Modern applications produce petabytes of data every day. As an example, during the year 2019, every minute, the number of Google searches has been estimated to be more than 4.4 billion. During the same amount of time, 180 billion emails, and more than 500,000 tweets are sent, while the number of videos watched on YouTube is about 4.5 billion. Organizing this data and transforming it into knowledge is a real challenge.
Knowledge graphs try to address this challenge by storing the following in the same data structure:
- Entities related to a specific field, such as users or products
- Relationships between entities, for instance, user A bought a surfboard
- Context to understand the previous entities and relationships, for instance, user A lives in Hawaii and is a surf teacher
Graphs are the perfect structure to store all this information since it is very easy to aggregate data from different data sources: we just have to create new nodes (with maybe...
