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Introduction to big data and data careers
Your data projects need a clear view of information flows and responsibilities. Understand big data architectures, processing stages and the roles that make them work. Build the knowledge needed to understand technical constraints and contribute to better-coordinated projects.
- Duration
- 1 day 7 hours
- Code
- DATA007FR Code
Presentation
Data has become the new oil for businesses, yet its terminology and professional roles often remain unclear to newcomers. This one-day course provides a comprehensive, accessible overview of big data. It is designed for anyone who wants to understand how data transforms organisations and the skills needed to contribute.
The program explains fundamental concepts such as the 5Vs (Volume, Velocity, Variety and more), and clarifies the distinction between structured and unstructured data. Explore the technology ecosystem, including cloud, Hadoop and Spark, to understand how information is stored and processed. Particular attention is given to data careers, helping you distinguish the specific roles of a Data Analyst, Data Scientist and Data Engineer.
Far from being purely theoretical, the day includes practical workshops using widely available tools such as Excel, Power BI and Tableau Public. Experience the data lifecycle, from exploration to visualisation, to consolidate your new knowledge.
Objectives
By the end of this course, you will be able to:
- define key big data concepts and analyse their strategic impact on businesses;
- identify major ecosystem technologies, including NoSQL, Spark and cloud;
- distinguish the roles and responsibilities of Data Analysts, Data Scientists and Data Engineers;
- describe the stages of a data project lifecycle, from collection to visualisation;
- use simple tools to explore and represent data.
Program
Module 1: understanding big data challenges
- Defining big data and distinguishing structured from unstructured data.
- The 5Vs that characterise big data: Volume, Velocity, Variety, Veracity and Value.
- The technology ecosystem: an overview of tools such as Hadoop, Spark and NoSQL, and an introduction to cloud.
Hands-on exercises
- Explore structured datasets using accessible tools such as Excel or Google Sheets.
Module 2: exploring roles and skills
- The Data Analyst profile: responsibilities, skills and reporting tools.
- The Data Scientist role: predictive modelling and algorithms.
- The Data Engineer function: architecture and data pipelines.
- Cross-functional roles: Chief Data Officer, Data Steward and governance.
Hands-on exercises
- Check your understanding of roles through an interactive quiz on data careers and tools.
Module 3: understanding the data project lifecycle
- Key stages: collection, cleaning, analysis and value creation.
- Governance, data security and ethical issues.
- Exploring practical use cases in healthcare, finance or marketing.
Hands-on exercises
- Create a simple data visualisation with Power BI or Tableau Public to bring the figures to life.
Audience
This course is intended for participants seeking to develop data literacy, including:
- professionals changing careers who want to move into digital roles;
- recruitment and HR professionals who need to assess data profiles;
- managers and IT project managers working with technical teams;
- students or recent graduates in management or IT.
Prerequisites
The following background is useful for this course:
- General IT knowledge or familiarity with data management is an advantage.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Quiz / multiple-choice questions
- Practical exercises
Course highlights
- 360° perspective: gain a clear map of the data ecosystem, from technologies to professional roles.
- Accessibility: explore complex concepts without technical barriers, using language suited to non-specialists.
- Clarity for HR: learn to distinguish job descriptions precisely (analyst versus scientist versus engineer) to support recruitment or career choices.
- Engaging practice: use modern visualisation tools to put theory into practice.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
Any brand names and logos mentioned in this course description (such as Excel, Power BI, Tableau and Hadoop) belong to their respective owners. Their mention for educational purposes does not imply any commitment or partnership.