About the Course

Organizations often possess large volumes of operational, financial, programme and customer data but struggle to convert it into timely decisions. Generative AI and modern analytics tools can accelerate data preparation, exploratory analysis, visualization, narrative explanation and decision support, especially for professionals who are not full-time data scientists. However, AI-assisted analytics must be grounded in sound data practices and verified quantitative reasoning.

This course develops practical capability to use AI as an analytics copilot. Participants work with spreadsheets, tabular data and visualization tools to support data cleaning, formula generation, descriptive analysis, segmentation, trend analysis, scenario exploration, dashboard design, narrative insight and decision briefs. Where appropriate, exercises can incorporate Excel, Power BI and generative AI tools available to the client.

The programme emphasizes verification of calculations, reproducibility, source traceability and decision relevance. Participants develop an AI-assisted analysis workflow, cleaned dataset, analytical prompt library, dashboard specification, insight narrative and decision brief that can be adapted to workplace reporting and management processes.

Target Participants

The course is suitable for data analysts, M&E professionals, finance staff, planners, project managers, operations teams, business analysts, programme officers, managers, researchers and professionals who use spreadsheets, dashboards or business data to support decisions.

What You Will Learn

By the end of this course the participants will be able to:

• Prepare and structure data for AI-assisted analysis.
• Use AI to support spreadsheet formulas, data cleaning and exploratory analysis.
• Apply AI-assisted methods for descriptive analysis, segmentation and trend interpretation.
• Develop visualization and dashboard specifications for decision support.
• Generate evidence-based narratives from analytical outputs.
• Verify AI-assisted calculations and identify unsupported interpretations.
• Design repeatable analytics prompts and quality-control checks.
• Produce a management decision brief using AI-assisted analysis.

Course Duration

• Classroom – 5 Days
• Online – 7 Days

Course Outline

Decision Intelligence Foundations

• From reporting to decision intelligence
• Role of AI in analytics workflows
• Analytical questions and decision context
• Quantitative reasoning limitations
• Human validation responsibilities

Data Preparation

• Data structure and tidy-data concepts
• Missing-value identification
• Duplicate and consistency checks
• Category standardization
• Documenting data-cleaning decisions

Spreadsheet Copilot

• Formula generation support
• Formula explanation and debugging
• Lookup and aggregation assistance
• Data-validation rules
• Spreadsheet quality checks

Exploratory Analysis

• Descriptive statistics
• Distribution interpretation
• Outlier review
• Cross-tabulation support
• Question generation from datasets

Trend Analysis

• Time-series pattern review
• Growth and variance calculations
• Seasonality identification
• Comparative trend interpretation
• Avoiding false causal explanations

Segmentation

• Grouping and classification concepts
• Customer or beneficiary segmentation
• Performance-band creation
• Risk-tier analysis
• Interpreting segment differences

Visualization Design

• Choosing appropriate chart types
• Visual hierarchy and clarity
• Dashboard layout principles
• AI-assisted chart commentary
• Avoiding misleading visualizations

Insight Generation

• Turning analysis into findings
• Evidence-to-insight logic
• Materiality and prioritization
• Alternative explanations
• Decision-relevant recommendations

Analytics Governance

• Data confidentiality
• Calculation verification
• Reproducibility and audit trail
• Source traceability
• Responsible use of AI-generated analysis

Decision Brief

• Executive question framing
• Key evidence selection
• Scenario and option comparison
• Decision narrative development
• Action-oriented management brief

Practical Outputs

• AI-assisted data-cleaning checklist
• Spreadsheet prompt library
• Exploratory analysis output
• Dashboard wireframe
• Insight-validation checklist
• Management decision brief

Training Approach

Participants work with structured datasets in guided labs. Demonstrations show how generative AI can support formulas, analysis, visualization design and narrative interpretation, followed by manual verification of calculations and claims. The final exercise integrates the analytical workflow into a concise management decision brief.

Organizational Benefits

• Faster preparation and exploration of organizational data
• Improved confidence using analytics in routine decisions
• Better quality of dashboards and management narratives
• Reduced errors through structured verification steps
• Greater accessibility of analytics for non-specialist professionals
• More consistent evidence-based decision support

Certification

Participants who successfully complete this course will receive a Certificate of Course Completion from Devimpact Institute, recognizing the knowledge, practical skills and competencies developed through the programme.

Tailor-Made Course

This course can be customized and delivered as an in-house programme to address the specific policies, systems, sector context and capacity-development priorities of an organization. The course duration, modules, case studies and practical exercises may be adjusted following a training needs assessment.