Graphs

The Graph Pipeline feature enables you to transform data in relational tables into a graph.

This feature uses the latest technology to harness the power of Graph Analytics to give Financial Institutions the ability to monitor the data financial institutions effectively. The data is organized as nodes, edges, and properties (property data is stored on the nodes or edges). The results of analytics algorithms are stored as transient properties of nodes and edges in the Graph.

Users can harness the power of Graph Analytics using our in-built in-memory Oracle Graph Analytics Engine (PGX).

The Graph Pipeline functionality allows users to define graphs easily, attach underlying data, and match pipelines to populate data in the graph.

The Graph Pipeline functionality allows users to quickly create and configure a graph for use in advanced analytics. It can also manage and schedule the tasks required to run populate the graph on a periodic basis.

The Graph Pipeline functionality allows you to:

• Creating Graph Model from their existing relational data model
• Configuring the Graph Model through Pipeline UI
• Creating and Scheduling the data pipeline and matching (creation of similarity relationships) for created Graph Model
• Adding new sources and contextualizing the links quickly
• Standardizing the data before pushing it to Graph Model
• Using the following data source for Graph Model:
  • Oracle
  • File System (CSV)
• Using BD data source definitions for pre-seeded Workspace
• Using pre-configured Financial Crime Graph Model pipelines
• Using pre-seeded mappings of Graph Model properties with BD Data source properties
• Scheduling to create Graph by running pre-configured batches
• Blending data and getting insights from data quickly
• Load data into elastic search indexes so matching and entity resolution can occur in the graph
• Define matching rules for the generation of similarity edges in the graph.

An example of a preconfigured Financial Crime Graph Model with Nodes and Edges is provided here.

Figure 8-94 Example of Graph Model

The Graph Model defines the nodes and the relationship between them:

• Node: Represents a single entity with its attributes. The entity can be a single table or combination of tables merged on some common feature, it could be from a file, or any generalized component of multiple substructures merged for a specific reason/objective.

  For example, Customer.

  A customer could be a single entity.

  Customer, Salesperson, Manager, and so could be individual entities that can be structured together as a “Person” entity with a set of attributes persisted across individual entities.

• Edge: A connector between nodes or the same Node itself. Each edge can have a set of attributes associated with it. These edges will map to 'join' between two entities that could be direct or transitive.
• Modeler Attributes: Properties of the Node/Edge, and these are mandatory inputs.

  For example:

  A Customer Node will have properties like Customer ID, Name, Age, Gender, etc.

  A Transaction edge will have properties like Transaction ID, Date, Amount, From/To account, etc.

See the Adding a Graph Pipeline section for creating Graph, Nodes, Edges, and Scheduling.