Double Master in Big Data & BI + AI for Business

Master in Big Data and Business Intelligence + Master in AI for Business | ENEB Business School

• Type: Double Master
• Duration: 12 months
• Delivery Mode: 100% Online / Distance Learning
• Credits: 72 ECTS
• Language: English
• Start Date: Chosen by the student
• Regular Fee: $3,260
• Offer Price: $1157
• Yearly Fee: $1157 for the full 12-month program
• Scholarships: Available

The Master in Big Data and Business Intelligence + Master in AI for Business is a Double Master program designed for professionals who want to combine advanced data-analysis capabilities with a practical understanding of Artificial Intelligence and its application across modern business functions.

Organizations now collect information from websites, transactions, customers, logistics networks, financial systems, employee platforms, marketing campaigns, connected devices, and operational processes. However, large volumes of data do not automatically create useful knowledge. Companies need professionals who can structure, interpret, visualize, protect, and communicate data while connecting analytical findings to strategic goals.

This Double Master brings those responsibilities together. The Big Data and Business Intelligence component develops knowledge of data management, Business Intelligence systems, reports, dashboards, KPIs, databases, Python, Power BI, Google Data Studio, statistical analysis, machine learning, Hadoop, Spark, streaming technologies, and cloud platforms. The AI for Business component expands this technical foundation through practical Artificial Intelligence applications in finance, marketing, human resources, operations, decision-making, leadership, e-commerce, business planning, and digital transformation.

The combined structure is especially relevant because AI depends on data. Artificial Intelligence systems require suitable information, clear objectives, reliable storage, appropriate governance, and careful interpretation. A company may want to automate a process, forecast demand, personalize marketing, improve recruitment, or analyze financial risk, but these initiatives will be more effective when the organization understands both data and business context.

The program is designed to help students connect technical tools with practical business needs. Learners examine how data is collected, stored, analyzed, visualized, and used for decision-making. They also explore how AI may support daily business activity, improve processes, optimize resources, and contribute to digital transformation.

The curriculum combines technical and managerial knowledge. Students study machine learning, data analysis, SQL, NoSQL, cloud databases, Hadoop, Spark, and visualization. At the same time, they develop project-management, communication, leadership, decision-making, business-planning, and operations-management skills.

This balance is important because data and AI projects are often multidisciplinary. A successful initiative may require collaboration between analysts, developers, managers, finance teams, marketing departments, HR professionals, operations leaders, legal advisors, and senior executives. Professionals who understand both the technical and organizational dimensions may be better prepared to coordinate these teams and communicate effectively.

The program also addresses digital transformation. Artificial Intelligence, Big Data, cloud computing, cybersecurity, blockchain, automation, robotics, and connected technologies are changing how organizations operate. The curriculum helps students understand these developments within a wider strategic context rather than treating them as isolated tools.

The e-commerce and web-positioning subjects provide additional business relevance. Companies increasingly use data and AI to understand online behavior, improve user experience, manage campaigns, optimize conversion, personalize communication, and support digital sales. The program helps learners see how analytics and AI connect with customer acquisition and digital operations.

The program is delivered entirely online through ENEB Business School’s Virtual Campus. Students can access academic materials, communicate with professors and tutors, complete assessments, submit final projects, and connect with classmates without relocating. The student chooses the start date, providing flexibility for working professionals and international learners.

The stated duration is 12 months, and the Double Master includes 72 ECTS credits. The language of study is English. According to the supplied program information, students also receive registration in ENEB’s job bank, the possibility of internships in companies, and tutorials from Monday to Sunday.

Choosing to study through ENEB, the European Business School of Barcelona, allows learners to follow a distance-learning model designed for professionals who want advanced education while maintaining their current work and personal responsibilities.

This Double Master may be especially suitable for IT professionals, data analysts, Business Intelligence specialists, computer scientists, engineers, statisticians, mathematicians, business managers, consultants, entrepreneurs, digital-transformation professionals, operations leaders, and graduates who want to build a career at the intersection of data, AI, and business.

Double Certification

Upon completing the program, eligible students can receive a double certification awarded by the European Business School of Barcelona and described in the supplied information as endorsed and certified by Universidad Isabel I.

The program includes:

1. Master in Big Data and Business Intelligence + Master in AI for Business
2. Diploma of Specialization in Innovation and Project Management, issued by the European Business School of Barcelona

The principal qualification reflects advanced study in Big Data, Business Intelligence, data management, databases, visualization, machine learning, Artificial Intelligence, business applications, digital transformation, leadership, and strategic decision-making.

