Training on Foundations of Data Science for Non-Technical Staff and Managers

Module 1: Understanding Data Science in Business

• Overview of data science, analytics, and the data lifecycle.

• Key data concepts: structured vs unstructured, descriptive vs predictive.

• The role of data in corporate strategy and digital transformation.

• Real-world examples of data-driven business success.
  Case Study: How organizations use analytics to enhance strategic planning.

Module 2: Data Collection, Quality, and Interpretation

• Identifying reliable data sources and managing data quality.

• Basics of data cleaning and preprocessing.

• Reading and interpreting charts, dashboards, and summaries.

• Recognizing errors, bias, and misinterpretation in analysis.
  Case Study: Evaluating customer data to improve operational efficiency.

Module 3: Data-Driven Decision-Making for Managers

• Translating business challenges into analytical questions.

• Linking insights to KPIs and performance metrics.

• Reviewing and assessing analytical reports for business value.

• Communicating findings to non-technical stakeholders.
  Case Study: Using analytics to guide resource allocation and performance improvement.

Module 4: Business Intelligence Tools and Data Visualization

• Introduction to key BI tools: Power BI, Tableau, and Looker Studio.

• Essentials of dashboard interpretation and data storytelling.

• Best practices in visualization for executive communication.

• Overview of automation in reporting and trend analysis.
  Practical Session: Reviewing dashboards to extract actionable insights.

Module 5: Data Ethics, Governance, and Future Trends

• Ethical and responsible use of data in organizations.

• Data privacy, compliance, and governance frameworks.

• Building a data-driven culture and institutionalizing analytics.

• Emerging trends: AI, machine learning, and predictive analytics for managers.
  Capstone Case Study: Designing a simple data-informed strategy for your organization.