Knowledge Graph -An Overview and its Applications
Overview of Knowledge Graph, Graph Database, types of Knowledge Graph, Data to Knowledge Graph, FAIR Data and AWS Neptune Graph Database
Series: AWS Data and AI (15 articles)
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- 5Knowledge Graph -An Overview and its Applications This article
This article is a brief summary of my session on the topic at AWS Student Community Day Chennai Event.
How do we provide personalized experience for the customers?
Representation of customer data as graphs in graph database has helped organizations provide personalized experience for the customers. Graphs are used solve real-life problems that involve representation of the problem space as network. Examples of network include telephone, road networks, social networks (like LinkedIn, Facebook, etc.). We will see more about this in this article.
Types of Databases
Relational Database
it is used to store structured data. Data stored in Rows and Columns of a table.
No SQL
No SQL Database handles unstructured data like columnar, graph, key-value pairs and document.
What is Graph Database?
It is used to store graph data structure as a data in form of nodes and relationships instead of tables or documents. Here, Data is natively stored just like we sketch graph on paper.
When to use Graph Database?
When relationship between data matters more than Data itself, Graph Database is used. It is used to derive insights and relationships between data.
What is Graph?
•It is a Data structure
•Has vertices (or nodes) and
•A set of edges (relationships) connecting nodes
•Graph can directed graph or undirected Graph
What is a Knowledge Graph?
Knowledge Graph is representation of data as a graph with the understanding of who, what, when, why ,etc.
Two types of Knowledge Graph
•Resource Description Framework (RDF) graphs
•Labeled Property Graphs (LPG)
Data to Knowledge Graph
- Data is ingested from multiple sources.
- Organizations create taxonomy, which is a hierarchical representation of how data has to represented in a graph. For example - A School will have a principal followed by HOD of each department, which is further followed in a tree structure by Lecturers in each department.
- Organization create Ontology to represent more complex data relationships.
- In parallel, Data modelling is done to create schema representation of the Graph.
- Data Quality Management is done by data transformation using Medallion architecture.
- Medallion architecture is a layered data engineering pattern that progressively transforms raw data into high-quality, business-ready assets through bronze, silver, and gold layers.
- The details above are uploaded into a Graph database to create a Knowledge Graph.
FAIR Data
- Findable - Data must be findable by Humans and AI Agents
- Accessible - Data must be accessible to authorized users only. However, metadata must be accessible to Human users and AI agents.
- Interoperable - Data must be interoperable between different platforms and warehouses.
- Reusable -Data must be reusable to create new data insights and complex data architectures.
AWS Neptune – Graph Database
- Serverless Managed Graph Database by Amazon
- Stores data in triple format (subject, Predicate, object)
- Integrated with S3 for data ingestion.
- Accepts inputs as vertex file and edges file to create knowledge Graph.
Series: AWS Data and AI (15 articles)
- …
- 5Knowledge Graph -An Overview and its Applications This article
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