Big Data Training Courses

Big Data Training Courses

Local, instructor-led live Big Data training courses start with an introduction to elemental concepts of Big Data, then progress into the programmeming 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". Onsite live Big Data training can be carried out locally on customer premises in the UK or in NobleProg corporate training centres in the UK. Remote live training is carried out by way of an interactive, remote desktop.

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Big Data Subcategories

Hadoop Training CoursesHadoop
Data Mining Training CoursesData Mining
Apache Spark Training CoursesApache Spark
Apache ZooKeeper Training CoursesApache ZooKeeper
Avro Training CoursesAvro
Apache ActiveMQ Training CoursesApache ActiveMQ
Teradata Training CoursesTeradata
Stream Processing Training CoursesStream Processing
Data Warehouse Training CoursesData Warehouse
Apache Drill Training CoursesApache Drill
Dremio Training CoursesDremio
Apache Kylin Training CoursesApache Kylin
Apache Accumulo Training CoursesApache Accumulo
Apache Zeppelin Training CoursesApache Zeppelin
Apache Hama Training CoursesApache Hama
Apache Arrow Training CoursesApache Arrow

Big Data Course Outlines

Title
Duration
Overview
Title
Duration
Overview

Statistics with SPSS Predictive Analytics Software

14 hours
Overview
Goal:

Learning to work with SPSS at the level of independence

The addressees:

Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package and learn popular data mining techniques.

SolrCloud

14 hours
Overview
Apache SolrCloud is a distributed data processing engine that facilitates the searching and indexing of files on a distributed network.

In this instructor-led, live training, participants will learn how to set up a SolrCloud instance on Amazon AWS.

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

- Understand SolCloud's features and how they compare to those of conventional master-slave clusters
- Configure a SolCloud centralized cluster
- Automate processes such as communicating with shards, adding documents to the shards, etc.
- Use Zookeeper in conjunction with SolrCloud to further automate processes
- Use the interface to manage error reporting
- Load balance a SolrCloud installation
- Configure SolrCloud for continuous processing and fail-over

Audience

- Solr Developers
- Project Managers
- System Administrators
- Search Analysts

Format of the course

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

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

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

Python and Spark for Big Data (PySpark)

21 hours
Overview
In this instructor-led, live training in the UK, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.

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

- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world circumstances.
- Use different tools and techniques for big data analysis using PySpark.

Big Data Business Intelligence for Criminal Intelligence Analysis

35 hours
Overview
Advances in technologies and the increasing amount of information are transforming how law enforcement is conducted. The challenges that Big Data pose are nearly as daunting as Big Data's promise. Storing data efficiently is one of these challenges; effectively analyzing it is another.

In this instructor-led, live training, participants will learn the mindset with which to approach Big Data technologies, assess their impact on existing processes and policies, and implement these technologies for the purpose of identifying criminal activity and preventing crime. Case studies from law enforcement organizations around the world will be examined to gain insights on their adoption approaches, challenges and results.

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

- Combine Big Data technology with traditional data gathering processes to piece together a story during an investigation
- Implement industrial big data storage and processing solutions for data analysis
- Prepare a proposal for the adoption of the most adequate tools and processes for enabling a data-driven approach to criminal investigation

Audience

- Law Enforcement specialists with a technical background

Format of the course

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

Big Data Analytics for Telecom Regulators

14 hours
Overview
To meet compliance of the regulators, CSPs (Communication service providers) can tap into Big Data Analytics which not only help them to meet compliance but within the scope of same project they can increase customer satisfaction and thus reduce the churn. In fact since compliance is related to Quality of service tied to a contract, any initiative towards meeting the compliance, will improve the “competitive edge” of the CSPs. Therefore, it is important that Regulators should be able to advise/guide a set of Big Data analytic practice for CSPs that will be of mutual benefit between the regulators and CSPs.

The course consists of 8 modules (4 on day 1, and 4 on day 2)

Introduction to Graph Computing

28 hours
Overview
In this instructor-led, live training in the UK, 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.