The additional Diploma of Specialization in Innovation and Project Management strengthens the professional profile by emphasizing two areas that are highly relevant to data and AI initiatives.

Innovation is important because organizations use data and AI to improve products, services, operations, customer experiences, and business models. Project management is equally important because AI implementation, data-platform development, dashboard creation, cloud migration, process automation, and Business Intelligence transformation all require structured planning and execution.

The combination may therefore support professionals who want to lead AI implementation, Big Data projects, Business Intelligence programs, data-strategy initiatives, digital-transformation projects, or technology-enabled operational improvements.

Students should confirm the current certification and issuance conditions directly with ENEB before enrolling. Recognition may vary by country, employer, university, immigration authority, or regulated profession. Anyone planning to use the qualification for a specific academic, legal, employment, immigration, or professional purpose should verify the relevant requirements independently.

Who Is It For?

The Master in Big Data and Business Intelligence + Master in AI for Business is aimed at:

• IT professionals who want to specialize in Big Data, Business Intelligence, and AI.
• Computer scientists who want to connect technical knowledge with business decision-making.
• Data analysts who want to strengthen machine-learning, visualization, and leadership skills.
• Business Intelligence professionals who want broader knowledge of AI and business transformation.
• Engineers who want to apply analytical and technical capabilities in business environments.
• Mathematicians and statisticians who want to specialize in data-driven business decisions.
• Business professionals who want to improve analytical and strategic decision-making.
• Managers and executives who want to understand how data and AI can improve performance.
• Project managers who lead Big Data, Business Intelligence, or Artificial Intelligence initiatives.
• Digital-transformation professionals who need stronger analytics and AI capabilities.
• Operations managers who want to use data and automation to improve efficiency.
• Marketing professionals interested in AI-supported customer analysis and campaign optimization.
• Finance professionals who want to understand AI applications in financial analysis and forecasting.
• Human resources professionals who want to understand AI-enabled talent and workforce processes.
• E-commerce professionals who want to combine analytics, AI, user experience, and online sales.
• Consultants and advisors who help organizations implement data and AI strategies.
• Entrepreneurs interested in launching businesses related to Big Data, Business Intelligence, or AI.
• University graduates from any discipline who want advanced knowledge of data analysis and business decision-making.
• Career changers who want to move into data, AI, Business Intelligence, or digital-transformation roles.
• Professionals working in international environments who need to communicate data insights across teams and cultures.

The program is particularly relevant to learners who understand that technical tools create value only when they solve real business problems. A successful data or AI initiative requires clear objectives, reliable information, ethical awareness, appropriate technology, and effective communication.

Program Objectives

The curriculum aims to help students:

• Develop advanced data-analysis skills.
• Understand data mining and machine learning.
• Master the use of data-analysis and programming tools.
• Learn Business Intelligence techniques.
• Improve strategic decision-making.
• Apply AI in daily business operations.
• Improve processes through AI.
• Optimize business resources.
• Develop leadership capabilities.
• Build project-management skills.
• Improve communication and teamwork.
• Lead digital-transformation processes.
• Understand Big Data storage technologies.
• Learn Hadoop and Spark concepts.
• Understand streaming technologies.
• Develop database knowledge.
• Build SQL and NoSQL awareness.
• Understand cloud-based databases.
• Learn data-management and privacy principles.
• Design reports, dashboards, and KPIs.
• Use Python for data interpretation and visualization.
• Understand Microsoft Power BI.
• Learn Google Data Studio.
• Develop statistical-analysis knowledge.
• Understand supervised, unsupervised, and reinforcement learning.
• Build awareness of deep learning.
• Apply AI in finance, marketing, human resources, and operations.
• Develop e-commerce and web-positioning knowledge.
• Improve leadership and change-management skills.
• Build business-planning and operations-management awareness.
• Prepare students to lead complex AI, Big Data, and Business Intelligence projects.

By completing the program, students should be better prepared to analyze data, evaluate AI opportunities, communicate insights, manage projects, and connect technical capabilities with business strategy.

Distance Learning Methodology

The Double Master is delivered entirely online to help students balance study with professional and personal responsibilities.

All educational content is accessed through ENEB’s Virtual Campus. Students can study from different locations, organize learning according to their availability, communicate with professors, and complete assessments and final projects remotely.

