Local, instructor-led live Big Data training courses start with an introduction to elemental concepts of Big Data, then progress into the programming languages and methodologies used to perform Data Analysis. Tools and infrastructure for enabling Big Data storage, Distributed Processing, and Scalability are discussed, compared and implemented in demo practice sessions.

Big Data training is available as "onsite live training" or "remote live training". Luxembourg onsite live Big Data trainings 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

Testimonials

★★★★★

This is one of the best hands-on with exercises programming courses I have ever taken.

Laura Kahn

Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

This is one of the best quality online training I have ever taken in my 13 year career. Keep up the great work!.

Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

It was very hands-on, we spent half the time actually doing things in Clouded/Hardtop, running different commands, checking the system, and so on. The extra materials (books, websites, etc. .) were really appreciated, we will have to continue to learn. The installations were quite fun, and very handy, the cluster setup from scratch was really good.

Ericsson

Course: Administrator Training for Apache Hadoop

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 trainer was fantastic and really knew his stuff. I learned a lot about the software I didn't know previously which will help a lot at my job!

Steve McPhail - Alberta Health Services - Information Technology

Course: Data Analysis with Hive/HiveQL

The high level principles about Hive, HDFS..

Geert Suys - Proximus Group

Course: Data Analysis with Hive/HiveQL

The handson. The mix practice/theroy

Proximus Group

Course: Data Analysis with Hive/HiveQL

Fulvio was able to grasp our companies business case and was able to correlate with the course material, almost instantly.

Samuel Peeters - Proximus Group

Course: Data Analysis with Hive/HiveQL

Lot of hands-on exercises.

Ericsson

Course: Administrator Training for Apache Hadoop

Ambari management tool. Ability to discuss practical Hadoop experiences from other business case than telecom.

Ericsson

Course: Administrator Training for Apache Hadoop

I enjoyed the good balance between theory and hands-on labs.

N. V. Nederlandse Spoorwegen

Course: Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing

I generally was benefit from the more understanding of Ignite.

N. V. Nederlandse Spoorwegen

Course: Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing

I mostly liked the good lectures.

N. V. Nederlandse Spoorwegen

Course: Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing

Richard was very willing to digress when we wanted to ask semi-related questions about things not on the syllabus. Explanations were clear and he was up front about caveats in any advice he gave us.

ARM Limited

Course: Spark for Developers

I generally liked the fernando's knowledge.

Valentin de Dianous - Informatique ProContact INC.

Course: Big Data Architect

I really enjoyed the all the best.

Halil polat - Amazon Development Center Poland Sp. z o.o.

Course: Data Mining and Analysis

The trainer concentrated on the key topics.

Amazon Development Center Poland Sp. z o.o.

Course: Data Mining and Analysis

Expertise and huge knowledge of the trainer.

Amazon Development Center Poland Sp. z o.o.

Course: Data Mining and Analysis

I was benefit from the guidance and sharing life examples + answering all questions.

Marta Melloch - Amazon Development Center Poland Sp. z o.o.

Course: Data Mining and Analysis

I really enjoyed learning new and interesting things.

SIVECO Romania SA

Course: Data Mining

I was benefit from the good examples and opportunity to follow along.

Environmental and Climate Change Canada

Course: Foundation R

I genuinely enjoyed the hands passed exercises.

Yunfa Zhu - Environmental and Climate Change Canada

Course: Foundation R

I thought he did a great job of tailoring the experience to the audience. This class is mostly designed to cover data analysis with HIVE, but me and my co-worker are doing HIVE administration with no real data analytics responsibilities.

ian reif - Franchise Tax Board

Course: Data Analysis with Hive/HiveQL

The VM I liked very much The Teacher was very knowledgeable regarding the topic as well as other topics, he was very nice and friendly I liked the facility in Dubai.

Safar Alqahtani - Elm Information Security

Course: Big Data Analytics in Health

Recalling/reviewing keypoints of the topics discussed.

Paolo Angelo Gaton - SMS Global Technologies Inc.

Course: Building Stream Processing Applications with Kafka Streams

Roxane Santiago - SMS Global Technologies Inc.

