AM10: Introduction to Graph Data Management

Even though conventional relational database management systems RDBMS have been the core of most business applications, the tabular structure of the RDBMS actually can impede certain types of advanced analyses. Data about entities is easily captured in the RDBMS, but logging the characteristics of the relationships between those entities is limited to clumsy methods. Fortunately, we are beginning to see alternatives to the relational model such as graph databases that enable greater flexibility for analyzing modeled entities in the context of their relationships.

Graph databases and analytics systems, based on the mathematical graph abstraction for representing connectivity, rely on an alternative approach to data representation that captures information about entities and their attributes and elevates the relationships among the entities to be first-class objects. In this tutorial we introduce the concepts of graphs and graph database systems and guide the attendees through a process of mapping data sets into the graph paradigm using real-world examples. Attendees will learn about:

Graph data models
Assessing data and identifying entities and relationships
Graph querying
Simple graph analytics functions
More complex graph analytics
Types of vendor graph products

David Loshin is the President of Knowledge Integrity, Inc, (www.knowledge-integrity.com), a consulting company focusing on information management solutions (information quality, business intelligence, metadata, and data governance). David is among Knowledge Integrity’s recognized experts in information management, contributing to Intelligent Enterprise and DM Review, and is a channel expert for the Business Intelligence network (www.b-eye-network.com).

David's books include "The Practitioner's Guide to Data Quality Improvement" and "Master Data Management,” and his book, "Business Intelligence: The Savvy Manager’s Guide" (June 2003) has been hailed as a resource allowing readers to "gain an understanding of business intelligence, business management disciplines, data warehousing, and how all of the pieces work together." David has created courses for TDWI, DATAVERSITY, and any other number of venues, and is often asked to provide thought leadership to the Information Management Community.