
Online or onsite, 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 "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Finland onsite live Big Data trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Testimonials
I generally liked the fernando's knowledge.
Valentin de Dianous - Informatique ProContact INC.
Course: Big Data Architect
The tutor, Mr. Michael Yan, 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 introduction of new packages
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
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 to meet 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
The broad coverage of the subjects
Roche
Course: Big Data Storage Solution - NoSQL
Overall the Content was good.
Sameer Rohadia
Course: A practical introduction to Data Analysis and Big Data
presentation of technologies
Continental AG / Abteilung: CF IT Finance
Course: A practical introduction to Data Analysis and Big Data
Willingness to share more
Balaram Chandra Paul
Course: A practical introduction to Data Analysis and Big Data
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
Intensity, Training materials and expertise, Clarity, Excellent communication with Alessandra
Marija Hornis Dmitrovic - Marija Hornis
Course: Data Science for Big Data Analytics
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
Many hands-on sessions.
Jacek Pieczątka
Course: Administrator Training for Apache Hadoop
Big competences of Trainer
Grzegorz Gorski
Course: Administrator Training for Apache Hadoop
Trainer give reallive Examples
Simon Hahn
Course: Administrator Training for Apache Hadoop
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
I found this course gave a great overview and quickly touched some areas I wasn't even considering.
Veterans Affairs Canada
Course: Hadoop Administration
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
practical things of doing, also theory was served good by Ajay
Dominik Mazur - Capgemini Polska Sp. z o.o.
Course: Hadoop Administration on MapR
The trainer was always open for questions and willing to answer and explain everything. He seems to have very good and deep knowledge of what he is teaching. We were able to focus more on topics that might bring value for us since we were only two students.
DEVK Deutsche Eisenbahn Versicherung Sach- und HUK-Versicherungsverein a.G.
Course: Hadoop and Spark for Administrators
The working sessions where we worked on real issues we are trying to solve and built out solutions together.
Jacob Jaskolka, BHG Financial
Course: Apache NiFi for Administrators
Hands on
Isaac Hastings, New Zealand Defence Force
Course: Apache NiFi for Administrators
Hands on.
Dwayne McDonald - Isaac Hastings, New Zealand Defence Force
Course: Apache NiFi for Administrators
James answered my every question, was extremely patient and explained me everything. NIFI was Greek and latin for me and i have learnt what was a processor, flunnel and the root process from Beginner level to Advanced Level.
Firdous Hashim Ali - MOD A BLOCK
Course: Apache NiFi for Developers
That I had it in the first place.
Peter Scales - CACI Ltd
Course: Apache NiFi for Developers
Work exercises with cluster to see performance of nodes across cluster and extended functionality
CACI Ltd
Course: Apache NiFi for Developers
The fact that we were able to take with us most of the information/course/presentation/exercises done, so that we can look over them and perhaps redo what we didint understand first time or improve what we already did.
Raul Mihail Rat - Edina Kiss, Accenture Industrial SS
Course: Python, Spark, and Hadoop for Big Data
I liked that it managed to lay the foundations of the topic and go to some quite advanced exercises. Also provided easy ways to write/test the code.
Ionut Goga - Edina Kiss, Accenture Industrial SS
Course: Python, Spark, and Hadoop for Big Data
The live examples
Ahmet Bolat - Edina Kiss, Accenture Industrial SS
Course: Python, Spark, and Hadoop for Big Data
good overview, good balance between theory and exercises
Proximus
Course: Data Analysis with Hive/HiveQL
It was a very practical training, I liked the hands-on exercises.
Proximus
Course: Data Analysis with Hive/HiveQL
Liked very much the interactive way of learning.
Luigi Loiacono
Course: Data Analysis with Hive/HiveQL
The information given was interesting and the best part was towards the end when we were provided with Data from Murex and worked on Data we are familiar with and perform operations to get results.
Jessica Chaar
Course: Data Mining and Analysis
The hands on exercise and the trainer capacity to explain complex topics in simple terms
youssef chamoun
Course: Data Mining and Analysis
I like the exercices done
Nour Assaf
Course: Data Mining and Analysis
I really enjoyed learning new and interesting things.
SIVECO Romania SA
Course: Data Mining
very tailored to needs
Yashan Wang
Course: Data Mining with R
The Topic
Accenture Inc.
Course: Data Vault: Building a Scalable Data Warehouse
Learning about all the chart types and what they are used for. Learning the value of decluttering. Learning about the methods to show time data.
Susan Williams
Course: Data Visualization
I really appreciated that Jeff utilized data and examples that were applicable to education data. He made it interesting and interactive.
Carol Wells Bazzichi
Course: Data Visualization
I thought that the information was interesting.
Allison May
Course: Data Visualization
The trainer was so knowledgeable and included areas I was interested in
Mohamed Salama
Course: Data Mining & Machine Learning with R
The trainer was very concern about individual understanding.