Course: Building Stream Processing Applications with Kafka Streams

practice tasks

Pawel Kozikowski - GE Medical Systems Polska Sp. Zoo

Course: Python and Spark for Big Data (PySpark)

Excercises were good, trainer was helpful. I also assume that trainer adapted a little to our knowledge after first day.

Capgemini Polska sp. z o.o.

Course: Teradata Fundamentals

Trainer's enthusiasm and energy

Capgemini Polska sp. z o.o.

Course: Teradata Fundamentals

Tips to improve performance

Capgemini Polska sp. z o.o.

Course: Teradata Fundamentals

The trainer was very concern about individual understanding.

Muhammad Surajo Sanusi - Birmingham City University

Course: Foundation R

Excellent presentation and it gives me confidence to build on knowledge gained.

Birmingham City University

Course: Foundation R

Background knowledge and 'provenance' of trainer.

Francis McGonigal - Birmingham City University

Course: Foundation R

practical things of doing, also theory was served good by Ajay

Dominik Mazur - Capgemini Polska Sp. z o.o.

Course: Hadoop Administration on MapR

Exercises

Capgemini Polska Sp. z o.o.

Course: Hadoop Administration on MapR

Resources

Hafiz Rana - Birmingham City University

Course: Foundation R

Good explanations on how we do things

Birmingham City University

Course: Foundation R

I feel more confident with coding now. I've never done it before but now I understand that it's not rocket science and I can do it when necessary.

Anna Yartseva - Birmingham City University

Course: Foundation R

I found the training good, very informative....but could have been spread over 4 or 5 days, allowing us to go into more details on different aspects.

Veterans Affairs Canada

Course: Hadoop Administration

I found this course gave a great overview and quickly touched some areas I wasn't even considering.

Veterans Affairs Canada

Course: Hadoop Administration

The broad coverage of the subjects

Roche

Course: Big Data Storage Solution - NoSQL

Small group (4 trainees) and we could progress together. Also the trainer could so help everybody.

ICE International Copyright Enterprise Germany GmbH

Course: Spark for Developers

Ajay was very friendly, helpful and also knowledgable about the topic he was discussing.

Biniam Guulay - ICE International Copyright Enterprise Germany GmbH

Course: Spark for Developers

The lab exercises. Applying the theory from the first day in subsequent days.

Dell

Course: A Practical Introduction to Stream Processing

* Organization * Trainer's expertise with the subject

ENGIE- 101 Arch Street

Course: Python and Spark for Big Data (PySpark)

This is one of the best quality online training I have ever taken in my 13 year career. Keep up the great work!.

Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

Big Data Subcategories

Big Data Course Outlines

Title

Duration

Overview

Title

Duration

Overview

Apache Accumulo Fundamentals

21 hours

Overview

Apache Accumulo is a sorted, distributed key/value store that provides robust, scalable data storage and retrieval. It is based on the design of Google's BigTable and is powered by Apache Hadoop, Apache Zookeeper, and Apache Thrift.

This instructor-led, live courses covers the working principles behind Accumulo and walks participants through the development of a sample application on Apache Accumulo.

Format of the Course

- Part lecture, part discussion, hands-on development and implementation, occasional tests to gauge understanding

IoT ( Internet of Things) for Entrepreneurs, Managers and Investors

21 hours

Overview

Unlike other technologies, IoT is far more complex encompassing almost every branch of core Engineering-Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics and Mobile. For each of its engineering layers, there are aspects of economics, standards, regulations and evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering.

Summary

-

An advanced training program covering the current state of the art in Internet of Things

-

Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help businesses and organizations.

-

Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation and use cases around connected devices & things

Target Audience

-

Managers responsible for business and operational processes within their respective organizations and want to know how to harness IoT to make their systems and processes more efficient.

-

Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it in an effective manner.

Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.

In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.

However, the underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.

Due to unbounded opportunities in IoT business, a large number of small and medium sized entrepreneurs jumped on a bandwagon of IoT gold rush. Also due to emergence of open source electronics and IoT platform, cost of development of IoT system and further managing its sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their device with Internet or Mobile app.

This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in home & city automation (smart homes and cities), Industrial Internet, healthcare, Govt., Mobile Cellular and other areas.

-

Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and Total control plane

-

M2M Wireless protocols for IoT- WiFi, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one?

