database in which data is recorded about the movie industry. The data needs are summarized as follows:

_ Each movie is recoganized by title and year of release. Each movie has a length in minutes.

_ Each has a production company, and each is divided under one or more genres(such as horror, drama, action, and so forth). Each movie has one or more directors and one or more actors appear in it. Each movie also has a plot outline. Finally, each movie has zero or more quotable quotes, each of which is spoken by a particular actor appearing in the movie.

_ Actors are taken by name and date of birth and appear in one or more movies. Each actor has a role in the movie.

_ Directors are also identified by name and date of birth and direct one or more movies.

_ Production companies are shown by name and each has an address. A production company produces one or more movies.

Prepare the E-R diagram for the Movie database. Make sure that your model properly depicts entities, relationships and attributes and weak entities (if any).

For example, the description above referring to actors, it does not mention or imply anything about if an actor is related with any production company. Therefore, don't even attempt to create a model that connects them.

It is also very important that you do not add attributes if they are not required by the problem. For example, the description above refers to actors. It does not mention or imply anything about actor sex (i.e. female or male). Therefore, don't even attempt to prepare a model that includes sex as an attribute, it would be superfluous.

These are just examples of how you will find yourself out of bounds.

Developing a general, all inclusive model to solve the problem is as important as creating a well-bounded model to solve the problem.