About the Course

Organizations increasingly collect sex-disaggregated and inclusion-related data, but the management value of that information depends on data quality, appropriate measures, sound analysis and clear communication. Gender data can be misleading when indicators are poorly defined, intersectional groups are obscured by averages, time-use and unpaid work are ignored, or dashboards present activity without revealing meaningful disparities.

This 10-day technical programme builds capability to prepare, analyse, visualize and communicate gender data using Excel, Power Query and Power BI. It integrates gender-statistics concepts, SDG and sector indicators, measurement bias, data-quality assessment, intersectional analysis, time-use and labour-market statistics, data transformation, descriptive analytics, dashboard modelling, visualization and evidence storytelling. The programme emphasizes responsible interpretation rather than software mechanics alone.

Participants work with realistic gender datasets and produce a cleaned analytical dataset, indicator dictionary, gender-gap analysis, intersectional analysis, Excel analytical model, Power Query workflow, Power BI data model and management dashboard. These outputs can be adapted for programme monitoring, policy analysis, management reporting and evidence-based decision-making.

Target Participants

Gender-data specialists; statisticians; M&E professionals; policy analysts; researchers; government planning and statistics staff; development practitioners; data analysts; consultants and professionals responsible for gender evidence, SDG reporting or policy analysis.

Course Duration

• Classroom – 10 Days
• Online – 14 Days

Course Objectives

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

• Assess gender data requirements for policy and programme decisions.
• Identify appropriate administrative, survey, and other gender-data sources.
• Diagnose data gaps, measurement bias and quality limitations.
• Construct and interpret gender indicators and gap measures.
• Prepare and clean gender datasets for analysis.
• Conduct intersectional and subgroup analysis.
• Analyse selected gender topics using appropriate statistical summaries.
• Develop clear gender-data visualizations and dashboards.
• Communicate gender evidence responsibly to decision-makers.
• Produce an integrated gender analytics output and evidence brief.

Course Content

Foundations of Gender Statistics and Data

• Gender data concepts
• Sex versus gender variables
• Gender indicators
• Demand and use of gender statistics
• Gender data needs assessment

Sources of Gender Data and Statistics

• Household surveys
• Administrative data
• Population and housing censuses as sources of gender statistics
• Facility and programme data
• Source assessment matrix

Gender-Related SDG Indicators and Measurement

• Gender-related SDGs
• Indicator metadata
• Numerators and denominators
• Disaggregation requirements
• Indicator computation exercise

Bias and Measurement Error in Gender Data

• Question design bias
• Proxy respondents
• Underreporting and disclosure bias in sensitive gender data
• Sampling bias
• Bias diagnostic

Quality Assessment of Gender Data

• Completeness of gender-disaggregated datasets and indicator records
• Consistency of gender data across sources, periods and definitions
• Timeliness of gender data for programme and policy decisions
• Comparability of gender data across populations, locations and time periods
• Data quality assessment

Preparing Gender Data for Analysis

• Data structure
• Cleaning rules
• Missing values
• Recoding and derived variables
• Cleaning lab

Analysing Gender Gaps and Disparities

• Rates and proportions
• Absolute versus relative gaps
• Ratios and indexes
• Trend analysis
• Gender-gap analysis

Intersectional Analysis of Gender Data

• Age and location
• Disability and socioeconomic status
• Education and employment
• Multiple-disadvantage profiles
• Intersectional cross-tabulation

Time-Use Statistics and Unpaid Care Analysis

• Paid and unpaid work
• Care-work measurement
• Time-use diaries
• Interpretation issues
• Time-use analysis exercise

Measuring Gender-Based Violence through Statistics

• Prevalence concepts
• Ethical measurement
• Disclosure and underreporting
• Indicator interpretation
• Violence-data interpretation case

Gender Analysis of Labour Market Statistics

• Labour-force participation
• Employment quality
• Occupational segregation
• Pay gaps
• Labour gender profile

 Gender Data for Management Decision-Making

• Policy questions
• Benchmarking gender performance against targets, peers and reference populations
• Trend diagnostics
• Priority identification
• Decision-analysis matrix

Visualizing Gender Data for Decision-Makers

• Chart selection
• Gender gap visuals
• Intersectional visuals
• Dashboard design
• Power BI/Excel dashboard lab

Storytelling with Gender Data and Evidence

• Evidence narratives
• Uncertainty and caveats
• Audience tailoring
• Avoiding harmful representation
• Gender evidence brief

Integrated Gender Analytics Capstone

• Integrated dataset
• Indicator dashboard
• Gap diagnosis
• Policy implications
• Gender analytics presentation

Gender Data Analysis Using Excel

• Structured tables and analytical formulas
• PivotTables and gender-disaggregated summaries
• Conditional logic for indicator calculation
• Trend and variance analysis
• Development of an Excel gender-analysis model

Preparing Gender Data with Power Query

• Importing and combining source files
• Data-type and quality controls
• Reshaping and unpivoting data
• Repeatable transformation workflows
• Development of a refreshable Power Query process

Building Gender Dashboards in Power BI

• Data-model relationships
• Measures and KPI calculations
• Interactive filters and disaggregation
• Accessible dashboard design
• Development and presentation of a gender dashboard

Practical Outputs

• Gender data-quality assessment
• Gender indicator dictionary
• Clean analytical dataset
• Excel gender-analysis model
• Intersectional analysis output
• Power Query transformation workflow
• Power BI gender dashboard
• Executive evidence brief

Training Approach

The programme is delivered as a guided analytics laboratory combining short technical inputs with hands-on work in Excel, Power Query and Power BI. Participants clean and reshape gender datasets, construct indicators, test disaggregation choices, perform gap and trend analysis, build data models and create management-ready visualizations. Gender-statistics concepts and data ethics are integrated into each software exercise so analytical judgement develops alongside technical proficiency.

A progressive capstone uses one realistic dataset across the programme. Participants move from data-quality assessment to analysis and dashboard development, then present findings to a simulated management audience and receive peer/facilitator review on analytical validity, visual clarity, and decision usefulness.

Organizational Benefits

• Improves institutional gender-data literacy and analytical capability.
• Strengthens quality of gender indicators and reporting.
• Improves identification of hidden inequalities through intersectional analysis.
• Supports more evidence-based policy and programme decisions.
• Builds internal dashboard and data-communication capability.
• Improves recognition and management of gender-data bias and quality issues.

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.

Customization Options

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.