
Online or onsite, instructor-led live Data Analysis (Analysis of Data or Data Analytics) training courses demonstrate through discussion and hands-on practice the programmeming languages and methodologies used to perform Data Analysis.
Data Analysis 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. The UK onsite live Data Analysis trainings can be carried out locally on customer premises or in NobleProg corporate training centres.
NobleProg -- Your Local Training Provider
Testimonials
The way the trainer made complex subjects easy to understand.
Adam Drewry
Course: Data and Analytics - from the ground up
learning how to use excel properly
Torin Mitchell
Course: Data and Analytics - from the ground up
I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Kamil was held up helping other people, I could crack on with the next parts.
Luke Pontin
Course: Data and Analytics - from the ground up
Fast paced - good interaction - clearly very knowledgable trainer.
Course: Business Process Analysis with UML and BPMN
I enjoyed all of Day 1.
Peter Mahaffey
Course: Contemporary Development Principles and Practices
Very informative and gave a nice overall summary of the course outline
Matthew Steptoe
Course: Contemporary Development Principles and Practices
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
loved the hands on exercises and that the trainer walked us through how to do them and helped anyone that was having an issue. He made excellent use of the training room functionality and actually watched everyones progress.
Jill Schmaedeke - Elaine Rodger, Tech NorthWest Skillnet
Course: Tableau Fundamentals
The time spent on data modeling. As most of the persons are not IT, it is good for everyone to know the implication of the relationships and the useful star concept
Filipe Fernandes - Isidro de Paz, European Space Agency
Course: Advanced Power BI
Good examples / demonstrations
Ofqual
Course: D3.js for Data Visualization
The trainer was very concern about individual understanding.
Muhammad Surajo Sanusi - Birmingham City University
Course: Foundation R
The trainer was very good. He presented the material in a really accessible way.
Hydrock
Course: Introduction to Data Visualization with Tidyverse and R
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course: Introduction to Data Visualization with Tidyverse and R
I was benefit from the detailed notes to keep and work through after the course.
Public Health Wales NHS Trust
Course: Introduction to Data Visualization with Tidyverse and R
It gave me a better understanding of Zabbix monitoring
Leicestershire County Council
Course: Automated Monitoring with Zabbix
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
Exercises on time series modeling
Teleperformance
Course: Data Analytics With R
I get answers on all my questions.
Natalia Gladii
Course: Data Analytics With R
Trainer develops training based on participant's pace
Farris Chua
Course: Data Analysis in Python using Pandas and Numpy
That we have used our own data as examples
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
customised, in-house file processing and data analysis
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
Doing the exercises. I really enjoyed the practicals.
Warren Stephen - Quidco
Course: Elasticsearch for Developers
Marcin knew exactly what he talking about and had proper hands on in-depth experience with the tools. He had answers to all our questions and made some really strong recommendations that we could start working towards with future projects and uses.
Conor Glasman - Quidco
Course: Elasticsearch for Developers
I thought the training was very thorough and while we covered a lot of material, Martin made ample time for questions and gave good focus to each individual and their different requirements.
Jeán Thysse - Quidco
Course: Elasticsearch for Developers
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
His deep knowledge about the subject
Course: MATLAB Fundamentals, Data Science & Report Generation
the trainer was very good and made the training perfect for my needs
Florentin - Brenda TSATSU, EXPERIS
Course: Search and Analytics with Amazon OpenSearch
Fast paced - good interaction - clearly very knowledgable trainer.
Course: Business Process Analysis with UML and BPMN
His deep knowledge about the subject
Course: MATLAB Fundamentals, Data Science & Report Generation
Data Analysis Course Outlines
- Create and manage projects on dbt Cloud.
- Use the dbt Cloud interface to schedule and run data transformations.
- Collaborate on projects with team members.
- Deploy their dbt projects to production.
- Debug and troubleshoot dbt projects.
- Learn how Python can be integrated into Power BI for data analysis.
- Use Python scripts to load, clean, and preprocess data within the Power BI environment.
- Enhance data visualization capabilities by creating custom and interactive visualizations using Python.
- Acquire advanced data analysis skills using Python.
- Understand the fundamentals of AWS Glue.
- Set up an AWS Glue pipeline.
- Set up AWS Glue crawlers and jobs.
- Learn how to use AWS Glue transformations.
- Perform data analysis using Python, R, and SQL.
- Create insights through data visualization with Tableau.
- Make data-driven decisions for business operations.
- Learn how to analyze data using IBM Planning Analytics.
- Create custom views of the data in a database.
- Build reports and forms that communicate with TM1.
