Global Learning for Operational Leaders
Classroom
15 sessions
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Online / Live
15 sessions
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Introduction
Course overview
Why Attend
Data-driven decision-making is now essential across all industries, from engineering and construction to business and technology. This course equips participants with advanced data analysis techniques to transform raw data into meaningful insights that support strategic and operational decisions. Participants will learn how to handle complex datasets, apply statistical and analytical methods, and use modern tools to identify trends, patterns, and performance indicators. By attending, you will significantly improve your ability to support evidence-based decisions, optimize processes, and enhance organizational performance.
Course Methodology
This course combines conceptual explanations with hands-on practice using real-world datasets. Participants will engage in guided exercises, case studies, and problem-solving sessions. Practical demonstrations using analytical tools (such as Excel advanced functions, Power BI, or Python-based analysis concepts) will be included depending on the training level. Group discussions and scenario-based learning will help reinforce applied analytical thinking.
Course Objectives
By the end of this course, participants will be able to:
- Understand advanced concepts in data analysis and interpretation
- Clean, structure, and prepare complex datasets for analysis
- Apply statistical methods for decision-making
- Identify trends, correlations, and patterns in data
- Use data visualization techniques to communicate insights effectively
- Apply predictive and descriptive analytics techniques
- Improve reporting and business intelligence capabilities
- Support data-driven strategic decisions
Target Audience
- Data Analysts and Business Analysts
- Engineers and Technical Professionals
- Project and Operations Managers
- Financial Analysts and Consultants
- IT Professionals working with data systems
- Decision-makers seeking analytical skills
Target Competencies
- Data interpretation and critical thinking
- Statistical analysis and modeling
- Data cleaning and preparation
- Data visualization and reporting
- Analytical problem-solving
- Business intelligence understanding
- Decision support using data insights
What you will achieve
Learning objectives
- Understand advanced concepts in data analysis and interpretation
- Clean, structure, and prepare complex datasets for analysis
- Apply statistical methods for decision-making
- Identify trends, correlations, and patterns in data
- Use data visualization techniques to communicate insights effectively
- Apply predictive and descriptive analytics techniques
- Improve reporting and business intelligence capabilities
- Support data-driven strategic decisions
Who should attend
Target audience
- Data Analysts and Business Analysts
- Engineers and Technical Professionals
- Project and Operations Managers
- Financial Analysts and Consultants
- IT Professionals working with data systems
- Decision-makers seeking analytical skills
- Target Competencies
- Data interpretation and critical thinking
Methodology
Learning approach
- This course combines conceptual explanations with hands-on practice using real-world datasets. Participants will engage in guided exercises, case studies, and problem-solving sessions. Practical demonstrations using analytical tools (such as Excel advanced functions, Power BI, or Python-based analysis concepts) will be included depending on the training level. Group discussions and scenario-based learning will help reinforce applied analytical thinking.
Course content
Five focused days of learning and application
Day 1
Foundations of Advanced Data Analysis
- Role of data analysis in decision-making
- Types of data and data structures
- Data lifecycle: collection, processing, analysis
- Introduction to descriptive and inferential analytics
- Overview of analytical tools and environments
Day 2
Data Preparation and Transformation
- Data cleaning techniques and error handling
- Handling missing data and outliers
- Data normalization and transformation methods
- Data integration from multiple sources
- Building structured datasets for analysis
Day 3
Statistical Analysis and Interpretation
- Descriptive statistics and summary measures
- Probability concepts in data analysis
- Correlation and regression analysis
- Hypothesis testing fundamentals
- Interpretation of statistical outputs
Day 4
Data Visualization and Insights
- Principles of effective data visualization
- Charts, dashboards, and reporting techniques
- Storytelling with data
- KPI tracking and performance dashboards
- Introduction to BI tools (e.g., Power BI concepts)
Day 5
Predictive Analytics and Practical Applications
- Introduction to predictive modeling concepts
- Trend analysis and forecasting techniques
- Decision-making using analytical models
- Case studies from real-world industries
- Final project: end-to-end data analysis exercise
FAQ
Frequently asked questions
What does Advanced Data Analysis Techniques (DMBI-001) cover?
This course covers Data Management and Business Intelligence through a structured five-day outline focused on practical application, discussion, and implementation planning.
When is the next available session?
The next scheduled session starts on 19 - 23 October 2026, with additional classroom dates and mirrored Online / Live options listed in the course schedules section.
Who should attend this course?
Data Analysts and Business Analysts, Engineers and Technical Professionals, Project and Operations Managers
Is bilingual course delivery available?
Yes. All course materials and presentations are provided in English, while bilingual explanation and discussion support may be available depending on the selected location and trainer availability. For example, when attending a course in Istanbul, you may request a Turkish-speaking trainer to explain the English course content in Turkish. Arabic explanation support may also be requested at this location. Other languages are available in selected cities. You can choose your preferred language support as an optional preference during registration.
How can I register for a session?
Use any Register button next to the available course dates to open the participant registration page and submit your booking request for the selected session.
Is this course available online as well as classroom-based?
Yes. The course detail page includes both classroom sessions and Online / Live sessions, with online options aligned to the same course dates for easier planning.
Where are classroom sessions delivered?
Current classroom venues include Munich, London, Barcelona, Amsterdam, Rome.
How long is the training programme?
The programme runs for five days, with up to five training hours per day, from 9:00 AM to 2:00 PM. Each programme includes a total of 25 accredited training hours.
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