After enrollment, students receive access to academic resources, discussion forums, communication channels, executive training in English, and the wider ENEB Campus community.

The online format may be particularly useful to professionals who already work in data, technology, consulting, operations, e-commerce, project management, or business leadership. These roles may involve technical teams, reporting responsibilities, deadlines, and rapidly changing priorities.

The student-selected start date provides additional flexibility. However, successful completion still requires planning, consistent study, and regular progress throughout the program.

Evaluation

Self-assessments are available through the Virtual Campus to help students consolidate their knowledge. These self-assessments are voluntary and do not count toward the final grade.

To pass all subjects, students must submit a final project for each course. Once tutors evaluate the work, the grade becomes available through the Virtual Campus. Students also receive a detailed evaluation document by email.

Tutors assess:

1. Presentation — including design, visual quality, and spelling.
2. Development — including complexity, logic, and coherence.
3. Added value — including depth and professional contribution.

This project-based approach allows students to analyze Big Data, Business Intelligence, and AI-related business situations and present structured recommendations.

Grants & Scholarships

ENEB states that scholarship places are limited and granted in order of enrollment.

Direct Scholarship

Available without requirements or administrative procedures during each enrollment period.

Academic Excellence Scholarship

Designed for students whose academic and professional qualifications demonstrate excellence.

Entrepreneurial Talent Scholarship

Intended for entrepreneurs who want to apply the program to their careers or businesses.

Women and Equality Scholarship

Designed for female candidates who want to grow professionally and achieve a higher level of education.

Management Scholarship

Intended for professionals whose responsibilities require continuous growth and development.

Corporate Scholarship

Designed for professionals who want to strengthen their careers and compete for more senior positions.

Scholarship for Self-Employed Professionals

Intended for independent professionals who want to deepen their knowledge or grow their businesses.

SMEs Scholarship

Designed for entrepreneurs who want to contribute more effectively to the growth of their companies.

Scholarship for the Unemployed

Intended for people pursuing further study to improve their ability to re-enter the employment market.

Geographical Mobility Scholarship

Designed for applicants who want to study from anywhere and develop a global view of business.

Applicants should confirm current eligibility rules, award amounts, evidence requirements, and whether scholarships can be combined with the promotional price.

Why This Program Stands Out

The Double Master combines advanced Big Data and Business Intelligence knowledge with practical AI-for-business applications.

Many data programs focus mainly on analytics, databases, or technical tools. AI programs may focus on algorithms or automation. This program connects both while also developing project-management, leadership, business-planning, e-commerce, and operations capabilities.

Students study Hadoop, Spark, machine learning, data management, Business Intelligence, databases, statistics, Python, Power BI, AI for Business, e-commerce, web positioning, digital transformation, leadership, decision-making, business planning, and operations.

Key features include:

• Two complementary master’s specializations
• 72 ECTS credits
• 12-month duration
• Fully online delivery
• Student-selected start date
• English-language study
• Remote assessments and final projects
• Big Data and Business Intelligence
• Machine learning and deep-learning fundamentals
• Hadoop, Spark, and streaming technologies
• Python, Power BI, Carto, and Google Data Studio
• SQL, NoSQL, and cloud databases
• Data analysis and statistics
• AI applications across business functions
• E-commerce and web positioning
• Digital transformation
• Project management and agile methodologies
• Leadership and decision-making
• Operations management
• Innovation and project-management specialization
• Job-bank registration
• Possibility of internships
• Tutorials from Monday to Sunday
• Scholarships and flexible payment options

The program may help data professionals develop stronger business and leadership skills and help managers understand AI, analytics, and technical infrastructure. It may also support consultants and entrepreneurs who want to build or lead data-driven and AI-enabled initiatives.

Frequently Asked Questions

What is the Double Master in Big Data & BI + AI for Business?

It combines the Master in Big Data and Business Intelligence with the Master in AI for Business in one online program.

How long does the program take?

The stated duration is 12 months.

How many ECTS credits are included?

The program includes 72 ECTS credits.

Is the program fully online?

Yes. Learning content, assessments, final projects, and tutor communication are delivered online.

What language is used?

The stated language is English.

When can I start?

The student chooses the start date.

What is the offer price?

The regular fee is $3,260, and the offer price is $1157.

Are scholarships available?

Yes. ENEB lists several scholarship categories, subject to availability and current eligibility conditions.

Do I need a degree in data science or AI?

