Online or onsite, instructor-led live Graph Database training courses demonstrate through hands-on practice how Graph Database uses graph theory to store, map and query relationships.
Graph Database 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 Graph Database training can be carried out locally on customer premises in Zakopane or in NobleProg corporate training centers in Zakopane.
NobleProg -- Your Local Training Provider
Zakopane
Dafne, Jagiellońska 30, Zakopane, Poland, 34-500
The training room is located just 350 meters from the railway and bus stations and 700 meters from Krupówki, the main shopping street in Zakopane. There is a fenced parking area on the premises, providing convenience for participants traveling by car and facilitating access to the facility.
In this instructor-led, live training in Zakopane, 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 Zakopane (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.
In this instructor-led, live hands-on training in Zakopane, 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 Zakopane (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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Exercises and their translation methods
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