Stream Processing Training Courses

Stream Processing Training Courses

Local, instructor-led live Stream Processing training courses demonstrate through interactive discussion and hands-on practice the fundamentals and advanced topics of Stream Processing. Stream Processing training is available as "onsite live training" or "remote live training". Onsite live Stream Processing trainings in Canada can be carried out locally on customer premises or in NobleProg corporate training centers. Remote live training is carried out by way of an interactive, remote desktop. NobleProg -- Your Local Training Provider

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Stream Processing Course Outlines

CodeNameDurationOverview
stormApache Storm28 hoursApache Storm is a distributed, real-time computation engine used for enabling real-time business intelligence. It does so by enabling applications to reliably process unbounded streams of data (a.k.a. stream processing).

"Storm is for real-time processing what Hadoop is for batch processing!"

In this instructor-led live training, participants will learn how to install and configure Apache Storm, then develop and deploy an Apache Storm application for processing big data in real-time.

Some of the topics included in this training include:

- Apache Storm in the context of Hadoop
- Working with unbounded data
- Continuous computation
- Real-time analytics
- Distributed RPC and ETL processing

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Audience

- Software and ETL developers
- Mainframe professionals
- Data scientists
- Big data analysts
- Hadoop professionals

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
samzaSamza for Stream Processing14 hoursApache Samza is an open-source near-realtime, asynchronous computational framework for stream processing. It uses Apache Kafka for messaging, and Apache Hadoop YARN for fault tolerance, processor isolation, security, and resource management.

This instructor-led, live training introduces the principles behind messaging systems and distributed stream processing, while walking participants through the creation of a sample Samza-based project and job execution.

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

- Use Samza to simplify the code needed to produce and consume messages.
- Decouple the handling of messages from an application.
- Use Samza to implement near-realtime asynchronous computation.
- Use stream processing to provide a higher level of abstraction over messaging systems.

Audience

- Developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
flinkFlink for Scalable Stream and Batch Data Processing28 hoursApache Flink is an open-source framework for scalable stream and batch data processing.

This instructor-led, live training introduces the principles and approaches behind distributed stream and batch data processing, and walks participants through the creation of a real-time, data streaming application.

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

- Set up an environment for developing data analysis applications
- Package, execute, and monitor Flink-based, fault-tolerant, data streaming applications
- Manage diverse workloads
- Perform advanced analytics using Flink ML
- Set up a multi-node Flink cluster
- Measure and optimize performance
- Integrate Flink with different Big Data systems
- Compare Flink capabilities with those of other big data processing frameworks

Audience

- Developers
- Architects
- Data engineers
- Analytics professionals
- Technical managers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
apexApache Apex: Processing Big Data-in-Motion21 hoursApache Apex is a YARN-native platform that unifies stream and batch processing. It processes big data-in-motion in a way that is scalable, performant, fault-tolerant, stateful, secure, distributed, and easily operable.

This instructor-led, live training introduces Apache Apex's unified stream processing architecture, and walks participants through the creation of a distributed application using Apex on Hadoop.

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

- Understand data processing pipeline concepts such as connectors for sources and sinks, common data transformations, etc.
- Build, scale and optimize an Apex application
- Process real-time data streams reliably and with minimum latency
- Use Apex Core and the Apex Malhar library to enable rapid application development
- Use the Apex API to write and re-use existing Java code
- Integrate Apex into other applications as a processing engine
- Tune, test and scale Apex applications

Audience

- Developers
- Enterprise architects

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
ApacheIgniteApache Ignite: Improve Speed, Scale and Availability with In-Memory Computing14 hoursApache Ignite is an in-memory computing platform that sits between the application and data layer to improve speed, scale, and availability.

In this instructor-led, live training, participants will learn the principles behind persistent and pure in-memory storage as they step through the creation of a sample in-memory computing project.

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

- Use Ignite for in-memory, on-disk persistence as well as a purely distributed in-memory database.
- Achieve persistence without syncing data back to a relational database.
- Use Ignite to carry out SQL and distributed joins.
- Improve performance by moving data closer to the CPU, using RAM as a storage.
- Spread data sets across a cluster to achieve horizontal scalability.
- Integrate Ignite with RDBMS, NoSQL, Hadoop and machine learning processors.

Audience

- Developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
tigonTigon: Real-time Streaming for the Real World14 hoursTigon is an open-source, real-time, low-latency, high-throughput, native YARN, stream processing framework that sits on top of HDFS and HBase for persistence. Tigon applications address use cases such as network intrusion detection and analytics, social media market analysis, location analytics, and real-time recommendations to users.

This instructor-led, live training introduces Tigon's approach to blending real-time and batch processing as it walks participants through the creation a sample application.

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

- Create powerful, stream processing applications for handling large volumes of data
- Process stream sources such as Twitter and Webserver Logs
- Use Tigon for rapid joining, filtering, and aggregating of streams

Audience

- Developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
nifiApache NiFi for Administrators21 hoursApache NiFi (Hortonworks DataFlow) is a real-time integrated data logistics and simple event processing platform that enables the moving, tracking and automation of data between systems. It is written using flow-based programming and provides a web-based user interface to manage dataflows in real time.

