
Online or onsite, instructor-led live Data Analysis (Analysis of Data or Data Analytics) training courses demonstrate through discussion and hands-on practice the programming 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. Onsite live Data Analysis training can be carried out locally on customer premises in Finland or in NobleProg corporate training centers in Finland.
NobleProg -- Your Local Training Provider
Testimonials
I mostly liked the knowledge of the Trainer.
Sripal S
Course: Understanding Business Process Modeling with BPMN 2.0
I generally enjoyed the way of delivering speech.
Bhaskar naidu
Course: Understanding Business Process Modeling with BPMN 2.0
I genuinely enjoyed the trainer's helping.
Urszula Kuza
Course: Tableau Advanced
I get answers on all my questions.
Natalia Gladii
Course: Data Analytics With R
I gained a good overview of the process editors, business rules and BPMS tools landscape. I highly recommend the practical BPMN for Business Analysts course, even for experienced analysts, with its excellent process scenarios and modeling practice it will position you a cut above the rest!.
Anees Baig
Course: BPMN 2.0 for Business Analysts
Very informative and gave a nice overall summary of the course outline.
Matthew Steptoe
Course: Contemporary Development Principles and Practices
I enjoyed all of Day 1.
Peter Mahaffey
Course: Contemporary Development Principles and Practices
I liked the exercises as it's the only way to learn, by repetition.
David Rushe
Course: Tableau Advanced
I enjoyed the exercises, The training room, Tea kitchen.
Alisher Khaydarov
Course: BPMN 2 Fundamentals and Workshop
The pace and progression was perfect to really understand things quickly.
Stephen Brewell
Course: BPMN 2.0 for Business Analysts
The examples given really helped me to understand some concepts. The trainer made sure that we were following the whole training and didn't hesitate to come back to a previous point of there was any doubt. The trainer adapted the training to our needs, giving focus to the items we would like to have more details. Practical exercises were good too.
Amanda Moscardini - Campinas Valley
Course: Understanding Business Process Modeling with BPMN 2.0
Debra made sure to understand my questions and answered them precisely. The suggestions on how to design diagrams under certain conditions were really good. I would like to reinforce how professional and efficient Debra was with us.
Leandro Antonio
Course: Understanding Business Process Modeling with BPMN 2.0
I like the exercises done.
Nour Assaf
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
The information given was interesting and the best part was towards the end when we were provided with Data from Durex and worked on Data we are familiar with and perform operations to get results.
Jessica Chaar
Course: Data Mining and Analysis
I thought that the information was interesting.
Allison May
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
Learning about all the chart types and what they are used for. Learning the value of cluttering. Learning about the methods to show time data.
Susan Williams
Course: Data Visualization
Trainer was enthusiastic.
Diane Lucas
Course: Data Visualization
I really liked the content / Instructor.
Craig Roberson
Course: Data Visualization
I am a hands-on learner and this was something that he did a lot of.
Lisa Comfort
Course: Data Visualization
I liked the examples.
Peter Coleman
Course: Data Visualization
I liked the examples.
Peter Coleman
Course: Data Visualization
I enjoyed the good real world examples, reviews of existing reports.
Ronald Parrish
Course: Data Visualization
I like the way Birol customized some parts of the training catering to my role as Business Analyst. This way, he was able to focus on the topics that are important and not dwell on topics that I generally will not use in my work. He teaches very clear and ensures that you understand a topic before going to the next. You can say that he is a seasoned professor and very knowledgeable on his subject, and knows how to analyze training needs of the student to effectively cover topics which are essential and relevant. This makes his sessions very effective as it is flexible and right on target. His materials are very comprehensive and he makes a point to follow the curriculum but making it more relevant to the student. I appreciate that he knows industry standards and is able to give his insights as to what works. I've never learned as much as I did on a 2-day course and it is worth all the time and effort. The training did expedite my learning of BPMN 2.0 and gave me the basics and confidence to start practicing the technique in my work. Thank you Birol and NobleProg for a wonderful learning experience I will surely recommend the course and trainer to future colleagues.
Irma Irosido
Course: BPMN 2.0 for Business Analysts
I really was benefit from the willingness of the trainer to share more.
Balaram Chandra Paul
Course: A practical introduction to Data Analysis and Big Data
I really was benefit from the interactivity and dedicated trainer.
Pierre Bruwier
Course: BPMN 2 Fundamentals and Workshop
Offering a more in-depth scope about Power BI more than any training institute that I came across to.
Mohammed Al Ameer
Course: Power BI
Fast paced - good interaction - clearly very knowledgeable trainer.
Course: Business Process Analysis with UML and BPMN
Liked very much the interactive way of learning.
Luigi Loiacono
Course: Data Analysis with Hive/HiveQL
I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Tamil was held up helping other people, I could crack on with the next parts.
Luke Pontin
Course: Data and Analytics - from the ground up
Learning how to use excel properly.
Torin Mitchell
Course: Data and Analytics - from the ground up
The way the trainer made complex subjects easy to understand.
Adam Drewry
Course: Data and Analytics - from the ground up
It was a very practical training, I liked the hands-on exercises.
Proximus
Course: Data Analysis with Hive/HiveQL
Detailed and comprehensive instruction given by experienced and clearly knowledgeable expert on the subject.
Justin Roche
Course: Data and Analytics - from the ground up
Tamil is very knowledgeable and nice person, I have learned from him a lot.
Aleksandra Szubert
Course: Data and Analytics - from the ground up
I liked the first session. Very intensive and quick.
Digital Jersey
Course: Data and Analytics - from the ground up
I was benefit from the good overview, good balance between theory and exercises.
Proximus
Course: Data Analysis with Hive/HiveQL
I mostly liked the patience of Tamil.
