
Local, instructorled live Graph Database training courses demonstrate through handson practice how Graph Database uses graph theory to store, map and query relationships
Graph Database training is available as "onsite live training" or "remote live training" Onsite live training can be carried out locally on customer premises in Norge or in NobleProg corporate training centers in Norge Remote live training is carried out by way of an interactive, remote desktop
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Autodata Ltd
Kurs: Beyond the relational database: neo4j
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Mengden kunnskap vi fikk.
Kurs: Beyond the Relational Database: Neo4j
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Mengden kunnskap vi fikk.
Kurs: Beyond the Relational Database: Neo4j
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Graph Database Underkategorier
Graph Database Kursplaner
I denne instruktørledede, Blazegraph , vil deltakerne lære hvordan de bruker Blazegraph til å fange komplekse data i grafisk format for henting fra en rekke eksempler. Alle øvelser vil bli gjennomført praktisk i et live-lab-miljø.
Ved slutten av denne opplæringen vil deltakerne kunne:
- Installer og konfigurer Blazegraph i frittstående modus, gruppert modus (valgfritt) eller innebygd modus (valgfritt)
- Opprett, test og distribuer et eksempelapplikasjon for å spørre om komplekse data i et Blazegraph datalager
- Forstå hvordan du utnytter GPU (grafikkbehandlingsenhet) for å akselerere beregningene
Publikum
- Utviklere
Kursets format
- Delforelesning, deldiskusjon, øvelser og tung praktisk øvelse
Merk
- For å be om en tilpasset opplæring for dette kurset, vennligst kontakt oss for å avtale.
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
In this instructor-led, live training, 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 and Distributed Graph Processing) 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.
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
In this instructor-led, live hands-on training, 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.
Format of the Course
- Heavy emphasis on hands-on practice. Most of the concepts are learned through samples, exercises and hands-on development.