Faculty of Social Sciences

Sagicor Cave Hill School of Business and Management

Short Courses

Applied Business Analytics

Registration is Open

Programme Overview

The Power of Applied Data: Intelligence. Action. Results.

In today’s business environment, data is everywhere but insight is rare. Applied Business Analytics is designed for leaders who need to move beyond numbers and dashboards, turning data into a direct source of competitive advantage. This is a journey from data overload to clarity, from descriptive reporting to predictive and prescriptive action, and from analytics as a support function to analytics as the driving force of growth.

The programme takes you deep into the foundations of modern analytics, from governance and architecture to advanced predictive techniques, showing you how to transform raw information into business value. You will learn how to design strategies that align analytics with organisational priorities, build decision-ready dashboards and models that steer performance, and apply advanced methods to real commercial challenges. Just as importantly, you will explore how to scale analytics responsibly across the enterprise, embedding it as a culture that powers resilience and growth.

By the end, you will not just understand analytics; you will speak its language fluently. You will know how to ask sharper business questions, demand smarter answers from your data, and apply those insights directly to the choices that shape revenue, manage risk, and create long-term advantage. This is about more than data literacy. It is about using intelligence to take action, and action to deliver results that matter.

Programme Objectives

On successful completion of the programme, you will be able to: 

  • Explain how analytics problem-solving can support team collaboration and project outcomes. 
  • Apply analytics problem-solving techniques to guide teams in addressing business challenges. 
  • Differentiate between descriptive, diagnostic, predictive, and prescriptive analytics. 
  • Evaluate data sources for quality, relevance, and reliability to ensure accurate insights. 
  • Construct dashboards and KPI hierarchies that provide decision-ready intelligence. 
  • Apply predictive models to anticipate trends, risks, and customer behaviours. 
  • Deploy prescriptive analytics to optimise decisions. 
  • Translate complex analytics outputs into clear, actionable business recommendations. 
  • Integrate analytics into functional areas to enhance performance. 
  • Measure the ROI and business impact of analytics initiatives, linking insights to growth and efficiency. 
  • Apply ethical and responsible analytics practices to ensure transparency, fairness, and trust. 

At a Glance

Course Duration:

April 7 - May 19, 2026

Times:

Tuesdays and Thursdays, 5:30 - 8:30 PM AST

Certificate Awarded:

Professional Development Certificate of Competence

Cost:

US $2,250.00
Register by January 7, 2026 and save 10%

Registration Deadline:

Modality:

Online

Contact Us Today


Direct Contacts

Wanda Monrose
wanda.monrose@uwi.edu

Additional Information

Programme Curriculum 

  • Foundations of Applied Business Analytics 
    • The Role of Analytics and AI in Competitive Advantage and Decision-Making 
    • Types of Analytics: Descriptive, Diagnostic, Predictive, Prescriptive 
    • Data Lifecycle: Collection, Cleaning, Governance, Integration 
    • Framing Business Problems into Analytics-Ready Questions 
  • Descriptive and Diagnostic Analytics: Seeing the Story in the Data 
    • Exploratory Data Analysis (EDA) for Commercial Insight 
    • KPI Hierarchies and Performance Metrics Alignment 
    • Dashboard Design for Executive Decision-Making 
    • Root Cause Analysis: Identifying Drivers of Business Outcomes 
    • Applications: Customer Segmentation, Sales Funnel Analysis, Financial Variance 
  • Predictive Analytics: Looking Ahead with Confidence 
    • Fundamentals of Predictive Modelling (Regression, Classification, Clustering) 
    • Forecasting Demand, Sales, and Operational Needs 
    • Churn Prediction and Customer Retention Strategies 
    • Marketing Mix Modelling and Campaign Forecasting 
    • Applied Tools in Predictive Applications 
  • Prescriptive Analytics: From Insight to Action 
    • Optimisation Models for Pricing, Promotions, and Allocation 
    • Simulation and Scenario Planning for Strategic Decisions 
    • Prescriptive Analytics in Resource Planning and Supply Chain 
    • Recommendation Engines: Personalisation and Product Adoption 
    • Connecting Prescriptive Insights to Measurable ROI 
  • Commercial Analytics in Practice 
    • Customer Lifetime Value (CLV) as a Growth Driver 
    • Marketing Attribution and Multi-Touch Journey Analytics 
    • Sales Productivity: Pipeline Health, Quota Attainment, and Velocity 
    • Product Usage and Adoption Analytics 
    • Linking Commercial Analytics to Financial Performance and Profitability 
  • Scaling Analytics Across the Enterprise 
    • Building the Analytics Operating Model (Centralised, Federated, Hybrid) 
    • Governance, Ethics, and Responsible AI in Analytics Deployment 
    • Upskilling Leaders for Analytics and AI Fluency and Cross-Functional Impact 
    • Measuring Business Value and Communicating Analytics ROI 

