Data Analytics for Business Leaders

Data Collection Methods

• Design structured and unstructured data collection strategies.
• Use quantitative and qualitative methods for reliable data capture.
• Integrate APIs and automation tools for continuous data gathering.
• Ensure ethical compliance in data collection and storage practices.

Data Cleaning and Preparation

• Apply data validation and cleansing techniques to ensure accuracy.
• Develop processes for handling missing, inconsistent, or duplicate data.
• Automate preprocessing workflows using Python and SQL tools.
• Prepare datasets for effective analysis and visualisation.

Foundations of Data Analytics

• Understand the core principles, tools, and methodologies in analytics.
• Explore data lifecycle stages from collection to insight generation.
• Apply descriptive, diagnostic, and predictive analytics techniques.
• Develop problem-solving approaches using statistical reasoning.

Data Visualisation and Communication

• Transform data into meaningful and actionable visual insights.
• Use dashboards and storytelling to communicate analytical outcomes.
• Apply visual design principles to enhance understanding and engagement.
• Leverage software tools like Power BI and Tableau for visual analytics.

Predictive Analytics and Forecasting

• Develop predictive models using regression and time-series techniques.
• Apply machine learning algorithms for accurate forecasting.
• Interpret predictive results to support business decisions.
• Integrate predictive analytics into enterprise planning systems.