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 trainings in San Francisco Bay Area can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
CA, Sunnyvale - Downtown Sunnyvale
640 W California Ave Suite 210, Sunnyvale, united states, 94086
The Sunnyvale center is located one block from Caltrain rail station and provides easy access to Central Expressway and High...
The Sunnyvale center is located one block from Caltrain rail station and provides easy access to Central Expressway and Highway 101.
It is in walking distance to the city's downtown district, featuring numerous restaurants, shops, and businesses, as well as a short drive from San Jose International Airport.
CA, San Francisco - Golden Gate
75 Broadway, San Francisco , united states, 94111
With its fabulous arched windows, the 75 Broadway office, located in the heart of Jackson Square, is designed to impress. Sit...
With its fabulous arched windows, the 75 Broadway office, located in the heart of Jackson Square, is designed to impress. Situated at Golden Gateway Commons on the second floor of this unique campus-style building, it overlooks the green terrain's of Sydney Walton Park with the famous waterfront piers behind. This enviable location is a short walk from public transport and just blocks away from the Embarcadero and the ferry building, as well as a host of convenient amenities.
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.
In this instructor-led, live hands-on training in San Francisco Bay Area, 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 San Francisco Bay Area (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.
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
In this instructor-led, live training in San Francisco Bay Area, 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 San Francisco Bay Area (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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Los conocimientos del instructor y experiencia
Mauricio Somohano Ríos - INTERCAM BANCO SA INSTITUCION DE BANCA MULTIPLE, INTERCAM GRUPO FINANCIERO
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