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 training can be carried out locally on customer premises in Hong Kong or in NobleProg corporate training centers in Hong Kong. Remote live training is carried out by way of an interactive, remote desktop. NobleProg -- Your Local Training Provider
Testimonials
I really was benefit from the willingness of the trainer to share more.
Balaram Chandra Paul
Course: A Practical Introduction to Data Analysis and Big Data
I was benefit from some new and interesting ideas. Meeting and interacting with other attendees.
TECTERRA
Course: IoT ( Internet of Things) for Entrepreneurs, Managers and Investors
It covered a broad range of information.
Continental AG / Abteilung: CF IT Finance
Course: A Practical Introduction to Data Analysis and Big Data
I generally was benefit from the presentation of technologies.
Continental AG / Abteilung: CF IT Finance
Course: A Practical Introduction to Data Analysis and Big Data
Overall the Content was good.
Sameer Rohadia
Course: A Practical Introduction to Data Analysis and Big Data
I generally enjoyed the Hardtop Eco system.
Adnan Rafiq
Course: Big Data Business Intelligence for Govt. Agencies
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
I really enjoyed the introduction of new packages.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
The tutor, Mr. Michael An, interacted with the audience very well, the instruction was clear. The tutor also go extent to add more information based on the requests from the students during the training.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
The example and training material were sufficient and made it easy to understand what you are doing.
Teboho Makenete
Course: Data Science for Big Data Analytics
Richard's training style kept it interesting, the real world examples used helped to drive the concepts home.
Jamie Martin-Royle - NBrown Group
Course: From Data to Decision with Big Data and Predictive Analytics
The content, as I found it very interesting and think it would help me in my final year at University.
Krishan Mistry - NBrown Group
Course: From Data to Decision with Big Data and Predictive Analytics
The hands-on exercises are good for us to appreciate the capability and features of Talent.
Iverson Associates Sdn Bhd
Course: Talend Open Studio for Data Integration
I mostly enjoyed the hands-on Training.
Muraly Muniandy - Iverson Associates Sdn Bhd
Course: Talend Open Studio for Data Integration
I liked the trainer's knowledge and flexibility with discussions slightly off course topic.
Iverson Associates Sdn Bhd
Course: Talend Open Studio for Data Integration
I liked the vast knowledge and experience on topic.
Iverson Associates Sdn Bhd
Course: Talend Open Studio for Data Integration
the scope of material
Maciej Jonczyk
Course: From Data to Decision with Big Data and Predictive Analytics
Translated by
systematizing knowledge in the field of ML
Orange Polska
Course: From Data to Decision with Big Data and Predictive Analytics
Translated by
entirety
Szymon Bodak - Bridgestone Stargard Sp. z o.o.
Course: Talend Open Studio for Data Integration
Translated by
Stream Processing Subcategories
Stream Processing Course Outlines
| Code | Name | Duration | Overview |
|---|---|---|---|
| storm | Apache Storm | 28 hours | Apache 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 Request this course now! 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 |
| samza | Samza for Stream Processing | 14 hours | Apache 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 |
| flink | Flink for Scalable Stream and Batch Data Processing | 28 hours | Apache 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 |
| apex | Apache Apex: Processing Big Data-in-Motion | 21 hours | Apache 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 |
| ApacheIgnite | Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing | 14 hours | Apache 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 |
| tigon | Tigon: Real-time Streaming for the Real World | 14 hours | Tigon 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 |
| nifi | Apache NiFi for Administrators | 21 hours | Apache 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 |
| nifidev | Apache NiFi for Developers | 7 hours | Apache 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 |
| maprstreaming | Real-Time Stream Processing with MapR | 7 hours | In 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. |
| kafkastreams | Building Stream Processing Applications with Kafka Streams | 7 hours | Kafka Streams is a client-side library for building applications and microservices whose data is passed to and from a Kafka messaging system. Traditionally, Apache Kafka has relied on Apache Spark or Apache Storm to process data between message producers and consumers. By calling the Kafka Streams API from within an application, data can be processed directly within Kafka, bypassing the need for sending the data to a separate cluster for processing. In this instructor-led, live training, participants will learn how to integrate Kafka Streams into a set of sample Java applications that pass data to and from Apache Kafka for stream processing. By the end of this training, participants will be able to: - Understand Kafka Streams features and advantages over other stream processing frameworks - Process stream data directly within a Kafka cluster - Write a Java or Scala application or microservice that integrates with Kafka and Kafka Streams - Write concise code that transforms input Kafka topics into output Kafka topics - Build, package and deploy the application Audience - Developers 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 |
| introtostreamprocessing | A Practical Introduction to Stream Processing | 21 hours | Stream 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. |
| beam | Unified Batch and Stream Processing with Apache Beam | 14 hours | Apache 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. |
| confluent | Building Kafka Solutions with Confluent | 14 hours | This instructor-led, live training (onsite or remote) is aimed at engineers who wish to use Confluent (a distribution of Kafka) to build and manage a real-time data processing platform for their applications. By the end of this training, participants will be able to: - Install and configure Confluent Platform. - Use Confluent's management tools and services to run Kafka more easily. - Store and process incoming stream data. - Optimize and manage Kafka clusters. - Secure data streams. Format of the Course - Interactive lecture and discussion. - Lots of exercises and practice. - Hands-on implementation in a live-lab environment. Course Customization Options - This course is based on the open source version of Confluent: Confluent Open Source. - To request a customized training for this course, please contact us to arrange. |
Upcoming Stream Processing Courses
| Course | Course Date | Course Price [Remote / Classroom] |
|---|---|---|
| Apache Apex: Processing Big Data-in-Motion - Central Plaza - NobleProg Hong Kong | Wed, 2019-01-02 09:30 | HK$32187 / HK$50087 |
| Apache Apex: Processing Big Data-in-Motion - International Commerce Centre - NobleProg Hong Kong | Tue, 2019-01-15 09:30 | HK$32187 / HK$48587 |
| Apache Apex: Processing Big Data-in-Motion - Central Plaza - NobleProg Hong Kong | Tue, 2019-03-05 09:30 | HK$32187 / HK$50087 |
| Apache Apex: Processing Big Data-in-Motion - Central Plaza - NobleProg Hong Kong | Wed, 2019-04-24 09:30 | HK$32187 / HK$50087 |
| Apache Apex: Processing Big Data-in-Motion - Central Plaza - NobleProg Hong Kong | Wed, 2019-07-03 09:30 | HK$32187 / HK$50087 |
Other countries
Consulting
Course Discounts
| Course | Venue | Course Date | Course Price [Remote / Classroom] |
|---|---|---|---|
| Matlab for Predictive Analytics | Grand Century Place - NobleProg Hong Kong | Wed, 2019-02-06 09:30 | HK$41342 / HK$57742 |
| Machine Learning on iOS | The Center - NobleProg Hong Kong | Wed, 2019-02-13 09:30 | HK$27562 / HK$42162 |
| Introduction to R | International Commerce Centre - NobleProg Hong Kong | Mon, 2019-03-18 09:30 | HK$41342 / HK$57742 |
| Machine Learning Fundamentals with R | Miramar - NobleProg Hong Kong | Tue, 2019-04-30 09:30 | HK$27562 / HK$41162 |
| BPMN 2.0 for Business Analysts | Yen Sheng Centre - NobleProg Hong Kong | Wed, 2019-05-01 09:30 | HK$41342 / HK$57142 |
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