Praktyczne szkolenia na żywo z Graph Computing to kursy przedstawiające różne oferty technologii i implementacje do przetwarzania danych wykresu, w celu identyfikacji rzeczywistych obiektów, ich cech i relacji, a następnie modelowania tych relacji i przetwarzania ich jako danych przy użyciu metod obliczeniowych wykresów.
Szkolenie Graph Computing jest dostępne jako "szkolenie stacjonarne" lub "szkolenie online na żywo".
Szkolenie stacjonarne może odbywać się lokalnie w siedzibie klienta w Poznań lub w ośrodkach szkoleniowych NobleProg w Poznań. Zdalne szkolenie online odbywa się za pomocą interaktywnego, zdalnego pulpitu DaDesktop .
Sala szkoleniowa znajduje się w budynku Casa Verona przy ulicy Garbary 100/63, 61-757 Poznań.
Dojście od...
Sala szkoleniowa znajduje się w budynku Casa Verona przy ulicy Garbary 100/63, 61-757 Poznań.
Dojście od skrzyżowania ulic Garbary i Estkowskiego - należy kierować się na północ, w kierunku Parku Cytadela, wzdłuż ulicy Garbary. Casa Verona to pierwszy budynek po prawej stronie. Wejścia znajdują się od strony południowej, od ulicy Garbary oraz od strony północnej (patrz mapka poniżej).
Sala szkoleniowa znajduje się na trzecim piętrze w środkowej klatce budynku.
Parking
W pobliżu sali szkoleniowej liczba miejsc parkingowych jest ograniczona, obowiązuje strefa parkowania.
Płatne parkingi znajdują się przy skrzyżowaniu ulic Garbary i Piaskowej oraz Garbary i Grochowe Łąki (patrz mapka poniżej).
Many real world problems can be described in terms of graphs. For example, the Web graph, the social network graph, the train network graph and the language graph. These graphs tend to be extremely large; processing them requires a specialized set of tools and processes -- these tools and processes can be referred to as Graph Computing (also known as Graph Analytics).
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
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.
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.
SPARQL is a query language for querying RDF (Resource Description Framework) data. It is similar to SQL for relational data in databases.
This instructor-led, live training (online or onsite) 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.
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.