Strategic Information Technology – Level 2

Industrial Data Integration

• Leverage analytics in manufacturing and industrial engineering settings.
• Integrate IoT and machine data for predictive operations.
• Develop real-time analytics for asset utilisation and uptime monitoring.
• Apply data standards to streamline industrial decision-making.

Predictive Maintenance Analytics

• Use analytics models to predict equipment failure and maintenance needs.
• Implement machine learning algorithms for predictive insights.
• Design dashboards to visualise performance indicators and trends.
• Optimise operational schedules through data-based forecasting.

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.