Online or onsite, instructor-led live Neo4j training courses demonstrate through hands-on practice how to model, manage and access your data in a live project. We contrast and compare graph databases with SQL-based databases as well as other NoSQL databases and clarify when and where it makes sense to implement each within your infrastructure.
Neo4j training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Neo4j training can be carried out locally on customer premises in wielkopolskie or in NobleProg corporate training centers in wielkopolskie.
In this instructor-led, live hands-on training in wielkopolskie, we will set up a live project and put into practice the skills to model, manage and access your data using neo4j. We contrast and compare graph databases with SQL-based databases as well as other NoSQL databases and clarify when and where it makes sense to implement each within your infrastructure.
This instructor-led, live training in wielkopolskie (online or onsite) is aimed at developers who wish to use Neo4j AuraDB graph database to build cloud applications with high availability and zero administration.
By the end of this training, participants will be able to:
Set up the necessary development environment to start developing graph database applications with Neo4j AuraDB.
Understand the features, core concepts, and architecture of Neo4j AuraDB.
Learn how to build and scale graph database applications in the cloud.
Enhance cloud security with AuraDB's pre-configured authentication and encryption features.
Neo4j is an innovative graph database that is based on a graph data structure, which means that data is stored in the form of nodes, relationships and properties. Neo4j has been used in many areas where relationships between data are crucial. As a graph database, it is used in cases where traditional relational databases may be insufficient to effectively analyze and extract information from related data. Its strength lies in representing and analyzing the relationships between different data elements, which makes it an important tool in the field of data analysis and knowledge management.
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