About this Course
Data has become one of the most important resources for modern organisations, generated every day through operational systems, customer interactions, digital platforms, connected devices and public sources. When managed and analysed properly, it supports better decisions, operational efficiency, innovation and competitive advantage.
Big Data refers not only to the volume of information, but also to its complexity, speed, variety and value. Adoption requires careful planning around data quality, infrastructure, cost, security, compliance and ethical use, so that initiatives stay governed and sustainable rather than fragmented.
What You Will Learn
- Understand the concept of Big Data and its relevance for SMEs
- Recognise the opportunities and limitations of large-scale data collection and analysis
- Identify key Big Data technologies, including NoSQL, NewSQL, Hadoop and MongoDB
- Understand how different data sources support insight and decision-making
- Evaluate security, privacy, compliance and ethical considerations
- Assess how Big Data supports operational improvement, innovation and strategic planning
Course Structure 7 modules
Introduction to Big Data and SME Relevance
- The concept of Big Data and its organisational relevance
- Opportunities: efficiency, customer experience, innovation
- Challenges and limits: collection, storage, processing, security
- Available resources, platforms and technologies
Big Data Technologies and Platforms
- NoSQL databases: document, column, key-value, graph
- NewSQL databases: scalability and transactional consistency
- Hadoop and MongoDB for distributed processing
- Selecting platforms by cost and organisational maturity
Data Sources, Data Preparation and Data Management
- Internal sources: enterprise systems, Oracle, SAP, data warehouses
- External sources: social media, APIs, public data
- Data preparation: cleaning, transformation, validation
- Metadata, governance and lifecycle management
Data Analysis, Visualisation and Machine Learning for Big Data
- Analysis methods: statistical, clustering, correlation, trends
- Visualisation tools: Tableau, Power BI, Matplotlib
- Interactive dashboards for business stakeholders
- Machine learning principles: prediction and classification
Big Data Security, Privacy and Ethics
- Protecting data throughout the full lifecycle
- Encryption, anonymisation and access control
- Ethical principles: privacy, transparency, consent
- Regulatory requirements, including GDPR
Big Data Implementation and Business Value
- Planning initiatives aligned with business objectives
- Defining the problem, requirements and success criteria
- Connecting analysis to measurable outcomes
- Implementation challenges and sustainability strategies
Course Closing and Consolidation
- Structured review across all modules
- Preparation for the final assessment
- Reflecting on responsible application in your own context
- Personalised trainer feedback (on request)
Who It Is For
Professionals seeking to understand, evaluate and apply Big Data concepts, platforms and analytics methods in organisational and business contexts.