BUSINESS ANALYTICS FOR DATA-DRIVEN DECISION MAKING
Transforming Data into Strategic Insights and Competitive Advantage
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Course Schedule
| Date | Venue | Fees (Face-to-Face) |
|---|---|---|
| 06 – 10 Oct 2025 | Dubai, UAE | USD 3495 per delegate |
Course Introduction
In today’s digital economy, data is a vital asset—but only when properly analyzed and interpreted. Business analytics empowers professionals to extract meaningful insights from data, enabling smarter decisions, optimized processes, and competitive performance.
This hands-on course provides participants with the essential analytical tools and frameworks to analyze data effectively and make decisions based on facts, not guesswork. Covering descriptive, diagnostic, predictive, and prescriptive analytics, the course bridges data science techniques with real-world business applications.
Course Objectives
By the end of this course, participants will be able to:
• Understand the business analytics lifecycle and its role in decision-making
• Use Excel and modern analytics tools to perform descriptive and predictive analysis
• Translate business problems into data analysis questions
• Visualize and communicate insights effectively to stakeholders
• Integrate analytics into business processes and strategic planning
Key Benefits of Attending
• Learn data analysis techniques even without a technical background
• Master practical tools such as Excel, pivot tables, dashboards, and data models
• Discover how to turn business challenges into data questions and insights
• Make decisions with greater confidence and clarity
• Support your organization’s digital transformation with analytical thinking
Intended Audience
This program is designed for:
• Business managers and team leaders
• Finance, HR, marketing, and operations professionals
• Business analysts and strategy consultants
• Project managers and decision-makers seeking to apply data analysis
• Anyone involved in reporting, forecasting, or performance evaluation
Individual Benefits
Key competencies that will be developed include:
• Data literacy and interpretation skills
• Excel-based business analytics techniques
• Ability to evaluate trends, outliers, and performance metrics
• Confidence in presenting data stories and dashboards
• Decision-making based on empirical evidence
Organization Benefits
Upon completing the training course, participants will demonstrate:
• Improved decision-making and reduced reliance on intuition
• Faster identification of risks, opportunities, and inefficiencies
• More consistent, data-supported business planning and forecasting
• Stronger cross-functional collaboration through shared metrics
• Enhanced performance monitoring across departments
Instructional Methdology
The course follows a blended learning approach combining theory with practice:
• Strategy Briefings – Core business analytics models and use cases
• Case Studies – Real-world business decisions informed by analytics
• Workshops – Hands-on Excel analysis and dashboard building
• Peer Exchange – Data challenges and discussion across functions
• Tools – Excel templates, KPI calculators, visualization frameworks
Course Outline
Detailed 5-Day Course Outline
Training Hours: 7:30 AM – 3:30 PM
Daily Format: 3–4 Learning Modules | Coffee breaks: 09:30 & 11:15 | Lunch Buffet: 01:00 – 02:00
Day 1: Fundamentals of Business Analytics
Module 1: Introduction to Business Analytics (07:30 – 09:30)
• Types of analytics: descriptive, diagnostic, predictive, prescriptive
• Business analytics vs. business intelligence
• Overview of analytics lifecycle
Module 2: Data Types, Sources, and Structures (09:45 – 11:15)
• Structured and unstructured data
• Internal vs. external data sources
• Basic database concepts for non-technical professionals
Module 3: Excel as a Business Analytics Tool (11:30 – 01:00)
• Data importing, cleaning, and validation
• Pivot tables and conditional formatting
• Best practices in spreadsheet modeling
Module 4: Workshop – Descriptive Analytics in Excel (02:00 – 03:30)
• Hands-on analysis using historical business data
• Generating performance summaries and trend visualizations
Day 2: Diagnostic Analytics and Data Interpretation
Module 1: Exploring Relationships and Patterns (07:30 – 09:30)
• Correlation, outliers, and variability
• Slicing and filtering data to answer key questions
Module 2: Root Cause Analysis Techniques (09:45 – 11:15)
• Fishbone diagrams and Pareto analysis
• Data-driven problem solving
Module 3: Business KPI Development (11:30 – 01:00)
• Selecting and defining meaningful metrics
• Linking KPIs to business objectives and outcomes
Module 4: Workshop – Diagnostic Dashboards (02:00 – 03:30)
• Creating interactive Excel dashboards
• Data storytelling and insight presentation
Day 3: Predictive Analytics and Forecasting
Module 1: Introduction to Predictive Techniques (07:30 – 09:30)
• Regression analysis and time-series forecasting basics
• Recognizing patterns and projecting trends
Module 2: Forecasting Models in Excel (09:45 – 11:15)
• Moving averages and exponential smoothing
• Scenario and sensitivity analysis
Module 3: Predictive Use Cases in Business (11:30 – 01:00)
• Demand planning, budgeting, and customer behavior prediction
• Understanding model limitations and assumptions
Module 4: Workshop – Forecasting Simulation (02:00 – 03:30)
• Building and validating forecasts
• Evaluating model accuracy
Day 4: Prescriptive Analytics and Data-Driven Decisions
Module 1: Decision Models and Optimization (07:30 – 09:30)
• Decision trees, what-if analysis, and goal seek
• Using Solver for business optimization problems
Module 2: Data-Driven Strategy and Planning (09:45 – 11:15)
• Applying analytics to strategic decision-making
• Allocating resources and prioritizing actions
Module 3: Performance Monitoring and Alerts (11:30 – 01:00)
• Setting data thresholds and alert systems
• Building KPI trackers and scorecards
Module 4: Workshop – Business Decision Scenario (02:00 – 03:30)
• Group challenge: solving a business problem using analytics
• Presentation of findings and decisions
Day 5: Integration, Implementation & Certification
Module 1: Embedding Analytics in the Organization (07:30 – 09:30)
• Analytics maturity models and governance
• Overcoming resistance and building data culture
Module 2: Final Project – Business Analytics Plan (09:45 – 11:15)
• Team presentations of analytics insights and strategies
• Peer critique and instructor feedback
Module 3: Knowledge Review & Certification Exam (11:30 – 01:00)
• Multiple-choice and practical application questions
• Reflection and Q&A
Module 4: Wrap-Up & Personal Action Planning (02:00 – 03:30)
• Applying insights to current job roles
• Certificate distribution and course closure
Certification
Participants will receive a Certificate of Completion in Business Analytics for Data-Driven Decision Making, recognizing their ability to apply analytical techniques and tools for effective business performance and strategic decision-making.