Differentiate between structured and unstructured data with examples.

Structured Data: Structured data is highly organized and formatted in a way so it's easily searchable in relational databases. This type of data adheres to a schema, so all of the data in a field of the database is of the same type, and each field relates to a specific definition. Examples of structured data include numbers, dates, and groups of words and numbers called strings. For instance, a database storing data about music could have a structured database schema consisting of tables like 'Artists', 'Albums', 'Tracks', etc. Each of these tables would then have specific fields. For example, the 'Artists' table might have 'Name', 'Genre', 'Date of Birth', etc.

Unstructured Data: Unstructured data, on the other hand, is data that doesn't fit into a pre-defined model or is not organized in a pre-defined manner. It is typically text-heavy, but may contain data such as dates, numbers, and facts as well. This type of data is often harder to analyze and process. Examples of unstructured data include Word documents, PDF files, emails, blog posts, social media posts, video and audio files, etc. For instance, a collection of manuscripts, photographs, and government documents related to the Civil Rights Movement would be considered unstructured data.