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

Apache NiFi for Developers

7 hours
Overview
In this instructor-led, live training in the UK, 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.

Apache NiFi for Administrators

21 hours
Overview
In this instructor-led, live training in the UK (onsite or remote), 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.

Data Vault: Building a Scalable Data Warehouse

28 hours
Overview
In this instructor-led, live training in the UK, participants will learn how to build a Data Vault.

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

- Understand the architecture and design concepts behind Data Vault 2.0, and its interaction with Big Data, NoSQL and AI.
- Use data vaulting techniques to enable auditing, tracing, and inspection of historical data in a data warehouse.
- Develop a consistent and repeatable ETL (Extract, Transform, Load) process.
- Build and deploy highly scalable and repeatable warehouses.

Apache Drill

21 hours
Overview
Apache Drill is a schema-free, distributed, in-memory columnar SQL query engine for Hadoop, NoSQL and other Cloud and file storage systems. The power of Apache Drill lies in its ability to join data from multiple data stores using a single query. Apache Drill supports numerous NoSQL databases and file systems, including HBase, MongoDB, MapR-DB, HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, Swift, NAS and local files. Apache Drill is the open source version of Google's Dremel system which is available as an infrastructure service called Google BigQuery.

In this instructor-led, live training, participants will learn the fundamentals of Apache Drill, then leverage the power and convenience of SQL to interactively query big data across multiple data sources, without writing code. Participants will also learn how to optimize their Drill queries for distributed SQL execution.

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

- Perform "self-service" exploration on structured and semi-structured data on Hadoop
- Query known as well as unknown data using SQL queries
- Understand how Apache Drills receives and executes queries
- Write SQL queries to analyze different types of data, including structured data in Hive, semi-structured data in HBase or MapR-DB tables, and data saved in files such as Parquet and JSON.
- Use Apache Drill to perform on-the-fly schema discovery, bypassing the need for complex ETL and schema operations
- Integrate Apache Drill with BI (Business Intelligence) tools such as Tableau, Qlikview, MicroStrategy and Excel

Audience

- Data analysts
- Data scientists
- SQL programmers

Format of the course

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

Datameer for Data Analysts

14 hours
Overview
Datameer is a business intelligence and analytics platform built on Hadoop. It allows end-users to access, explore and correlate large-scale, structured, semi-structured and unstructured data in an easy-to-use fashion.

In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources.

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

- Create, curate, and interactively explore an enterprise data lake
- Access business intelligence data warehouses, transactional databases and other analytic stores
- Use a spreadsheet user-interface to design end-to-end data processing pipelines
- Access pre-built functions to explore complex data relationships
- Use drag-and-drop wizards to visualize data and create dashboards
- Use tables, charts, graphs, and maps to analyze query results

Audience

- Data analysts

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

Apache Ignite for Developers

14 hours
Overview
In this instructor-led, live training in the UK, 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.

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

Apache Apex: Processing Big Data-in-Motion

21 hours
Overview
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

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.

Alluxio: Unifying Disparate Storage Systems

7 hours
Overview
Alluxio is an open-source virtual distributed storage system that unifies disparate storage systems and enables applications to interact with data at memory speed. It is used by companies such as Intel, Baidu and Alibaba.

In this instructor-led, live training, participants will learn how to use Alluxio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio.

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

- Develop an application with Alluxio
- Connect big data systems and applications while preserving one namespace
- Efficiently extract value from big data in any storage format
- Improve workload performance
- Deploy and manage Alluxio standalone or clustered

Audience

- Data scientist
- Developer
- System administrator

Format of the course

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

Apache Flink Fundamentals

28 hours
Overview
This instructor-led, live training in the UK 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 in Apache Flink.

Samza for Stream Processing

14 hours
Overview
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

Zeppelin for Interactive Data Analytics

14 hours
Overview
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

MonetDB

28 hours
Overview
MonetDB is an open-source database that pioneered the column-store technology approach.

In this instructor-led, live training, participants will learn how to use MonetDB and how to get the most value out of it.