Laszlo Maros
Course: Data and Analytics - from the ground up
I enjoyed the dynamic interaction and “hands-on” the subject, thanks to the Virtual Machine, very stimulating!.
Philippe Job
Course: Data Analysis with Hive/HiveQL
I really was benefit from the real life practical examples.
Wioleta (Vicky) Celinska-Drozd
Course: Data and Analytics - from the ground up
I was benefit from the competence and knowledge of the trainer.
Jonathan Puvilland
Course: Data Analysis with Hive/HiveQL
Exercises, additional tips from the trainer, flexibility to add more insights when requested.
Anna Alechno
Course: Power BI
I generally was benefit from the presentation of technologies.
Continental AG / Abteilung: CF IT Finance
Course: A practical introduction to Data Analysis and Big Data
Overall the Content was good.
Sameer Rohadia
Course: A practical introduction to Data Analysis and Big Data
I mostly enjoyed the power BI possibility.
British American Shared Services Europe
Course: Power BI
I genuinely enjoyed the visualization part.
Alexandra Grigoriu
Course: Power BI
Good coverage of all Power BI themes relevant and useful for creating reliable dashboards and reports as a beginner.
Gabriel Purghel
Course: Power BI
I liked the focus and the emphasis on self-learning, playing and reading on external resources. No Application can be taught in 2 days and self-study is very important.
Vlad Andrei Bucur
Course: Power BI
I generally was benefit from the power bi web- Q.
Cristina Palii
Course: Power BI
Fast paced - good interaction - clearly very knowledgeable trainer.
Course: Business Process Analysis with UML and BPMN
Data Analysis Course Outlines in Finland
By the end of this training, participants will be able to:
- Perform data analysis using Python, R, and SQL.
- Create insights through data visualization with Tableau.
- Make data-driven decisions for business operations.
By the end of this training, participants will be able to:
- 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.
By the end of this training, participants will be able to:
- 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.
By the end of this training, participants will be able to:
- 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.
By the end of this training, participants will be able to:
- 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.
By the end of this training, participants will be able to:
- 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.
By the end of this training, participants will be able to:
- Learn how to use Mixpanel as a web analytics tool.
- Understand the Mixpanel concepts and implementation.
- Understand and interpret event data.
By the end of this training, participants will be able to:
- Understand how Matomo works in analyzing web data.
- Learn how data is collected and tracked with Matomo.
- Understand and interpret Matomo reports.
By the end of this training, participants will be able to:
- Set up and configure Databricks.
- Understand how Databricks and Apache Spark work together.
- Learn how to load and transform data in Databricks.
By the end of this training, participants will be able to:
- Understand the fundamentals of data mining.
- Learn how to import and assess data quality with the Modeler.
- Develop, deploy, and evaluate data models efficiently.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability.
Audience
Developers / data analytics
Duration
3 days
Format
Lectures and Hands-on
The training starts with a discussion of the Elasticsearch architecture, including its distributed model and search API. This is followed by an explanation of Elasticsearch's functionality and how to best integrate it into an existing application.
Hands-on exercises make up an important part of the training, and give participants a chance to put into practice their knowledge while receiving feedback on their implementation and progress.
In the second part, we demonstrate how to use MATLAB for data mining, machine learning and predictive analytics. To provide participants with a clear and practical perspective of MATLAB's approach and power, we draw comparisons between using MATLAB and using other tools such as spreadsheets, C, C++, and Visual Basic.
In the third part of the training, participants learn how to streamline their work by automating their data processing and report generation.
Throughout the course, participants will put into practice the ideas learned through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough grasp of MATLAB's capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation.
Assessments will be conducted throughout the course to gauge progress.
Format of the Course
- Course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation.
Note
- Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange.
Analysts, researchers, scientists, graduates and students and anyone who is interested in learning how to facilitate statistical analysis in Microsoft Excel.
Course Objectives
This course will help improve your familiarity with Excel and statistics and as a result increase the effectiveness and efficiency of your work or research.
This course describes how to use the Analysis ToolPack in Microsoft Excel, statistical functions and how to perform basic statistical procedures. It will explain what Excel limitation are and how to overcome them.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Data Science, then progresses into the tools and methodologies used in Data Science.
Audience
- Developers
- Technical analysts
- IT consultants
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.
By the end of this training, participants will be able to:
- Understand the principles of data analysis, objectives of data analysis, and approaches for data analysis.
- Use DAX formulas in Power BI for complex calculations.
- Create and use visualizations and charts for particular analysis cases.
- Import with Power View to move from Excel based Power BI to independent Power BI.
What has happened?
- processing and analyzing data
- producing informative data visualizations
What will happen?
- forecasting future performance
- evaluating forecasts
What should happen?
- turning data into evidence-based business decisions
- optimizing processes
The course itself can be delivered either as a 6 day classroom course or [remotely](https://www.nobleprog.co.uk/instructor-led-online-training-courses) over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.
By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.
Format of the Course
- Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
databases (Oracle, SQL Server, MS Access...). Understanding of analytic functions and the
way how to join different tables in a database will help delegates to move data analysis
operations to the database side, instead of doing this in MS Excel application. This can also
help in creating any IT system, which uses any relational database.
In this instructor-led, live training, participants will learn how to use R to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
- Understand the fundamentals of the R programming language
- Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate deploy and optimize an R application
Audience
- Developers
- Analysts
- Quants
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
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.
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
The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers.
This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.
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
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
In this instructor-led, live training, participants will learn how to install, configure and use Dremio as a unifying layer for data analysis tools and the underlying data repositories.
By the end of this training, participants will be able to:
- 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
Audience
- Data scientists
- Business analysts
- Data engineers
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.
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