Course schedules

Upcoming dates Classroom

Start date	End date	Location	Fee	Registration
5 Oct 2026	9 Oct 2026	Munich - Germany	€2,100 + VAT	→
16 Nov 2026	20 Nov 2026	London - United Kingdom	€1,925 + VAT	→
7 Dec 2026	11 Dec 2026	Barcelona - Spain	€1,725 + VAT	→
18 Jan 2027	22 Jan 2027	Munich - Germany	€2,125 + VAT	→
15 Feb 2027	19 Feb 2027	London - United Kingdom	€2,100 + VAT	→
15 Mar 2027	19 Mar 2027	Barcelona - Spain	€1,925 + VAT	→
19 Apr 2027	23 Apr 2027	Amsterdam - Netherlands	€2,125 + VAT	→
17 May 2027	21 May 2027	Geneva - Switzerland	€2,625 + VAT	→

Request an in-house date

Online live Remote

5 - 9 October 2026 €1,050 + VAT → 16 - 20 November 2026 €1,050 + VAT → 7 - 11 December 2026 €1,050 + VAT → 18 - 22 January 2027 €1,050 + VAT → 15 - 19 February 2027 €1,050 + VAT → 15 - 19 March 2027 €1,050 + VAT → 19 - 23 April 2027 €1,050 + VAT → 17 - 21 May 2027 €1,050 + VAT →

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 Objectives

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

Designed for

This program is intended for professionals involved in Data Management and Business Intelligence.

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

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 content

Day1

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

Day2

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

Day3

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

Day4

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

Day5

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

The certificate

SPARK Training Certificate of Completion is awarded to participants who attend and complete the full training course.