Project Management - Big Data and Business Intelligence ENEB Business School

Overview

ENEB Business School stands out as a leading institution in distance education across Europe, offering a unique dual master's programme that combines Project Management with Big Data and Business Intelligence. This programme is designed for professionals seeking to enhance their expertise in both fields, ensuring they remain competitive in a rapidly evolving job market. With a strong emphasis on practical skills and real-world applications, students benefit from a curriculum that integrates cutting-edge technologies and methodologies. ENEB is renowned for its commitment to quality education, providing students with robust support from experienced tutors and access to a rich network of industry connections.

The tuition fee for the Master in Project Management - Big Data and Business Intelligence is €8,400 for both international and European students. Visit the Fees and Funding section for a breakdown in your local currency.

The curriculum for the Master in Project Management - Big Data and Business Intelligence encompasses a wide range of topics, ensuring a holistic understanding of both project management and data analysis. The syllabus includes:

• Business Plan: Vision, mission and values; Strategic plan; Business model; Strategic analysis; Monitoring the strategic plan.
• Project Management: Project management figure; Team management; Communication in team management.
• Decision Making: Problem definition; Selection of criteria and techniques; Development of alternatives; Analysis; Decision; Action plan; Examples of problems.
• Agile Methodologies: Product management; Lean startup; Agile management.
• Management Skills: Leadership; Effective communication; Coaching; Empowering teams; Change management.
• Digital Business: E-commerce operations; e-procurement; Operational management of e-commerce; Marketplaces; The last mile; Exponential structures; Digital business.
• Digital Transformation: Business digitalisation; Artificial Intelligence; The Internet of Things; Blockchain; Big Data and Business Intelligence; Cloud computing; Industrial automation and robotics; Cybersecurity.
• Supply Chain: Supply chain management; Purchase management; Warehouse management; Logistic models; Reverse logistics; Amazon Model; Innovation and sustainability.
• Big Data: Introduction to big data; Big data applications in projects; Agile methodologies; Artificial Intelligence; Use cases in industry.
• Data Management: Open data; Data management; Data privacy; Data storage; Strategy and data.
• Business Intelligence: Introduction to business intelligence; Business intelligence systems; Designing reports, dashboards, and KPIs; Data sources; Data quality.
• Python, Carto, Power BI, and Google Data Studio: Data interpretation; Interactive visualisation with Python; Introduction to Carto; Microsoft Power BI; Google Data Studio.
• Databases: Database fundamentals; Database technology; SQL Practice; NoSQL practice; Databases for networks; Cloud databases.
• Data Analysis and Interpretation: Data representation; Measurements; Regression and correlation; Probability; Distributions; Confidence intervals; Introduction to Hypothesis Testing; Statistics with R.
• Artificial Intelligence: Data analysis with Python; Introduction to machine learning; Supervised and unsupervised machine learning; Reinforcement learning; Deep Learning Fundamentals.
• Storage Technologies for Big Data: Apache Hadoop; The Hadoop Ecosystem; Apache Spark; Streaming Technologies; File systems and platforms for big data in the cloud.

Graduates of the Master in Project Management - Big Data and Business Intelligence can pursue various career paths, including roles such as Information Technology (IT) and Big Data project managers, project management consultants, and business data analysts. They are well-equipped to work in diverse sectors, utilising their skills to manage technology and data in organisations of all sizes. This programme not only enhances employability but also prepares students for leadership positions in the technology industry, where they can drive data-informed decision-making and project success.