Graph Computing Training Courses

Apache Jena is an open source Java framework for building Semantic Web and Linked Data applications.

In this instructor-led, live training, participants will learn how to use Apache Jena to build and deploy a Semantic Web Application.

By the end of this training, participants will be able to:

- Install and configure Apache Jena
- Convert and store data in RDF format
- Query RDF data using SPARQL
- Test and deploy a semantic web application

Audience

- Developers
- Data Engineers

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.

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 training in the US, 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.

The Semantic Web is a collaborative movement led by the World Wide Web Consortium (W3C) that promotes common formats for data on the World Wide Web. The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.

This instructor-led, live training in the US (onsite or remote) is aimed at technical persons who wish to query RDF data stored in a Semantic Web database.

By the end of this training, participants will be able to:

- Understand the difference between semantic web data and relational data.
- Query public datasets based on Semantic Web standards.
- Model data for querying with SPARQL.
- Transition a website's data to semantic web linked data.
- Run SPARQL queries from within an existing application.

MediaWiki is a free and open-source wiki software. This one-day course provides participants with an introduction to Semantic MediaWiki.