Bydgoszcz

sale szkoleniowe NobleProg, ul. Dworcowa 94, Bydgoszcz, poland, 85-010
The Classroom is located at ul. Dworcowa 94 in Bydgoszcz

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

Subcategories (2)

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Neo4j
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Blazegraph

Explore Our Courses

Flockdb: A Simple Graph Database for Social Media

7 Hours
FlockDB is an open source distributed, fault-tolerant graph database for managing wide but shallow network graphs. It was initially used by Twitter to store relationships among users. In this instructor-led, live training, participants will learn how to set up and use a FlockDB database to help answer social media questions such as who follows whom, who blocks whom, etc. By the end of this training, participants will be able to:
  • Install and configure FlockDB
  • Understand the unique features of FlockDB, relative to other graph databases such Neo4j
  • Use FlockDB to maintain a large graph dataset
  • Use FlockDB together with MySQL to provide provide distributed storage capabilities
  • Query, create and update extremely fast graph edges
  • Scale FlockDB horizontally for use in on-line, low-latency, high throughput web environments
Audience
  • Developers
  • Database engineers
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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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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Blazegraph: Creating a Graph Database Application

21 Hours
Blazegraph is an open source, Java-based RDF graph database for storing and representing data with complex relationships. It supports Blueprints and RDF/SPARQL 1.1. In this instructor-led, live training, participants will learn how to use Blazegraph to capture complex data in graph format for retrieval from a number of sample applications. All exercises will be carried out hands-on in a live-lab environment. By the end of this training, participants will be able to:
  • Install and configure Blazegraph in standalone mode, clustered mode (optional) or embedded mode (optional)
  • Create, test and deploy a sample application to query complex data in a Blazegraph data store
  • Understand how to leverage GPU (graphics processing unit) to accelerate computations
Audience
  • Developers
Format of the Course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Note
  • To request a customized training for this course, please contact us to arrange.
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ćwiczenia i sposób ich tłumaczenia

Marcin Lipiec - Izba Administracji Skarbowej w Rzeszowie
Course - Wprowadzenie do Neo4j - grafowej bazy danych

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