Muhammad Surajo Sanusi - Birmingham City University
Course: Foundation R
I genuinely enjoyed the hands passed exercises.
Yunfa Zhu - Environmental and Climate Change Canada
Course: Foundation R
I was benefit from the good examples and opportunity to follow along.
Environmental and Climate Change Canada
Course: Foundation R
Very useful in because it helps me understand what we can do with the data in our context. It will also help me
Nicolas NEMORIN - Adecco Groupe France
Course: KNIME Analytics Platform for BI
The way it was conducted, the way trainer keeps contact with audience, materials, everything was really good!
Marcin Prewo - GE Medical Systems Polska Sp. Z O.O.
Course: Process Mining
Open discussion with trainer
Tomek Danowski - GE Medical Systems Polska Sp. Z O.O.
Course: Process Mining
A lot of exercises, trainer was always helping us and giving the solution, he was always answering our questions & explaining our doubts. The trainer was also always checking with us about the break we would like to take etc.
GE Medical Systems Polska Sp. Z O.O.
Course: Process Mining
Sufficient hands on, trainer is knowledgable
Chris Tan
Course: A Practical Introduction to Stream Processing
The trainer was passionate and well-known what he said I appreciate his help and answers all our questions and suggested cases.
Course: A Practical Introduction to Stream Processing
The trainer was passionate and well-known what he said I appreciate his help and answers all our questions and suggested cases.
Course: A Practical Introduction to Stream Processing
Big Data Course Outlines in Finland
- Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
- Understand the features, core components, and architecture of Spark and Hadoop.
- Learn how to integrate Spark, Hadoop, and Python for big data processing.
- Explore the tools in the Spark ecosystem (Spark MlLib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
- Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
- Use Apache Mahout to scale machine learning algorithms.
- Install and configure Weka.
- Understand the Weka environment and workbench.
- Perform data mining tasks using Weka.
- Understand the fundamentals of data mining.
- Learn how to import and assess data quality with the Modeler.
- Develop, deploy, and evaluate data models efficiently.
- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world cases.
- Use different tools and techniques for big data analysis using PySpark.
- Data analysts or anyone interested in learning how to interpret data to solve problems
- 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.
- Consume real-time streaming data using Kylin
- Utilize Apache Kylin's powerful features, rich SQL interface, spark cubing and subsecond query latency
- We use the latest version of Kylin (as of this writing, Apache Kylin v2.0)
- Big data engineers
- Big Data analysts
- Part lecture, part discussion, exercises and heavy hands-on practice
- 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
- Data analysts
- Part lecture, part discussion, exercises and heavy hands-on practice
- By the end of this training, participants will be able to:
- Explore data with Excel to perform data mining and analysis.
- Use Microsoft algorithms for data mining.
- Understand concepts in Excel data mining.
- Install and configure Dremio
- Execute queries against multiple data sources, regardless of location, size, or structure
- Integrate Dremio with BI and data sources such as Tableau and Elasticsearch
- Data scientists
- Business analysts
- Data engineers
- Part lecture, part discussion, exercises and heavy hands-on practice
- To request a customized training for this course, please contact us to arrange.
- 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
- Data analysts
- Data scientists
- SQL programmers
- Part lecture, part discussion, exercises and heavy hands-on practice
- Install and configure Apache Arrow in a distributed clustered environment
- Use Apache Arrow to access data from disparate data sources
- Use Apache Arrow to bypass the need for constructing and maintaining complex ETL pipelines
- Analyze data across disparate data sources without having to consolidate it into a centralized repository
- Data scientists
- Data engineers
- Part lecture, part discussion, exercises and heavy hands-on practice
- To request a customized training for this course, please contact us to arrange.
- Mobile devices and applications
- Cloud services
- Social business technologies and networking
- Big Data and analytics
- 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
- Law Enforcement specialists with a technical background
- Part lecture, part discussion, exercises and heavy hands-on practice
- 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.
- Ingest big data with Sqoop and Flume.
- Ingest data from multiple data sources.
- Move data from relational databases to HDFS and Hive.
- Export data from HDFS to a relational database.
- Install and configure Talend Open Studio for Big Data.
- Connect with Big Data systems such as Cloudera, HortonWorks, MapR, Amazon EMR and Apache.
- Understand and set up Open Studio's big data components and connectors.
- Configure parameters to automatically generate MapReduce code.
- Use Open Studio's drag-and-drop interface to run Hadoop jobs.
- Prototype big data pipelines.
- Automate big data integration projects.
- 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.
- Developers
- Part lecture, part discussion, exercises and heavy hands-on practice
- 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
- Data scientist
- Developer
- System administrator
- Part lecture, part discussion, exercises and heavy hands-on practice
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