Foundation Certificate in Business Analytics

FOUNDATION CERTIFICATE IN BUSINESS ANALYTICS

 

INTRODUCTION

 

The Foundation Certificate in Business Analytics provides learners with the essential knowledge and practical skills to turn data into meaningful insights that support smarter business decisions. Through a hands-on approach, the course introduces data preparation, analysis, visualisation, and basic predictive techniques using real-world business scenarios. It is designed for beginners or professionals looking to develop data-driven decision-making skills and start their journey in the growing field of business analytics.

 

LEARNING OUTCOMES:

 

 By the end of this course, learners will be able to collect, clean, and analyse business data, apply statistical and visualisation techniques to uncover insights, build simple predictive and prescriptive models, and present data-driven recommendations using industry tools.

Module 1: Introduction to Business Analytics

  • What is Business Analytics and why it matters
  • Difference between Business Analysis and Business Analytics
  • Types of analytics:
    • Descriptive (what happened?)
    • Diagnostic (why did it happen?)
    • Predictive (what will happen?)
    • Prescriptive (what should we do?)
  • Role of a Business Analyst vs Business Analytics professional

 

Module 2: Data Fundamentals

  • Data types: structured, semi-structured, unstructured
  • Sources of business data (CRM, ERP, web, IoT, social media)
  • Basics of databases (SQL overview)
  • Data governance, ethics, and GDPR considerations

 

Module 3: Data Preparation & Cleaning

  • Importance of clean and reliable data
  • Common issues: missing values, duplicates, outliers
  • Data wrangling techniques (Excel, Python, R, Power Query)
  • Case study: preparing a sales dataset for analysis

 

Module 4: Exploratory Data Analysis (EDA)

  • Descriptive statistics (mean, median, mode, variance, correlation)
  • Data visualisation techniques (charts, histograms, dashboards)
  • Identifying trends and patterns
  • Tools: Excel, Power BI, Tableau

 

Module 5: Predictive Analytics

  • Basics of forecasting and regression models
  • Introduction to classification techniques (decision trees, logistic regression)
  • Business applications: sales forecasting, churn prediction, risk analysis
  • Case study with a sample dataset

 

Module 6: Prescriptive Analytics & Decision-Making

  • “What-if” analysis and scenario planning
  • Optimisation models for decision-making
  • Simulations in business contexts (inventory, supply chain, staffing)
  • Example: resource allocation using Excel Solver/other tools

 

Module 7: Business Analytics in Practice

  • Case studies:
    • Retail (customer behaviour & segmentation)
    • Finance (fraud detection, credit scoring)
    • Healthcare (patient data analytics)
  • Introduction to AI and machine learning in analytics
  • Building a career in Business Analytics

Assessment Structure:

 

Practical Case Study Project

 

 

 

 

 

 

 

                                            

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