No specific degree in those subjects is listed. Degree holders in any field, current university students, and eligible professionals may apply.

What qualifications can I receive?

The supplied information lists the combined Double Master qualification and a Diploma of Specialization in Innovation and Project Management.

Does the program include machine learning?

Yes. Supervised, unsupervised, and reinforcement learning are included, along with deep-learning fundamentals.

Does the syllabus include Power BI?

Yes. Microsoft Power BI is included.

Is Python included?

Yes. Python is included for data analysis and interactive visualization.

Does the program include databases?

Yes. Database fundamentals, MySQL, NoSQL, network databases, and cloud databases are included.

Are Hadoop and Spark included?

Yes. Hadoop, the Hadoop ecosystem, Spark, streaming technologies, and cloud platforms are included.

Does the program include AI for business functions?

Yes. AI for finance, marketing, human resources, and operations is included.

Is statistical analysis included?

Yes. Regression, correlation, probability, confidence intervals, hypothesis testing, and statistics with R are included.

Does the program include e-commerce?

Yes. Online sales, web stores, mobile applications, analytics, user experience, digital campaigns, mobile payment, and landing pages are included.

Does the program include SEO and SEM?

Yes. SEO and SEM are included in the Web Positioning section.

How are students evaluated?

Students submit final projects, which are assessed for presentation, development, coherence, and added value.

Do self-assessments count toward the final grade?

No. They are voluntary and do not count toward the final grade.

Can I work while studying?

The online format is designed to support flexible study, but students must still organize their time consistently.

Is career support included?

The supplied information mentions registration in ENEB’s job bank and the possibility of internships.

What career paths may be relevant?

Relevant roles include Applied AI Specialist, Data Analyst, Digital Transformation Consultant, E-commerce Manager, Business Intelligence Analyst, Big Data Architect, AI and Big Data Project Leader, and Operations Director With AI.

A Double Master for Data Intelligence and AI-Enabled Business Transformation

Organizations need professionals who understand data, Artificial Intelligence, business strategy, and implementation.

The Double Master in Big Data & BI + AI for Business brings these responsibilities together.

The data side develops knowledge of analytics, Business Intelligence, databases, visualization, machine learning, and Big Data infrastructure. The AI-for-business side develops knowledge of practical AI applications across finance, marketing, HR, operations, and strategic decision-making.

For data professionals, this combination can strengthen business, leadership, and project capabilities. For managers, it can improve understanding of analytics and AI. For consultants and entrepreneurs, it can support the development of data-driven and technology-enabled business models.

The program is delivered fully online, allowing students to study without relocating. Before enrolling, applicants should confirm current tuition, scholarships, required documents, certification conditions, and recognition requirements.

Request Information

Request information to confirm:

• Admission eligibility
• Required documents
• Availability of the $1157 offer
• Scholarship options
• Payment conditions
• Tuition inclusions
• Certification details
• Virtual Campus access
• Tutor support
• Job-bank and internship availability
• Any additional administrative requirements

The Master in Big Data and Business Intelligence + Master in AI for Business is made up of the following syllabus:

Section 1: Storage Technologies for Big Data

• Topic 1. Apache Hadoop
• Topic 2. The Hadoop Ecosystem
• Topic 3. Apache Spark
• Topic 4. Streaming Technologies
• Topic 5. File systems and platforms for big data in the cloud

Section 2: Project Management

• Topic 1. Project management figure
• Topic 2. Team management
• Topic 3. Team management and communication
• Topic 4. Project management

Section 3: Agile Methodologies

• Topic 1. Product management
• Topic 2. Lean startup
• Topic 3. Agile management

Section 4: Artificial Intelligence

• Topic 1. Introduction to data analysis with Python
• Topic 2. Introduction to machine learning
• Topic 3. Supervised machine learning
• Topic 4. Unsupervised machine learning
• Topic 5. Reinforcement learning
• Topic 6. Deep Learning Fundamentals

Section 5: Data Management

• Topic 1. Open data
• Topic 2. Data management
• Topic 3. Data privacy
• Topic 4. Data storage
• Topic 5. Strategy and data

Section 6: Business Intelligence

• Topic 1. Introduction to business intelligence
• Topic 2. Business intelligence systems
• Topic 3. Design of reports, dashboards and KPIs
• Topic 4. Data sources
• Topic 5. Data quality