- Gain a thorough knowledge of Nagios, including installation, configuration, and administration.
- Use Nagios to monitor networks, servers, and applications.
- Implement advanced monitoring techniques for diverse IT environments, including cloud and virtualized infrastructures.
- Configure alerts, manage notifications and generate reports to ensure proactive network management.
- Take the Nagios Certified Administrator exam with confidence.
- Install and configure MongoDB for data analysis.
- Understand the concepts and stages of the MongoDB Aggregation Framework.
- Learn about the basic structure, syntax, and operations for aggregation.
- Learn how to handle advanced operations in aggregation.
- Apply some optimization tools and techniques to improve aggregation performance.
- Learn the fundamental concepts of Sisense and how it works.
- Create a Sisense dashboard to visualize big data and execute data-driven business decisions.
- Merge and manage data from multiple sources.
- Utilize Sisense for quick data manipulation and visualization.
- Have an in-depth understanding of the Tableau Server architecture.
- Understand Tableau Server processes and functions.
- User Tableau Server to automate tasks.
- Configure and manage the Tableau Server.
- Set up Tableau Server for high availability and scalability.
- Create and customize Grafana dashboards with different visualizations.
- Implement alerting and notifications for monitoring.
- Administer user accounts, teams, and permissions.
- Manage IT assets effectively, including hardware and software inventory.
- Implement a helpdesk system for user support and ticket management.
- Gain a solid foundation in both Nagios XI and Nagios Core, including their architecture and key components.
- Monitor hosts, services, and network components effectively using Nagios.
- Using Nagios for data visualization, dashboards, and reporting.
- Take the Nagios Certified Professional exam with confidence.
- Handle large data sets with sophisticated formatting tools.
- Create data visualization reports and directories.
- Use OrgPlus printing, exporting, and publishing features.
- Navigate complex charts with ease.
- Understand the basic concepts of AWS QuickSight.
- Use AWS QuickSight to create data analysis, reports, and insights.
- Use AWS to create relationships between data for enhanced analysis.
- Learn different types of visualizations in understanding data.
- Set up the necessary environment to perform data analysis with SQL, Python, and Tableau.
- Understand the key concepts of software integration (data, servers, clients, APIs, endpoints, etc.).
- Get a refresher on the fundamentals of Python and SQL.
- Perform data pre-processing techniques in Python.
- Learn how to connect Python and SQL for data analysis.
- Create insightful data visualizations and charts with Tableau.
- Have a comprehensive understanding of Data Analysis Expressions (DAX) in Power BI.
- Create custom calculations and expressions in Power BI for analyzing data and deriving insights.
- Learn best practices to optimize DAX performance.
- Fully understand the concepts and architecture of data warehousing.
- Understand how to use analytics, desktop objects, and schemas.
- Build and maintain MicroStrategy projects.
- Learn to use and configure all the tools in the developer tab.
- Design efficient workflows in Alteryx using the dynamic, validation, and testing tools.
- Learn how to use API tools to download and parse web data.
- Use Alteryx scripting tools, including Python and R.
- Understand the differences and enhancements in Cognos 11 compared to Cognos 10.
- Utilize the improved data module and data management features for more efficient data handling.
- Implement best practices for a smooth transition and optimal use of Cognos 11.
- Gain an in-depth understanding of advanced Grafana concepts and components.
- Leverage template variables and dynamic dashboards for enhanced data visualization.
- Use Grafana Query Language for complex queries.
- Learn best practices for scaling Grafana, optimizing performance, and ensuring high availability.
- Learn how to use Mixpanel as a web analytics tool.
- Understand the Mixpanel concepts and implementation.
- Understand and interpret event data.
- Understand how Matomo works in analyzing web data.
- Learn how data is collected and tracked with Matomo.
- Understand and interpret Matomo reports.
- Understand the fundamentals of ArcMap and ArcGIS.
- Collect, organize, manage, and analyze geographic information on the social and archaeological elements.
- Conduct spatial queries for impact evaluation.
- Learn and understand how the Datadog monitoring tool works.
- Understand the Datadog core concepts and features.
- Configure Datadog for infrastructure monitoring and account management.
- Use Datadog Application Performance Monitoring (APM) and continuous profiling.
- Understand Nagios architecture, components, and advanced monitoring strategies.
- Implement advanced service monitoring and extend Nagios functionality.
- Explore Nagios add-ons and advanced techniques.
- Understand the fundamentals of data mining.
- Learn how to import and assess data quality with the Modeler.
- Develop, deploy, and evaluate data models efficiently.
- Course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation.
- Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange.
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