Day 1:
Introduction to Data-Driven Decision Making
Overview of data-driven decision making and its importance in business.
Understanding key data concepts and terminologies.
Types of data and how they influence business decisions.
Introduction to data collection methods and data cleaning processes.
Day 2:
Data Analysis Techniques
Exploring descriptive analytics and its role in decision making.
Introduction to predictive modeling and forecasting techniques.
Using data visualization tools to communicate insights effectively.
Hands-on exercises on analyzing and interpreting sample data sets.
Day 3:
Advanced Analytical Methods
Introduction to machine learning and its applications in data-driven decision making.
Evaluating and selecting the right analytical techniques for different business problems.
Integrating external data sources into analysis for richer insights.
Case study analysis on applying advanced analytics in real-world scenarios.
Day 4:
Ethical and Strategic Considerations in Data Use
Understanding data privacy, security, and ethical implications.
Identifying and mitigating bias in data collection and analysis.
Exploring the limitations of data and the risks of overreliance on data-driven decisions.
Best practices for developing ethical data governance policies in organizations.
Day 5:
Implementing Data-Driven Decision Making in Your Organization
Creating a roadmap for adopting data-driven decision making in your team or organization.
Building a data-driven culture: training, tools, and strategies for success.
Communicating data insights to stakeholders and fostering alignment.
Final case study presentation: applying data-driven decision-making strategies to solve a business challenge.
