Programme purpose
Learning designed for immediate organisational application.
A hands-on workshop for converting scattered ESG spreadsheets into consistent datasets, meaningful metrics and decision-ready dashboards. Participants use Excel, Power Query and Power BI Desktop to clean and reconcile data, create a practical reporting model, calculate indicators and build a traceable management dashboard. Exercises focus on repeatable reporting and evidence quality rather than decorative charts or unsupported sustainability scores.
Available datesChoose the session that works for you.
Detailed two-day curriculumSix modules, practical exercises and workplace-ready outputs.
The programme moves from core concepts to guided application. Every major module includes focused submodules and a practical exercise.
Day 1Preparing reliable ESG data and a workable reporting model
Module 1 — Defining the reporting question and dataset
- Dashboard users, decision questions and meaningful ESG indicators
- Metric definitions, organisational boundaries, time periods, units and source evidence
- Data dictionaries, ownership, identifiers and the difference between missing values and zero
Practical application: Design a minimum viable ESG dataset and reporting brief for a fictional branch network.
Module 2 — Excel and Power Query for controlled data preparation
- Structured tables, input conventions and basic validation controls
- Combining files, shaping columns, correcting types and standardising units
- Duplicate checks, exception logs, control totals and repeatable transformation steps
Practical application: Clean and consolidate supplied site workbooks, documenting rejected records and reconciliation checks.
Module 3 — Building the Power BI data model
- Fact and dimension tables, a calendar table and stable identifiers
- Relationships, filter direction and avoiding double counting
- Model documentation, source lineage and separation of raw and transformed data
Practical application: Build and validate a multi-site ESG model against the supplied control totals.
Daily participant outputA cleaned practice dataset, data dictionary, transformation log and validated Power BI model.
Day 2Measures, dashboards and repeatable reporting controls
Module 4 — Practical DAX and ESG performance measures
- Measures versus calculated columns; SUM, DIVIDE, CALCULATE and filter context
- Trends, year-to-date values, target variance and meaningful intensity ratios
- Boundary consistency, denominator choices and checking calculation results
Practical application: Create and independently validate a small set of environmental and workforce measures.
Module 5 — Designing useful ESG dashboards
- Choosing charts for trends, comparisons, targets and exceptions
- Slicers, drill-through, tooltips and accessible visual design
- Narrative context, outliers and avoiding misleading scales or unsupported composite ratings
Practical application: Build a management dashboard and a separate data-quality exception page.
Module 6 — Validation, refresh and workplace implementation
- Reconciliation, metric-owner review and evidence retention
- Refresh planning, change control and an overview of service access and sharing considerations
- Integrating a dashboard with reporting workflows and governed systems such as ESG360
Practical application: Present a capstone dashboard, explain its limitations and prepare a 30-day application plan.
Daily participant outputA working practice dashboard, validation checklist, refresh plan and individual implementation roadmap.
Who should attendDesigned for the people responsible for delivery.
- ESG and sustainability officers responsible for metrics and reporting
- Data analysts, business-intelligence teams and reporting specialists
- Finance, HR, Operations, HSE and Procurement data owners
- Branch-network and multi-site reporting coordinators
- Internal control and audit staff reviewing spreadsheet-based ESG information
Learning outcomesWhat participants will be able to do.
- Design an ESG data dictionary with metric definitions, boundaries, units, owners and evidence requirements
- Clean and combine multi-site Excel datasets using repeatable Power Query steps
- Create a practical Power BI data model with a date table and appropriate relationships
- Build and validate core DAX measures for trends, intensity indicators and target tracking
- Produce an accessible management dashboard with reconciliation and exception views
- Document a refresh, access and evidence-control process for recurring ESG reporting
Participant resourcesPractical take-away tools.
- Synthetic Nigerian multi-site ESG practice dataset
- ESG data dictionary and metric-owner template
- Power Query cleaning and reconciliation checklist
- Worked Power BI model and core DAX measure examples
- Dashboard design, validation and accessibility checklist
- Refresh schedule, change log and 30-day workplace application plan
Before you attendPreparation and prerequisites.
- Confident use of Excel tables, formulas and basic charts; introductory ESG knowledge is recommended
- Bring a Windows laptop with a supported Power BI Desktop installation and an Excel version supporting Power Query; Mac users need access to a suitable Windows environment
- Install software before the workshop. Any paid Microsoft software or Power BI service sharing licences are arranged separately; they are not implied by course participation
- Use supplied synthetic or appropriately anonymised data; do not upload confidential organisational information to public tools
Practical casesRelevant scenarios for applied learning.
- Fictional Lagos-based manufacturer: combining electricity, fuel, water and waste data from several sites with different units
- Fictional branch network: validating headcount, training, customer inclusion and reporting completeness across locations
- Capstone: produce a management dashboard that separates missing data from zero performance and links exceptions to accountable owners
A CENGSSUD training certificate records participation. It is not an IFRS Foundation, IAASB or Microsoft qualification, accreditation or licence to practise.
Reference resourcesPrimary learning references.
Learning methodologyTechnical instruction translated into practical action.
Facilitator demonstration is followed by supervised laptop practice, short problem-solving sprints and a capstone dashboard clinic. Participants use supplied synthetic data, compare results with control totals and explain the evidence behind their charts. Power BI service deployment is discussed separately from the Desktop exercises.
Secure your place or train your organisation.
Register an individual participant, book a corporate cohort or request a tailored in-house version aligned with your sector and implementation priorities.