Data Strategy for Leaders In collaboration with Imperial Executive Education

Data Strategy for Leaders

In collaboration with Imperial Executive Education 

• Drive Innovation and Organizational Success with Data and GenAI
• Learn to create data strategy frameworks integrated with GenAI applications
• Explore key principles of data governance, privacy, and security
• Earn Associate Alumni status from Imperial Executive Education 

• 14 weeks length program of eLearning & Live classroom 
• Ask us for the next cohort and schedule details!

A robust data strategy is essential for businesses of all sizes, serving as the foundation for informed decision-making and effective navigation of complex challenges. Data strategy leaders design and implement frameworks that align with business goals, drive efficiency, foster innovation, ensure regulatory compliance, and provide a competitive edge.

The Data Strategy for Leaders program equips business leaders to harness data for strategic decisions, optimize performance, and accelerate growth. Developed and delivered by experienced data leaders, the program enhances strategic acumen and prepares participants to become influential data strategy leaders within their organizations.

Key Features

• Course and material are in English
• Learn from experienced data leaders
• Intermediate level
• 14 weeks of program with industry experts (3-6 hours/week time commitment)
• 1 year platform access & class recordings  
• 17 hours of self-paced eLearning content
• 50+ hours of study time and practice recommended
• Apply knowledge through business scenarios, case studies, and hands-on projects
• Gain Imperial Executive Education Associate Alumni status
• Earn a certificate of completion from Imperial Executive Education 

About Imperial Executive Education 

Established by royal charter in 1907, Imperial Executive Education  is consistently ranked among the world’s top universities, Imperial Executive Education drives global business and social transformation by combining business expertise, technological innovation, and an entrepreneurial mindset. Known for integrating cutting-edge technologies and practical research, the school develops solutions to real-world challenges. Recognized by governments, policymakers, and global business leaders, it consistently ranks among the top business schools in Europe and worldwide, fostering innovation, entrepreneurial thinking, and exceptional talent.

What added value does Imperial Executive Education contribute to the program?

The program curriculum is designed and reviewed with the assistance of the university, which gives the program quality legitimacy and a co-branded certificate of completion. Please be aware that the live classes are not all held by actual University faculty staff but by many experienced Industry experts who are suitable for each topic. 

Learning Objective

• Understand the key roles and responsibilities of a data strategy leader
• Identify the infrastructure and levers needed to align data practices with business goals
• Formulate and implement a data strategy that delivers measurable business value
• Secure executive buy-in for enterprise-level data initiatives
• Leverage AI and ML technologies to generate advanced insights and business intelligence
• Explore the use of Generative AI to enhance data strategy development
• Drive data-driven innovation while adhering to governance, ethical, and privacy standards
• Build and maintain a data-centric culture that fosters decision-making, innovation, and value creation

10+ Skills Covered

• Data Strategy & Governance
• Machine Learning & Data Science
• Generative AI for Data Innovation
• Data Monetization & Analytics
• Data Privacy & Security
• Digital Transformation

Target Audience:

This comprehensive, high-engagement program is designed for:

• Senior leaders with proven organizational leadership experience
• Business heads aiming to leverage data and scale products
• Aspiring or current C-level executives seeking to stay ahead of trends and drive business growth

Prerequisites:

• Preferably 8+ years of full-time professional experience
• Prior coding or technical knowledge is helpful but not required
• Strong motivation to leverage data for strategic advantage

Learning Path

1. Orientation Session
2. Introduction to Data Strategy
3. Data Orchestration
4. Data Science, AI, and Machine Learning for Managers & Leaders
5. Data-driven Digital Transformation
6. Data Monetisation
7. Data Governance, Privacy, and Security

Electives

• Career Path Towards a CDAO/Data Leader
• Masterclass: Generative AI for Data Strategy

COURSE CONTENT DETAILS

• Module 0: Orientation Session

Kick off the Data Strategy for Leaders program by exploring the course content. This orientation session introduces the curriculum and prepares you for an engaging, impactful learning experience.

• Module 1: Introduction to Data Strategy

This module introduces the fundamentals of data strategy, guiding you through its lifecycle and showing how to use data as a strategic asset.

Learning Outcomes:

• Build a foundational understanding of data strategy and its strategic categories
• Assess data’s transformational and commercial impact within an organization
• Learn to leverage and monetize metadata to enhance business operations
• Evaluate the maturity of an organization’s data strategy, including engineering and monetization aspects
• Understand principles of data governance and compliance in strategy execution

Topics Covered

• Overview of Data Strategy
• Key Components of a Successful Data Strategy
• Data Commercialization
• Assessing Data Strategy Maturity
• Designing a Data Strategy
• Implementing a Data Strategy

• Module 2: Data Orchestration

Data orchestration involves collecting, organizing, and preparing data from multiple sources for analysis. This module covers evaluating data sources, managing quality, handling extraction and modeling, and ensuring data security.

Learning Outcomes:

• Understand the strategic role of data orchestration
• Master principles of data quality management
• Assess and integrate diverse data sources and storage options
• Learn Extraction, Transformation, and Load (ETL) processes
• Define data quality metrics and build business use cases
• Explore data security, monitoring, and observability

Topics Covered:

• Introduction to Data Orchestration
• Data Quality and Management
• Data Sources, Integration, and Storage
• Modern Data Stack and ETL Processes
• Modeling Schemes and Relational Modeling
• Data Security and Monitoring

• Module 3: Data Science, AI, and Machine Learning for Managers & Leaders

This module builds on data orchestration, teaching you to analyze data and extract actionable business insights. Explore descriptive, predictive, and prescriptive analytics while learning how data science and machine learning can enhance your data strategy.