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

- Understand MonetDB and its features
- Install and get started with MonetDB
- Explore and perform different functions and tasks in MonetDB
- Accelerate the delivery of their project by maximizing MonetDB capabilities

Audience

- Developers
- Technical experts

Format of the course

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

AI Awareness for Telecom

14 hours
Overview
AI is a collection of technologies for building intelligent systems capable of understanding data and the activities surrounding the data to make "intelligent decisions". For Telecom providers, building applications and services that make use of AI could open the door for improved operations and servicing in areas such as maintenance and network optimization.

In this course we examine the various technologies that make up AI and the skill sets required to put them to use. Throughout the course, we examine AI's specific applications within the Telecom industry.

Audience

- Network engineers
- Network operations personnel
- Telecom technical managers

Format of the course

- Part lecture, part discussion, hands-on exercises

Hortonworks Data Platform (HDP) for Administrators

21 hours
Overview
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.

Unified Batch and Stream Processing with Apache Beam

14 hours
Overview
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.

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.

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.

Pivotal Greenplum for Developers

21 hours
Overview
This instructor-led, live training in the UK (onsite or remote) is aimed at developers who wish to set up a multi-node Greenplum database.

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

- Install and configure Pivotal Greenplum.
- Model data in accordance to current needs and future expansion plans.
- Carry out different techniques for distribute data across multiple nodes.
- Improve database performance through tuning.
- Monitor and troubleshoot a Greenplum database.

Building Kafka Solutions with Confluent

14 hours
Overview
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.

Data Mining with Python

14 hours
Overview
This instructor-led, live training (onsite or remote) is aimed at data analysts and data scientists who wish to implement more advanced data analytics techniques for data mining using Python.

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

- Understand important areas of data mining, including association rule mining, text sentiment analysis, automatic text summarization, and data anomaly detection.
- Compare and implement various strategies for solving real-world data mining problems.
- Understand and interpret the 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.

Upcoming Big Data Courses

Apache Drill Query Optimization

2019-07-31 09:30:00
Bradford - Carlisle Business Centre
Remote
£1200
 Classroom
£1450
Read more

Apache Drill Query Optimization

2019-08-05 09:30:00
Leicester - Knighton Road
Remote
£1200
 Classroom
£1400
Read more

Pivotal Greenplum for Developers

2019-08-05 09:30:00
London, Hatton Garden
Remote
£3600
 Classroom
£4725
Read more

Pivotal Greenplum for Developers

2019-08-07 09:30:00
Birmingham
Remote
£3600
 Classroom
£4575
Read more

Pivotal Greenplum for Developers

2019-08-07 09:30:00
Bristol, Temple Gate
Remote
£3600
 Classroom
£4350
Read more

Other regions

;BirminghamBrightonBristolCardiffLeedsLondonManchesterNewcastleGlasgowSheffieldSouthamptonPortsmouthLiverpoolEdinburghBathCambridgeOxfordPlymouthSwanseaBradfordExeterLeicesterYorkCoventryAberdeenReadingSwindonJersey, CIBelfast City

Other countries

These courses are also available in other countries ››

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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

Course Discounts

OpenLDAP Workshop

Mon, 2019-08-05 09:30
Cambridge
Remote
£3600
£3564
 Classroom
£4275
£4239
Read more

Data analysis with Tableau

Tue, 2019-08-13 09:30
London, Hatton Garden
Remote
£2600
£2340
 Classroom
£3350
£3090
Read more

Artificial Intelligence Overview

Tue, 2019-10-29 09:30
Glasgow
Remote
£1300
£1170
 Classroom
£1650
£1520
Read more

Modelling Decision and Rules with OMG DMN

Tue, 2019-11-05 09:30
Newcastle
Remote
£2600
£2340
 Classroom
£3000
£2740
Read more

Data analysis with Tableau

Mon, 2020-01-06 09:30
Oxford - The Quorum
Remote
£2600
£2340
 Classroom
£3150
£2890
Read more

OpenCL

Mon, 2020-01-20 09:30
York - Priory Street Centre
Remote
£3900
N/A
 Classroom
£4350
£3960
Read more

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