Torun

Sale szkoleniowe NobleProg, Bydgoska 1, Toruń, poland, 87-100

The NobleProg classrooms in Toruń are located in the Coworking Toruń office at Bydgoska 1 Street

Bydgoszcz

sale szkoleniowe NobleProg, ul. Dworcowa 94, Bydgoszcz, poland, 85-010

The Classroom is located at ul. Dworcowa 94 in Bydgoszcz

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Category for Neo4j

Neo4j

Explore Our Courses

Introduction to Graph Computing

 28 Hours
In this instructor-led, live training in kujawsko-pomorskie, 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.
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JanusGraph

 14 Hours
This instructor-led, live training in kujawsko-pomorskie (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.
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Beyond the Relational Database: Neo4j

 21 Hours
In this instructor-led, live hands-on training in kujawsko-pomorskie, 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.
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Building Graph Databases with Neo4j AuraDB

 14 Hours
This instructor-led, live training in kujawsko-pomorskie (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.
  • Migrate existing Neo4j databases to AuraDB.
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Wprowadzenie do Neo4j - grafowej bazy danych

 7 Hours
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

Marcin Lipiec - Izba Administracji Skarbowej w Rzeszowie

Course - Wprowadzenie do Neo4j - grafowej bazy danych

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