Module 6: Analytics and Data-driven Decision Making

Module 6: Analytics and Data-driven Decision Making-

Introduction to Analytics and Data-driven Decision Making

Data Collection and Sources

Data Cleaning and Preparation

Exploratory Data Analysis (EDA)

Key Performance Indicators (KPIs)

A/B Testing and Experimentation

Customer Behavior Analysis

Predictive Analytics and Forecasting

Data Visualization and Reporting

Ethical Data Usage and Privacy – Ethical considerations in data collection and analysis – Privacy regulations (e.g., GDPR) and compliance – Ensuring responsible data practices

Data-driven Decision Making – Integrating data into decision-making processes – Case studies of data-driven decision successes and failures – Overcoming common barriers to data-driven decision-making

Continuous Improvement and Optimization – Implementing feedback loops and iterative processes – Data-driven optimization of websites, marketing campaigns, and operations – Measuring the impact of optimizations

Emerging Trends in Analytics – Big data and real-time analytics – Artificial intelligence and machine learning in data analysis – The role of data analytics in IoT and connected devices