Section 7: Big Data

• Topic 1. Introduction to big data
• Topic 2. Big data in projects
• Topic 3. Agile methodologies
• Topic 4. Artificial Intelligence
• Topic 5. Use cases in industry

Section 8: Databases

• Topic 1. Database fundamentals
• Topic 2. Database technology
• Topic 3. SQL Practice (MySQL)
• Topic 4. SQL Practice (MySQL)
• Topic 5. NoSQL practice (Hbase)
• Topic 6. Databases for networks
• Topic 7. Databases in the cloud

Section 9: Data Analysis and Interpretation

• Topic 1. Data representation
• Topic 2. Measurements
• Topic 3. Regression and correlation
• Topic 4. Probability
• Topic 5. Distributions
• Topic 6. Confidence intervals
• Topic 7. Introduction to Hypothesis Testing
• Topic 8. Statistics with R

Section 10: Python, Carto, Power BI and Google Data Studio

• Topic 1. Interpretation of data
• Topic 2. Interactive visualization with Python
• Topic 3. Introduction to Carto
• Topic 4. Microsoft Power BI
• Topic 5. Google Data Studio

Section 11: AI for Business

• Topic 1. Introduction to AI
• Topic 2. How to Apply AI in Your Daily Life
• Topic 3. AI in the workplace
• Topic 4. AI for Finance
• Topic 5. AI for Marketing
• Topic 6. AI for Human Resources
• Topic 7. AI for Operations
• Topic 8. Case Studies
• Topic 9. Future of the AI

Section 12: E-commerce

• Topic 1. Online sales
• Topic 2. Web store
• Topic 3. Mobile applications
• Topic 4. From interested lead to buyer
• Topic 5. Web analytics
• Topic 6. User experience
• Topic 7. Digital campaigns
• Topic 8. Mobile payment
• Topic 9. Landing page

Section 13: Web Positioning

• Topic 1. How to attract customers
• Topic 2. SEO: Organic Optimization
• Topic 3. SEM: Payment optimization
• Topic 4. Automating sales
• Topic 5. Growth hacking
• Topic 6. Marketing automation
• Topic 7. Psychology in marketing

Section 14: Digital Transformation

• Topic 1. Business digitalization
• Topic 2. Artificial Intelligence (AI)
• Topic 3. The Internet of Things (IoT)
• Topic 4. Blockchain
• Topic 5. Big Data and Business Intelligence (BI)
• Topic 6. Cloud computing
• Topic 7. Industrial automation and robotics
• Topic 8. Cybersecurity

Section 15: Management Skills

• Topic 1. Leadership
• Topic 2. Effective communication
• Topic 3. Coaching
• Topic 4. Empowering teams
• Topic 5. Change management

Section 16: Decision Making

• Topic 1. Problem definition
• Topic 2. Selection of criteria and techniques
• Topic 3. Development of alternatives
• Topic 4. Analysis
• Topic 5. Decision
• Topic 6. Action plan
• Topic 7. Examples of problems

Section 17: Business Plan

• Topic 1. Vision, mission and values
• Topic 2. Strategic plan
• Topic 3. Business model
• Topic 4. Strategic analysis
• Topic 5. Monitoring the strategic plan

Section 18: Operations Management

• Topic 1. Business Strategy
• Topic 2. Operations Management
• Topic 3. Demand
• Topic 4. Product development
• Topic 5. Operating systems
• Topic 6. Process planning and management
• Topic 7. Operational planning
• Topic 8. The human factor in operations management

Applicants must meet at least one of the following requirements:

• Hold a degree in any field, including a Bachelor’s degree, Architecture qualification, Higher or Technical Engineering qualification, Licentiate, Diploma, or equivalent.
• Be a university student currently pursuing a degree or equivalent higher education studies.
• Be a professional with career prospects in a current position.

Applicants who do not meet one of these conditions may contact ENEB so the admissions department can evaluate their individual case.

A degree specifically in data science, computer science, engineering, mathematics, statistics, Artificial Intelligence, or business is not listed as a requirement. Applicants from different academic and professional backgrounds may therefore be considered through the appropriate admission route.

Prospective students should confirm that they can dedicate enough time to a 12-month online Double Master. They should also verify whether the qualification meets any academic, employment, immigration, or professional-recognition requirements that apply to their goals.

Applied AI Specialist

An Applied AI Specialist supports the implementation of Artificial Intelligence solutions across business functions.

The role may involve identifying suitable use cases, coordinating with technical teams, reviewing data requirements, supporting implementation, monitoring results, and communicating recommendations.

