Graph Database Training in Bradford

In this instructor-led, live training in Bradford, participants will learn about the technology offerings and implementation approaches for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using a Graph Computing (also known as Graph Analytics) approach. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments.

By the end of this training, participants will be able to:

• Understand how graph data is persisted and traversed.
• Select the best framework for a given task (from graph databases to batch processing frameworks.)
• Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel.
• View real-world big data problems in terms of graphs, processes and traversals.

This instructor-led, live training in Bradford (online or onsite) is aimed at engineers who wish to use JanusGraph to process very large graphs that require abnormal storage and computational capacity.

By the end of this training, participants will be able to:

• Install and configure JanusGraph.
• Integrate JanusGraph with multiple backend storage systems (Cassandra, HBase, etc.) and multiple indexing software (Elasticsearch, Solr, etc.). 
• Configure multiples machines into a cluster for use by JanusGraph.
• Query the database using the Gremlin query language.
• Process graph data at scale, beyond what a single machine can provide.
• Support thousands of concurrent users traversing graph data in real time.
• Query graph data for analysis.