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Data Analysis Fundamentals
Course overview
Why Attend
Data analysis is a core skill in today’s digital and business environments, enabling organizations to make informed, evidence-based decisions. This course introduces participants to the essential concepts, methods, and tools of data analysis. It is designed to build a strong foundation for anyone working with data, reporting, or decision support. Participants will learn how to transform raw data into meaningful insights, identify trends, and support business or operational decisions using structured analytical thinking.
Course Methodology
The course combines clear theoretical explanations with practical, hands-on exercises using real datasets. Participants will practice data cleaning, basic statistical analysis, and visualization techniques. Step-by-step guided activities will help learners understand how data is processed and interpreted. Case studies and simple analytical projects will reinforce learning and demonstrate real-world applications.
Course Objectives
By the end of this course, participants will be able to:
- Understand the basic concepts of data analysis and its importance
- Identify different types of data and data structures
- Perform basic data cleaning and preparation
- Apply simple statistical techniques for analysis
- Create basic charts and visual representations
- Interpret data to support decision-making
- Understand the data analysis workflow from start to finish
- Build confidence in working with datasets
Target Audience
- Beginners in Data Analysis and Business Intelligence
- Students and graduates entering data-related fields
- Business and Administrative Staff
- Engineers and Technical Professionals
- Managers who need basic data interpretation skills
- Anyone starting a career in analytics
Target Competencies
- Basic data handling and interpretation
- Descriptive statistics fundamentals
- Data cleaning and structuring
- Introductory data visualization
- Analytical thinking and problem-solving
- Reporting and insight generation
- Data literacy and decision support
Course outline
Day 1: Introduction to Data Analysis
- What is data analysis and why it matters
- Types of data: qualitative vs quantitative
- Data analysis workflow overview
- Sources of data in organizations
- Introduction to analytical thinking
Day 2: Data Collection and Preparation
- Data collection methods and tools
- Understanding data quality issues
- Data cleaning basics
- Handling missing and incorrect data
- Structuring datasets for analysis
Day 3: Basic Statistical Concepts
- Measures of central tendency (mean, median, mode)
- Measures of dispersion (range, variance, standard deviation)
- Introduction to probability concepts
- Understanding data distributions
- Simple interpretation of statistical results
Day 4: Introduction to Data Visualization
- Importance of data visualization
- Basic chart types (bar, line, pie, etc.)
- Selecting the right visualization
- Common visualization mistakes
- Creating simple visual reports
Day 5: Practical Data Analysis Project
- Step-by-step mini data analysis project
- From raw data to insights
- Basic reporting and interpretation
- Presenting findings clearly
- Review and best practices
Dates and fees
| Dates | City | Fee |
|---|---|---|
| 16 - 20 Nov 2026 | London, United Kingdom | £3,850 + VAT |
| 7 - 11 Dec 2026 | Barcelona, Spain | £3,450 + VAT |
| 18 - 22 Jan 2027 | Munich, Germany | £4,250 + VAT |
| 15 - 19 Feb 2027 | London, United Kingdom | £4,200 + VAT |
| 15 - 19 Mar 2027 | Barcelona, Spain | £3,850 + VAT |
| 19 - 23 Apr 2027 | Amsterdam, Netherlands | £4,250 + VAT |
| 17 - 21 May 2027 | Geneva, Switzerland | £5,250 + VAT |
| 21 - 25 Jun 2027 | Munich, Germany | £4,250 + VAT |
| 19 - 23 Jul 2027 | London, United Kingdom | £4,200 + VAT |
| 16 - 20 Aug 2027 | Barcelona, Spain | £3,850 + VAT |
| 20 - 24 Sep 2027 | Munich, Germany | £4,250 + VAT |
| 18 - 22 Oct 2027 | London, United Kingdom | £4,200 + VAT |
| 15 - 19 Nov 2027 | Barcelona, Spain | £3,850 + VAT |
| 20 - 24 Dec 2027 | Amsterdam, Netherlands | £4,250 + VAT |