Many data architects are well-accustomed to traditional database issues related to data storage, volumes and read/write tradeoffs. However, there are a lot of complex problems that are better served by non-traditional data storage models like graph databases. According to Gartner, “Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions after the design of data capture.” In this course, attendees will learn from Expero's graph experts how to properly model graph data to satisfy unique business needs and how to present the data to users so they can get the most value out of it.This course can be customized for any length from a 1-5 day training session to a 4-week bootcamp.Note: Attendees should be seasoned technologists with exposure to common relational database technologies and distributed system principles as well as common coding and scripting paradigms.
LENGTH: 1 - 5 Days (2- or 4-Week Bootcamp also available)
FORMAT: Lecture with group exercises and Q&A
Enterprise architectsData scientistsDatabase administratorsDevOps architectsSr. Developers focused on the persistence layerExecutive management with oversight responsibility
Rudimentary graph and graph ecosystemGraph design patternsWhole graph analytics and algorithmsProperty graph data modelingGraph query languages: Gremlin and CypherUnderstanding eventual consistencyFundamentals of JanusGraphGraph database performance tuningPhysical deployment strategiesDevOps best practices (setup, monitor, backups, etc.)Visualizing your graph and designing the user experiencePreparing for DataStax Enterprise GraphFundamentals of Neo4jDeveloper training: connecting and querying