Learning Outcomes:

• Master core analytics and machine learning concepts, including key ML algorithms
• Apply algorithms like K-Nearest Neighbours and Decision Trees to real-world scenarios
• Utilize clustering techniques to uncover patterns in data
• Evaluate performance metrics for regression and classification models
• Understand the importance of fairness, interpretability, and ethics in AI and ML

Topics Covered:

• Modern Analytics for Business Intelligence
• Demystifying AI
• Advanced Data Science and Machine Learning
• Predictive, Prescriptive, and Descriptive Analytics
• K-Nearest Neighbours
• Decision Tree
• K-Means Clustering

• Module 4: Data-Driven Digital Transformation

This module teaches how to leverage digital technologies to transform business processes. Building on previous modules, you’ll use data insights to develop growth-focused strategies while mastering key technologies such as AI, blockchain, and cloud computing.

Learning Outcomes:

• Understand digital transformation and its impact on organizational growth
• Explore data maturity models and their influence on data strategies
• Learn how innovation, including open innovation and crowdsourcing, drives transformation
• Develop skills in digital storytelling and data visualization for effective communication
• Understand Large Language Models (LLMs) and the economic implications of Generative AI
• Grasp the differences between structured and unstructured data

Topics Covered:

• Pillars of Digital Transformation
• Data Maturity Models
• Digital Storytelling
• Structured and Unstructured Data
• Link Between Innovation and Digital Transformation
• Fundamentals of Blockchain and Cloud Computing

• Module 5: Data Monetisation

Data monetisation involves leveraging organizational data to generate economic value. This module teaches how to transform data into actionable insights, improve business processes, and drive revenue growth, while considering key performance metrics, privacy, and ethics.

Learning Outcomes:

• Understand the principles and processes of data monetisation
• Identify and evaluate opportunities to monetise data
• Develop strategies for creating and pricing data products
• Balance data privacy with monetisation objectives
• Measure and assess the success of data monetisation initiatives
• Explore ethical considerations and regulatory compliance

Topics Covered:

• Different Ways to Monetise Data
• Benefits and Challenges of Monetisation
• Privacy Regulations and Ethical Considerations
• Data Anonymisation and Pseudonymisation
• Identifying Monetisation Opportunities
• Building a Data Monetisation Strategy

• Module 6: Data Governance, Privacy, and Security

Data governance, privacy, and security are interconnected pillars essential for safeguarding organisational data. Governance establishes rules and standards for data management, privacy ensures sensitive information is protected, and security prevents unauthorized access and cyber threats. Together, they ensure ethical, secure, and compliant data handling.

Learning Outcomes:

• Understand the principles and importance of data governance for risk management
• Learn key data privacy laws, including GDPR, and organisational obligations
• Develop skills to manage and respond to data breaches
• Master best practices in data security
• Explore the role of AI and ML in enhancing data security
• Gain insights into developing a comprehensive data governance framework

Topics Covered:

• Introduction to Data Governance
• Privacy and Data Protection Fundamentals
• Security in Data Governance
• Implementing Data Governance Frameworks

Industry Case Studies and Projects

• Project 1 – Designing a Strategic Data Blueprint: Create a 90-day data strategy plan, tackling challenges and aligning initiatives with business goals to gain a competitive advantage.
• Project 2 – Enhancing Data Orchestration for Growth: Design a data orchestration framework, including schematics, to integrate, manage, and govern data for improved decision-making.
• Project 3 – Aligning Analytics with Business Objectives: Build a portfolio of analytics initiatives and a decision tree model to solve business problems and enhance data-driven decision-making in a mortgage company.
• Project 4 – Assessing Data Maturity for Growth: Evaluate an organization’s data maturity and map growth strategies on a 2D matrix to foster a data-driven culture and drive profitability.
• Project 5 – Maximising Value Through Data Monetisation: Identify opportunities, risks, and non-financial benefits to monetise data effectively, driving strategic revenue growth.
• Project 6 – Enhancing Data Governance and Security at HealthPlus: Assess HealthPlus Analytics Inc. on governance, privacy, and infrastructure, and recommend improvements, risk mitigation, and success metrics.
• Project 7 – Revamping Data Strategy for Loan Services: Develop a unified data strategy for customer onboarding, risk management, and governance, implementing controls and metrics to optimise acquisition and reduce risk.

Elective Courses:

Elective 1: Career Path: Towards a CDAO / Data Leader

After completing the Data Strategy for Leaders programme, gain insights into advancing as a data leader within an organisation. Explore the role, responsibilities, and strategic impact of a Chief Data and Analytics Officer (CDAO). Learn career strategies and best practices directly from experienced CDAOs.

Elective 2: Masterclass: Generative AI for Data Strategy

Participate in interactive online masterclasses led by Imperial Executive Education  faculty, focusing on data governance frameworks, emerging trends, and the future of data strategy. Explore how Generative AI (GenAI) can be leveraged to enhance strategic decision-making and organisational value creation.

FREQUENTLY ASKED QUESTIONS

How is the program delivered?

The course is delivered mostly via self-paced eLearning, with some bonus live classes for certain courses.

What should I expect from the Data Strategy for Leaders programme?
In this programme, you will:

• Earn a certificate of completion from Imperial Executive Education 
• Understand data strategy frameworks and data orchestration
• Apply data science for business intelligence
• Lead data-driven digital transformation and governance initiatives
• Explore data monetisation and key performance metrics
• Implement data privacy and security best practices
  
  

Who are the instructors for the Data Strategy for Leaders programme, and how are they selected?

The programme is developed and taught by experienced senior data leaders, chosen for their expertise and industry experience.