-

Mobile/Desktop/Web app- for registration, data acquisition and control –Available M2M data acquisition platform for IoT-–Xively, Omega and NovoTech, etc.

-

Security issues and security solutions for IoT

-

Open source/commercial electronics platform for IoT-Raspberry Pi, Arduino , ArmMbedLPC etc

-

Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT cloud in addition to other minor IoT clouds

-

Studies of business and technology of some of the common IoT devices like Home automation, Smoke alarm, vehicles, military, home health etc.

MATLAB for Financial Applications

21 hours

Overview

MATLAB is a numerical computing environment and programming language developed by MathWorks.

Real-Time Stream Processing with MapR

7 hours

Overview

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.

Magellan: Geospatial Analytics on Spark

14 hours

Overview

Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics.

This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark.

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

- Efficiently query, parse and join geospatial datasets at scale
- Implement geospatial data in business intelligence and predictive analytics applications
- Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables

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.

Apache Kylin: From Classic OLAP to Real-Time Data Warehouse

14 hours

Overview

Apache Kylin is an extreme, distributed analytics engine for big data.

In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse.

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

- Consume real-time streaming data using Kylin
- Utilize Apache Kylin's powerful features, rich SQL interface, spark cubing and subsecond query latency

Note

- We use the latest version of Kylin (as of this writing, Apache Kylin v2.0)

Audience

- Big data engineers
- Big Data analysts

Format of the course

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

Confluent KSQL

7 hours

Overview

Confluent KSQL is a stream processing framework built on top of Apache Kafka. It enables real-time data processing using SQL operations.

This instructor-led, live training (onsite or remote) is aimed at developers who wish to implement Apache Kafka stream processing without writing code.

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

- Install and configure Confluent KSQL.
- Set up a stream processing pipeline using only SQL commands (no Java or Python coding).
- Carry out data filtering, transformations, aggregations, joins, windowing, and sessionization entirely in SQL.
- Design and deploy interactive, continuous queries for streaming ETL and real-time analytics.

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.

KNIME Analytics Platform - comprehensive training

35 hours

Overview

KNIME is a free and open-source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface and use of JDBC allows assembly of nodes blending different data sources, including preprocessing (ETL: Extraction, Transformation, Loading), for modeling, data analysis and visualization without, or with only minimal, programming. To some extent as advanced analytics tool KNIME can be considered as a SAS alternative.

Since 2006, KNIME has been used in pharmaceutical research, it also used in other areas like CRM customer data analysis, business intelligence and financial data analysis.

KNIME Analytics Platform for BI

21 hours

Overview

KNIME Analytics Platform is a leading open source option for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist and business analyst.

This course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows

Knowledge Discovery in Databases (KDD)

21 hours

Overview

Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. Real-life applications for this data mining technique include marketing, fraud detection, telecommunication and manufacturing.

In this instructor-led, live course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes.

Audience

- Data analysts or anyone interested in learning how to interpret data to solve problems

Format of the Course

- After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations.

Stream Processing with Kafka Streams

7 hours

Overview

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

A Practical Introduction to Stream Processing

21 hours

Overview

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.
- Integrate 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.

MemSQL

28 hours

Overview

MemSQL is an in-memory, distributed, SQL database management system for cloud and on-premises. It's a real-time data warehouse that immediately delivers insights from live and historical data.

In this instructor-led, live training, participants will learn the essentials of MemSQL for development and administration.

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

- Understand the key concepts and characteristics of MemSQL
- Install, design, maintain, and operate MemSQL
- Optimize schemas in MemSQL
- Improve queries in MemSQL
- Benchmark performance in MemSQL
- Build real-time data applications using MemSQL

Audience

- Developers
- Administrators
- Operation Engineers

Format of the course

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

Apache Avro: Data Serialization for Distributed Applications

14 hours

Overview

Audience

- Developers

Format of the Course

- Lectures, hands-on practice, small tests along the way to gauge understanding

Impala for Business Intelligence

21 hours

Overview

Cloudera Impala is an open source massively parallel processing (MPP) SQL query engine for Apache Hadoop clusters.

Impala enables users to issue low-latency SQL queries to data stored in Hadoop Distributed File System and Apache Hbase without requiring data movement or transformation.

