Graphs Made Easy: Find New Insights in Your Data with Graph in Autonomous Database
In this Autonomous Database Learning Lounge session, Oracle Graph and Autonomous Database Product Management presented how you can use graph queries and graph analytics to find new relationships in existing data in your Autonomous Database.
Slides at: https://bit.ly/adbll-slides-graph
Outline
Autonomous Database Learning Lounge series presents “Graphs Made Easy: Find New Insights in Your Data”
Melliyal Annamalai, Distinguished Product Manager will explain how modeling your data as a graph can help you find connections in data. With graphs you can uncover money laundering in financial transactions, traverse linked components in manufacturing data, search for connected parts in a supply chain inventory, find impacted nodes in a telecommunication network failure, and more. Graph Studio in Oracle Autonomous Database makes it easy for developers to get started with graph queries and graph analytics. You can create, query, analyze, and visualize graphs using automated graph modeling tools, a SQL-like graph query language, and pre-built graph algorithms, all using data in tables in your autonomous database. Melli will walk through an example of finding fraud in financial transactions and show you how you can get started with graphs in minutes.
Open Q&A
Autonomous Database product managers answered technical questions about the Autonomous Database service, its features, integration capabilities and use cases.
Video highlights:
00:55 Agenda
02:04 Important links on Autonomous Database
02:44 Graphs made easy: What are Graphs?
04:45 Customer quote: Paysafe
05:20 Why Graph? Typical relational model
06:15 Why Graph? Same data modeled as a graph
08:30 An Example: Bank Account and Cash Transfers
09:15 Uncovering Fraud
10:56 Property graph data model: key elements
12:35 Create a graph from Bank_Accounts and Bank_Txns
12:55 Automated graph modeler in Autonomous Database
15:04 Property graph in Oracle Database
16:23 Visualize a Graph of financial transactions
17:30 Property graph queries: search for patterns
17:51 Graph query language
20:06 Query property graph views
20:50 Live Demo: exploring connections in financial transactions
28:09 Property graph analytics
29:42 Graph analytics: 60+ built-in algorithms in Autonomous Database
31:34 Analyze property graphs: Java and Python APIs
32:10 Live Demo: analyze the complete graph
35:45 A movie recommendation example
37:10 personalized_salsa algorithm
38:23 Customer examples
41:00 Graph customers industries
42:21 Key takeaways
43:00 Graph Resources
43:42 Q&A
43:58 Final thoughts