In this instructor-led, live training, participants will learn how to deploy and manage Apache NiFi in a live lab environment.

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

- Install and configure Apachi NiFi
- Source, transform and manage data from disparate, distributed data sources, including databases and big data lakes
- Automate dataflows
- Enable streaming analytics
- Apply various approaches for data ingestion
- Transform Big Data and into business insights

Audience

- System administrators
- Data engineers
- Developers
- DevOps

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
nifidevApache NiFi for Developers7 hoursApache NiFi (Hortonworks DataFlow) is a real-time integrated data logistics and simple event processing platform that enables the moving, tracking and automation of data between systems. It is written using flow-based programming and provides a web-based user interface to manage dataflows in real time.

In this instructor-led, live training, participants will learn the fundamentals of flow-based programming as they develop a number of demo extensions, components and processors using Apache NiFi.

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

- Understand NiFi's architecture and dataflow concepts
- Develop extensions using NiFi and third-party APIs
- Custom develop their own Apache Nifi processor
- Ingest and process real-time data from disparate and uncommon file formats and data sources

Audience

- Developers
- Data engineers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
maprstreamingReal-Time Stream Processing with MapR7 hoursIn this instructor-led, live training, participants will learn the core concepts behind MapR Stream Architecture as they develop a real-time streaming application.

By the end of this training, participants will be able to build producer and consumer applications for real-time stream data procesing.

Audience

- Developers
- Administrators

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.
introtostreamprocessingA Practical Introduction to Stream Processing21 hoursStream Processing refers to the real-time processing of "data in motion", that is, performing computations on data as it is being received. Such data is read as continuous streams from data sources such as sensor events, website user activity, financial trades, credit card swipes, click streams, etc. Stream Processing frameworks are able to read large volumes of incoming data and provide valuable insights almost instantaneously.

In this instructor-led, live training (onsite or remote), participants will learn how to set up and integrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices.

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

- Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming
- Understand and select the most appropriate framework for the job
- Process of data continuously, concurrently, and in a record-by-record fashion
- Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
- Integrating the most appropriate stream processing library with enterprise applications and microservices

Audience

- Developers
- Software architects

Format of the Course

- Part lecture, part discussion, exercises and heavy hands-on practice

Notes

- To request a customized training for this course, please contact us to arrange.
beamUnified Batch and Stream Processing with Apache Beam14 hoursApache Beam is an open source, unified programming model for defining and executing parallel data processing pipelines. It's power lies in its ability to run both batch and streaming pipelines, with execution being carried out by one of Beam's supported distributed processing back-ends: Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Apache Beam is useful for ETL (Extract, Transform, and Load) tasks such as moving data between different storage media and data sources, transforming data into a more desirable format, and loading data onto a new system.

In this instructor-led, live training (onsite or remote), participants will learn how to implement the Apache Beam SDKs in a Java or Python application that defines a data processing pipeline for decomposing a big data set into smaller chunks for independent, parallel processing.

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

- Install and configure Apache Beam.
- Use a single programming model to carry out both batch and stream processing from withing their Java or Python application.
- Execute pipelines across multiple environments.

Audience

- Developers

Format of the Course

- Part lecture, part discussion, exercises and heavy hands-on practice

Note

- This course will be available Scala in the future. Please contact us to arrange.

Upcoming Stream Processing Courses

CourseCourse DateCourse Price [Remote / Classroom]
Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing - NS, Halifax - Hampton InnThu, Dec 27 2018, 9:30 amCA$4,730 / CA$6,730
Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing - Victoria - The AtriumThu, Dec 27 2018, 9:30 amCA$4,730 / CA$6,370
Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing - Vancouver - Pacific CentreMon, Dec 31 2018, 9:30 amCA$4,730 / CA$6,560
Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing - Burnaby - MetrotownTue, Jan 1 2019, 9:30 amCA$4,730 / CA$6,560
Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing - Toronto - West Toronto - EtobicokeTue, Jan 1 2019, 9:30 amCA$4,730 / CA$6,490
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Course Discounts

CourseVenueCourse DateCourse Price [Remote / Classroom]
Arduino: Programming a Microcontroller for BeginnersToronto - Toronto StreetTue, Dec 18 2018, 9:30 amCA$4,683 / CA$6,573
Public Speaking 101Oakville - Winston ParkTue, Jan 1 2019, 9:30 amCA$4,730 / CA$6,430
Comprehensive GitBrampton - Brampton County CourtMon, Jan 14 2019, 9:30 amCA$6,985 / CA$8,875
R for Data Analysis and Research Ottawa - 343 PrestonThu, Jan 17 2019, 9:30 amCA$2,450 / CA$4,160
Data Mining with RNS, Halifax - Hampton InnThu, Jan 31 2019, 9:30 amCA$3,870 / CA$5,870
OCEB 2 Certified Expert in BPM - Business Advanced Exam PreparationCalgary - Sun LifeFri, Feb 15 2019, 9:30 amCA$2,025 / CA$3,705
Go for Systems ProgrammingCalgary - Macleod Place IIMon, May 6 2019, 9:30 amCA$10,346 / CA$12,746

Course Discounts Newsletter

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