How You Will You Learn 

  • Instructor-Led Sessions: Expert facilitators will guide learners through key analytics concepts and applied frameworks. 
  • Case-Driven Learning: Analyse real-world business challenges to translate data into actionable insights. 
  • Hands-On Analytics Exercises: Work with sample datasets, predictive models, and dashboards using tools including Excel, Tableau, Power BI, Python, R, and SQL. 
  • AI-Enhanced Demonstrations: Explore how AI tools augment analytics and support smarter decision-making. 
  • Applied Scenario Simulations: Test analytics solutions in realistic business contexts to see immediate impact. 

 

What You Will Take Away 

  • Data-to-Decision Skills: Turn raw data into actionable insights that drive business outcomes. 
  • Analytics Fluency: Understand and apply descriptive, predictive, and prescriptive techniques. 
  • Decision-Ready Metrics: Build KPI hierarchies, dashboards, and performance indicators tied to objectives. 
  • Predictive and Prescriptive Playbooks: Apply models to anticipate trends, optimise decisions, and improve ROI. 
  • Commercial Insight Application: Use analytics to inform customer, sales, marketing, product, and financial strategies. 
  • Analytics Operating Knowledge: Design workflows, operating models, and governance frameworks for scale. 

Who Should Attend 

This programme is designed for professionals who want to leverage data to make smarter, faster, and more impactful decisions, including: 

  • Business leaders and managers responsible for strategic decision-making and who want to leverage analytics for growth, scaling and competitive positioning 
  • Professionals seeking to integrate analytics into operational and commercial processes 
  • Individuals looking to translate data into actionable insights for their teams or organisation 
  • Decision-makers who want to understand and apply descriptive, predictive, and prescriptive analytics 
  • Professionals aiming to lead data-driven initiatives and foster analytics adoption across teams 
  • Technology and data professionals who want to strengthen their ability to link analytics work with business strategy and impact 
  • Functional specialists looking to sharpen their analytics fluency within their domain 
  • Early- to mid-career professionals seeking to upskill and position themselves for leadership in data-driven roles 

All notification of cancellations, deferrals, and substitutions must be received in writing. Please submit your request via e-mail to schsbmopen@cavehill.uwi.edu

CANCELLATIONS

  • The Sagicor Cave Hill School of Business and Management (SCHSBM) reserves the right to make changes to any printed or online information on short courses, instructors, or course information; or cancel any short course due to under-subscription or circumstances beyond its control.
  • Delegates will be notified at least seven (7) days before the start of any course that must be cancelled.
  • Fees for short courses cancelled by the SCHSBM will be refunded in full.
  • The SCHSBM will not be liable for any loss, damages or other expenses that result from course cancellations.

REFUNDS

Due to the costs incurred for program preparation and administration any cancellations received 30 days or less from the program start date are subject to fees as described below. For programs with a virtual component, the start date will be considered the first day of live learning.

Written notice of cancellation received by SCHSBM Refund
30 days or more before the start of the specific course 100% of course fees.
29 to 15 days before the start of the specific course 50% of course fees.
14 days or less before the start of the specific course No refund

Sagicor Cave Hill School of Business and Management
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