Audience

This course is aimed at analysts and data scientists performing analysis on data stored in Hadoop via Business Intelligence or SQL tools.

After this course delegates will be able to

- Extract meaningful information from Hadoop clusters with Impala.
- Write specific programs to facilitate Business Intelligence in Impala SQL Dialect.
- Troubleshoot Impala.

Data Analysis with Hive/HiveQL

7 hours

Overview

This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive

Hortonworks Data Platform (HDP) for Administrators

21 hours

Overview

Hortonworks Data Platform (HDP) is an open-source Apache Hadoop support platform that provides a stable foundation for developing big data solutions on the Apache Hadoop ecosystem.

This instructor-led, live training (onsite or remote) introduces Hortonworks Data Platform (HDP) and walks participants through the deployment of Spark + Hadoop solution.

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

- Use Hortonworks to reliably run Hadoop at a large scale.
- Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows.
- Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project.
- Process different types of data, including structured, unstructured, in-motion, and at-rest.

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.

HBase for Developers

21 hours

Overview

This course introduces HBase – a NoSQL store on top of Hadoop. The course is intended for developers who will be using HBase to develop applications, and administrators who will manage HBase clusters.

We will walk a developer through HBase architecture and data modelling and application development on HBase. It will also discuss using MapReduce with HBase, and some administration topics, related to performance optimization. The course is very hands-on with lots of lab exercises.

Duration : 3 days

Audience : Developers & Administrators

Hadoop with Python

28 hours

Overview

Hadoop is a popular Big Data processing framework. Python is a high-level programming language famous for its clear syntax and code readibility.

In this instructor-led, live training, participants will learn how to work with Hadoop, MapReduce, Pig, and Spark using Python as they step through multiple examples and use cases.

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

- Understand the basic concepts behind Hadoop, MapReduce, Pig, and Spark
- Use Python with Hadoop Distributed File System (HDFS), MapReduce, Pig, and Spark
- Use Snakebite to programmatically access HDFS within Python
- Use mrjob to write MapReduce jobs in Python
- Write Spark programs with Python
- Extend the functionality of pig using Python UDFs
- Manage MapReduce jobs and Pig scripts using Luigi

Audience

- Developers
- IT Professionals

Format of the course

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

Hadoop Administration on MapR

28 hours

Overview

Audience:

This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand.

Hadoop for Project Managers

14 hours

Overview

As more and more software and IT projects migrate from local processing and data management to distributed processing and big data storage, Project Managers are finding the need to upgrade their knowledge and skills to grasp the concepts and practices relevant to Big Data projects and opportunities.

This course introduces Project Managers to the most popular Big Data processing framework: Hadoop.

In this instructor-led training, participants will learn the core components of the Hadoop ecosystem and how these technologies can be used to solve large-scale problems. In learning these foundations, participants will also improve their ability to communicate with the developers and implementers of these systems as well as the data scientists and analysts that many IT projects involve.

Audience

- Project Managers wishing to implement Hadoop into their existing development or IT infrastructure
- Project Managers needing to communicate with cross-functional teams that include big data engineers, data scientists and business analysts

Format of the course

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

Hadoop for Developers and Administrators

21 hours

Overview

Hadoop is the most popular Big Data processing framework.

Matlab for Predictive Analytics

21 hours

Overview

Predictive analytics is the process of using data analytics to make predictions about the future. This process uses data along with data mining, statistics, and machine learning techniques to create a predictive model for forecasting future events.

In this instructor-led, live training, participants will learn how to use Matlab to build predictive models and apply them to large sample data sets to predict future events based on the data.

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

- Create predictive models to analyze patterns in historical and transactional data
- Use predictive modeling to identify risks and opportunities
- Build mathematical models that capture important trends
- Use data from devices and business systems to reduce waste, save time, or cut costs

Audience

- Developers
- Engineers
- Domain experts

Format of the course

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

Machine Learning and Big Data

7 hours

Overview

This instructor-led, live training (onsite or remote) is aimed at technical persons who wish to learn how to implement a machine learning strategy while maximizing the use of big data.

