
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 trainings in Kazakhstan can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Testimonials
1. Clear theoretical explanation of concepts and alternatives to problem solving. 2. Practical examples where concepts are, and can be applied. 3. I learnt skills that I can use in my job, which will make some of my work easier 4. It will definitely bring some innovation into some of the reports I prepare for different Committees.
Sindiso Ndlovu - Export Credit insurance corporation
Course: Excel For Statistical Data Analysis
The reminder of the world of statistics :)
Export Credit insurance corporation
Course: Excel For Statistical Data Analysis
Steve was willing to answer every questions and worked diligently to address any individual concerns or technical issues as they arose in the class. He also did a great job of presenting the technical details in a way that made it less intimidating to even the least tech savvy people in the room. Personally, learning about some useful shortcuts in Excel that I didn't know about will certainly improve my overall workflow when using Excel in the future! I am so appreciative of those little details that I was exposed to during the two-day training.
Alan Gonzalez - Queens College, CUNY
Course: Excel For Statistical Data Analysis
The fact he had dif excel and data sheets with exercises for us to do.
Deepakie Singh Sodhi - Queens College, CUNY
Course: Excel For Statistical Data Analysis
The effort made by the trainer to engage the audience, as well as time taken to prepare exercises.
Hollie Coe, Wild Bioscience
Course: Data Analytics With R
The exercises to test what I had learnt. It felt like problem solving and I felt a sense of pride when I could solve it.
Hollie Coe, Wild Bioscience
Course: Data Analytics With R
Lots of relevant examples and R markdown files, which I hope will be useful to refer to later.
Hollie Coe, Wild Bioscience
Course: Data Analytics With R
The tool was interesting and I see the use. I would like to learn about more about it.
Teleperformance
Course: Data Analytics With R
new tool which is "R" and I find it interesting to know the existence of such tool for data analysis
Michael Lopez - Teleperformance
Course: Data Analytics With R
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
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
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
The handson. The mix practice/theroy
Proximus Group
Course: Data Analysis with Hive/HiveQL
The high level principles about Hive, HDFS..
Geert Suys - Proximus Group
Course: Data Analysis with Hive/HiveQL
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 competence and knowledge of the trainer
Jonathan Puvilland
Course: Data Analysis with Hive/HiveQL
Dynamic interaction and "hands on" the subject, thanks to the Virtual Machine, very stimulating!
Philippe Job
Course: Data Analysis with Hive/HiveQL
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 explanation provided is clear.
Course: Data Analysis in Python using Pandas and Numpy
The notebooks and examples were on point.
Course: Data Analysis in Python using Pandas and Numpy
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
customized, in-house file processing and data analysis
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
I liked the way that my trainer was teaching us, and the Meeting Room was taken for our course.
Mohammed Othman Karim, Sulaymaniyah Asayish Agency
Course: A Practical Introduction to Data Analysis and Big Data
Interactive topics and the style used by the lecture to simplified the topics for the students
Miran Saeed - Mohammed Othman Karim, Sulaymaniyah Asayish Agency
Course: A Practical Introduction to Data Analysis and Big Data
Smart and cleverness
Mohammed Othman Karim, Sulaymaniyah Asayish Agency
Course: A Practical Introduction to Data Analysis and Big Data
the trainer and his ability to lecture
ibrahim hamakarim - Mohammed Othman Karim, Sulaymaniyah Asayish Agency
Course: A Practical Introduction to Data Analysis and Big Data
Practical exercises
JOEL CHIGADA - University of the Western Cape
Course: A Practical Introduction to Data Analysis and Big Data
R programming
Osden Jokonya - University of the Western Cape
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
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
He is very knowledgeable and could answer all the questions
Chalmers Tekniska Högskola AB
Course: Elasticsearch for Developers
The trainer's openness to questions and willingness to help/answer/explain.
Chalmers Tekniska Högskola AB
Course: Elasticsearch for Developers
I liked that we got a general overview of elastic and learned tons of things that could be applied in current project the first day. I also liked that we went through current project code with a code review and mention improvements or/and stuff to think about or take up for discussion in the project on the second day. I like that the training gave me a good base to continue delve into elastic search.
Mattias Hansson - Chalmers Tekniska Högskola AB
Course: Elasticsearch for Developers
Trainer was very open minded about questions and tried to answer as many as possible.
Quidco
Course: Elasticsearch for Developers
The content relevnt and to the point
Qiniso Mdletshe - Quidco
Course: Elasticsearch for Developers
Relaxed style. Help with the issues we were having with current setup.
Quidco
Course: Elasticsearch for Developers
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
His deep knowledge about the subject
Course: MATLAB Fundamentals, Data Science & Report Generation
real life practical examples
Wioleta (Vicky) Celinska-Drozd
Course: Data and Analytics - from the ground up
The patience of Kamil.
Laszlo Maros
Course: Data and Analytics - from the ground up
First session. Very intensive and quick.
Digital Jersey
Course: Data and Analytics - from the ground up
Kamil is very knowledgeable and nice person, I have learned from him a lot.
Aleksandra Szubert
Course: Data and Analytics - from the ground up
Detailed and comprehensive instruction given by experienced and clearly knowledgeable expert on the subject.
Justin Roche
Course: Data and Analytics - from the ground up
The explanation provided is clear.
Course: Data Analysis in Python using Pandas and Numpy
The notebooks and examples were on point.
Course: Data Analysis in Python using Pandas and Numpy
His deep knowledge about the subject
Course: MATLAB Fundamentals, Data Science & Report Generation
Data Analysis Course Outlines in Kazakhstan
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Set up and configure Databricks.
- Understand how Databricks and Apache Spark work together.
- Learn how to load and transform data in Databricks.
- 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.
- Developers
- Technical analysts
- IT consultants
- Part lecture, part discussion, exercises and heavy hands-on practice
- To request a customized training for this course, please contact us to arrange.
- 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.
- processing and analyzing data
- producing informative data visualizations
- forecasting future performance
- evaluating forecasts
- turning data into evidence-based business decisions
- optimizing processes
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