Potential application areas include finance, marketing, human resources, operations, customer service, and business planning.

The program supports this profile through Artificial Intelligence, AI for Business, data management, Business Intelligence, machine learning, project management, digital transformation, and decision-making.

Data Analyst

A Data Analyst collects, processes, interprets, and communicates data that may support business decisions.

Responsibilities may include data preparation, reporting, dashboard creation, statistical analysis, trend identification, and presentation of insights.

The program supports this role through Big Data, Business Intelligence, Python, Power BI, databases, statistics, data management, and decision-making.

Digital Transformation Consultant

A Digital Transformation Consultant advises organizations on the adoption of new technologies and digital processes.

The role may involve assessing current capabilities, identifying opportunities, recommending systems, designing roadmaps, supporting implementation, and evaluating outcomes.

The Double Master supports this profile through digital transformation, AI, Big Data, Business Intelligence, cloud technologies, project management, leadership, and business planning.

E-commerce Manager

An E-commerce Manager oversees online sales platforms and digital commercial performance.

Responsibilities may include website operations, customer experience, campaigns, analytics, mobile payment, conversion, and coordination with marketing and operations teams.

The program supports this role through e-commerce, web analytics, digital campaigns, Business Intelligence, AI for Marketing, data analysis, and web positioning.

Business Intelligence Analyst

A Business Intelligence Analyst collects, analyzes, and presents business information to support strategic decisions.

The role may involve dashboard development, KPI design, data-quality review, reporting, stakeholder communication, and performance analysis.

The program supports this profile through Business Intelligence systems, reports, dashboards, data sources, Power BI, Google Data Studio, databases, and data management.

Big Data Architect

A Big Data Architect designs and supports systems for storing, processing, and managing large volumes of information.

The role may involve data platforms, architecture decisions, cloud systems, Hadoop, Spark, streaming technologies, databases, governance, and collaboration with developers and analysts.

The program provides relevant foundations through storage technologies, data management, databases, Big Data, cloud platforms, and project management.

AI and Big Data Project Leader

An AI and Big Data Project Leader plans, coordinates, and supervises data and Artificial Intelligence initiatives.

The role may involve defining scope, managing teams, reviewing risks, coordinating stakeholders, monitoring progress, and ensuring that projects support business objectives.

The program supports this profile through project management, agile methodologies, leadership, Big Data, AI, Business Intelligence, decision-making, and business planning.

Operations Director With AI

An Operations Director With AI focuses on improving business operations through data, automation, analytics, and Artificial Intelligence.

The role may involve demand planning, process improvement, resource allocation, performance monitoring, technology adoption, and team leadership.

The Double Master supports this direction through AI for Operations, operations management, data analysis, Business Intelligence, digital transformation, and leadership.

Additional Career Directions

Graduates may also pursue roles such as:

• Big Data Analyst
• Business Intelligence Consultant
• Power BI Analyst
• Data Visualization Specialist
• Data Strategy Consultant
• Machine Learning Business Analyst
• AI Implementation Coordinator
• Data Project Manager
• Digital Operations Manager
• Analytics Consultant
• Database Analyst
• Data Governance Coordinator
• Cloud Data Project Manager
• E-commerce Analytics Specialist
• Marketing Data Analyst
• Financial Data Analyst
• HR Analytics Specialist
• Technology and Innovation Manager
• Digital Business Analyst
• AI Business Consultant
• Data Product Manager
• PMO Analyst for Technology Projects
• Startup Founder
• Entrepreneur

Career outcomes depend on previous experience, sector knowledge, language ability, local market conditions, and employer requirements. Completion does not guarantee a particular role, promotion, or salary.

Skills Graduates May Develop

The program is designed to support skills in:

• Big Data
• Business Intelligence
• Data mining awareness
• Machine learning
• Python-based data analysis
• Dashboard and KPI design
• Microsoft Power BI
• Google Data Studio
• SQL and NoSQL awareness
• Data management
• Data privacy
• Cloud databases
• Hadoop and Spark
• Streaming technologies
• Statistical analysis
• AI for Finance
• AI for Marketing
• AI for Human Resources
• AI for Operations
• E-commerce analytics
• SEO and SEM awareness
• Project management
• Agile methodologies
• Digital transformation
• Leadership and communication
• Strategic decision-making
• Business planning
• Operations management
• Cross-functional collaboration
• AI and data project leadership