By the end of this training, participants will:

- Understand the evolution and trends for machine learning.
- Know how machine learning is being used across different industries.
- Become familiar with the tools, skills and services available to implement machine learning within an organization.
- Understand how machine learning can be used to enhance data mining and analysis.
- Learn what a data middle backend is, and how it is being used by businesses.
- Understand the role that big data and intelligent applications are playing across industries.

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.

Hadoop for Developers (4 days)

28 hours

Overview

Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. This course will introduce a developer to various components (HDFS, MapReduce, Pig, Hive and HBase) Hadoop ecosystem.

Apache Spark SQL

7 hours

Overview

Spark SQL is Apache Spark's module for working with structured and unstructured data. Spark SQL provides information about the structure of the data as well as the computation being performed. This information can be used to perform optimizations. Two common uses for Spark SQL are:
- to execute SQL queries.
- to read data from an existing Hive installation.

In this instructor-led, live training (onsite or remote), participants will learn how to analyze various types of data sets using Spark SQL.

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

- Install and configure Spark SQL.
- Perform data analysis using Spark SQL.
- Query data sets in different formats.
- Visualize data and query results.

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.

Zeppelin for Interactive Data Analytics

14 hours

Overview

Apache Zeppelin is a web-based notebook for capturing, exploring, visualizing and sharing Hadoop and Spark based data.

This instructor-led, live training introduces the concepts behind interactive data analytics and walks participants through the deployment and usage of Zeppelin in a single-user or multi-user environment.

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

- Install and configure Zeppelin
- Develop, organize, execute and share data in a browser-based interface
- Visualize results without referring to the command line or cluster details
- Execute and collaborate on long workflows
- Work with any of a number of plug-in language/data-processing-backends, such as Scala (with Apache Spark), Python (with Apache Spark), Spark SQL, JDBC, Markdown and Shell.
- Integrate Zeppelin with Spark, Flink and Map Reduce
- Secure multi-user instances of Zeppelin with Apache Shiro

Audience

- Data engineers
- Data analysts
- Data scientists
- Software developers

Format of the course

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

Vespa: Serving Large-Scale Data in Real-Time

14 hours

Overview

Vespa is an open-source big data processing and serving engine created by Yahoo. It is used to respond to user queries, make recommendations, and provide personalized content and advertisements in real-time.

This instructor-led, live training introduces the challenges of serving large-scale data and walks participants through the creation of an application that can compute responses to user requests, over large datasets in real-time.

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

- Use Vespa to quickly compute data (store, search, rank, organize) at serving time while a user waits
- Implement Vespa into existing applications involving feature search, recommendations, and personalization
- Integrate and deploy Vespa with existing big data systems such as Hadoop and Storm.

Audience

- Developers

Format of the course

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

Tigon: Real-time Streaming for the Real World

14 hours

Overview

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

Teradata Fundamentals

21 hours

Overview

Teradata is one of the popular Relational Database Management System. It is mainly suitable for building large scale data warehousing applications. Teradata achieves this by the concept of parallelism.

This course introduces the delegates to Teradata.

Upcoming Big Data Courses

Data Vault: Building a Scalable Data Warehouse

2019-10-14 09:30:00

Luxembourg, Place de la Gare

Remote

6000EUR

Classroom

7000EUR

MATLAB for Financial Applications

2019-10-23 09:30:00

Luxembourg, Place de la Gare

Remote

5250EUR

Classroom

6050EUR

Foundation R

2019-10-29 09:30:00

Luxembourg, Place de la Gare

Remote

1750EUR

Classroom

2150EUR

Process Mining

2019-11-05 09:30:00

Luxembourg, Place de la Gare

Remote

5250EUR

Classroom

6050EUR

MonetDB

2019-11-19 09:30:00

Luxembourg, Place de la Gare

Remote

6000EUR

Classroom

7000EUR

Other regions

;Luxembourg City

Other countries

These courses are also available in other countries ››

Consulting

Big Data Consulting

Weekend Big Data courses, Evening Big Data training, Big Data boot camp, Big Data instructor-led, Weekend Big Data training, Evening Big Data courses, Big Data coaching, Big Data instructor, Big Data trainer, Big Data training courses, Big Data classes, Big Data on-site, Big Data private courses, Big Data one on one training