Chief Data Officer Program

Course Outline

Day 1: Introduction to Data Management & the CDO Role

• Morning: CDO role & data strategy
  Objective: understand the strategic importance of data.
• Content:
  The role and responsibilities of the CDO.
  The place of data in digital transformation.
  Data as a competitive advantage.
• Afternoon: Data governance & digital transformation
  Objective: identify core data governance practices.
• Content:
  Data governance frameworks and principles.
  Levers of data-driven transformation.
  Case study: strategic impact of data in large enterprises.

• Morning: Data governance
  Objective: master governance fundamentals.
• Content:
  Defining and implementing a data governance policy.
  Data lineage and data catalogs.
  Metadata management.
• Afternoon: Data quality
  Objective: assess and ensure data quality.
• Content:
  Principles of Data Quality Management.
  Processes and tools to improve quality.
  Case study: data quality challenges in organizations.

• Morning: Modern data architectures
  Objective: choose architectures aligned to business needs.
• Content:
  Data lakes, data warehouses, and cloud platforms.
  Selecting storage/analytics architectures.
  Big Data solutions: Hadoop, Spark, etc.
• Afternoon: Data security & risk management
  Objective: secure data and manage risks.
• Content:
  Securing data in cloud and on-prem.
  Preventing data loss and leakage.
  Compliance (ISO 27001, etc.).
  Case study: securing data in multi-cloud.

• Morning: Analytics foundations
  Objective: understand analytics tools and business uses.
• Content:
  BI, Data Science, ML & AI overview.
  Building a data-driven culture.
  Use cases for advanced analytics.
• Afternoon: Embedding AI/ML in the enterprise
  Objective: integrate AI into decision-making.
• Content:
  Deploying AI/ML algorithms in production.
  Business optimization use cases.
  Case study: AI projects across industries.

• Morning: Data regulations & compliance
  Objective: apply standards to sensitive data.
• Content:
  GDPR, CCPA, and other regulations.
  Privacy principles and consent management.
  Corporate roles and responsibilities for personal data.
• Afternoon: Governance of sensitive data & risk
  Objective: govern and protect sensitive data.
• Content:
  Managing personal/health and other sensitive data.
  Access control and protection strategies.
  Case study: bringing a multinational into compliance.

• Morning: CDO leadership & change
  Objective: lead data-driven transformation.
• Content:
  The CDO as change leader.
  Driving data-centric culture change.
  Communicating the data strategy to executives.
• Afternoon: Building a high-performing data team
  Objective: staff and run an effective data organization.
• Content:
  Hiring and managing DS/DA/DE talent.
  Building multidisciplinary teams.
  Cross-functional collaboration (IT, marketing, finance).
  Case study: managing a data team in a complex org.

• Morning: Data value strategy
  Objective: design strategies to monetize and leverage data.
• Content:
  Monetization models.
  Data-driven business models and partnerships.
  Governance and operating models to maximize value.
• Afternoon: Process optimization with data
  Objective: improve internal processes using data.
• Content:
  Data-informed decision-making and process optimization.
  Defining and tracking KPIs for data initiatives.
  Case study: boosting operational efficiency with data.

• Morning: Review & strategic plan
  Objective: consolidate learning and draft a governance plan.
• Content:
  Key takeaways and best practices.
  Drafting a strategic data governance & value plan.
  Implementation challenges discussion.
• Afternoon: Project presentations & wrap-up
  Objective: apply concepts and receive feedback.
• Content:
  Group project presentations (governance & strategy).
  Feedback and discussion with instructors.
  Course conclusion and CDO career outlook.