Data for Sustainable Development Goals (SDGs) Reporting Training Course

Data for Sustainable Development Goals (SDGs) Reporting Training Course

Introduction

In the age of global transformation, high-quality, timely, and reliable data plays a pivotal role in measuring progress and implementing effective policies aligned with the United Nations Sustainable Development Goals (SDGs). Data for SDGs Reporting Training Course is designed to equip researchers, data analysts, policymakers, and development professionals with practical tools and techniques to collect, analyze, and report data that reflect true progress on the SDGs. Leveraging modern data science, data governance frameworks, and international reporting standards, this course promotes data literacy and enhances the capacity to drive data-informed decision-making for sustainable development.

Participants will gain cutting-edge skills in SDG indicator analysis, data visualization, big data integration, and policy impact reporting. By integrating real-world case studies, advanced research methodologies, and open-source tools, learners will be able to build sustainable data ecosystems and contribute to national and global SDG monitoring. This hands-on training fosters collaboration between statisticians, researchers, civil society, and government institutions to ensure inclusive and evidence-based SDG reporting.

Course Objectives

Participants will be able to:

1. Understand the global framework and significance of SDG data reporting.
2. Analyze the 232 UN-approved SDG indicators using quantitative and qualitative approaches.
3. Apply data science tools for monitoring and evaluating SDG progress.
4. Utilize geospatial data for regional and national SDG insights.
5. Explore big data applications in sustainable development tracking.
6. Create compelling data visualizations and SDG dashboards.
7. Leverage open data platforms for SDG research and analytics.
8. Develop country-specific SDG reporting strategies aligned with global standards.
9. Assess data gaps and propose robust data governance models.
10. Evaluate the role of academia in national and global SDG tracking.
11. Build evidence-based policy reports driven by disaggregated data.
12. Apply ethical principles in SDG data collection and use.
13. Collaborate with stakeholders for participatory SDG reporting.

Target Audiences

1. Government statisticians and policy analysts
2. UN agencies and international organizations
3. Academic researchers and students
4. NGO and civil society data specialists
5. Environmental data and climate change experts
6. ICT and data science professionals
7. Development economists and planners
8. Private sector professionals in ESG and sustainability

Course Duration: 5 days

Course Modules

Module 1: Introduction to the SDGs and Data Ecosystem

• Overview of the 2030 Agenda
• Understanding SDG indicators
• Data availability and data gaps
• Role of National Statistical Systems
• Stakeholder mapping and engagement
• Case Study: Kenya’s SDG Indicator Framework

Module 2: SDG Indicator Methodologies and Classifications

• Tier classification system of SDG indicators
• Statistical standards and metadata
• Disaggregation requirements
• Country-specific adaptations
• Integration with national development plans
• Case Study: India’s National Indicator Framework

Module 3: Data Collection Techniques for SDG Monitoring

• Household surveys and census data
• Administrative data sources
• Remote sensing and geospatial data
• Citizen-generated data
• Mobile and real-time data collection
• Case Study: Using DHS and MICS for SDG 3 in Sub-Saharan Africa

Module 4: Data Analysis Tools and Techniques

• Descriptive and inferential statistics
• SDG data trend analysis
• Multivariate and regression analysis
• Data quality assurance protocols
• Gender-sensitive and inclusive data analysis
• Case Study: Analyzing SDG 5 using STATA and SPSS

Module 5: Big Data and Emerging Technologies in SDG Tracking

• Role of AI and machine learning in SDG reporting
• Satellite imagery for environmental monitoring
• Internet of Things (IoT) for SDG 6 and 11
• Blockchain for data traceability
• Risks and opportunities of big data
• Case Study: Big Data Analytics in Monitoring SDG 13 (Climate Action)

Module 6: Data Visualization and SDG Dashboards

• Principles of effective data visualization
• Tools: Power BI, Tableau, Google Data Studio
• Creating interactive dashboards
• Storytelling with data
• Dashboard customization for policy use
• Case Study: Africa SDG Dashboard (Africa SDG Index)

Module 7: Policy Reporting and Impact Communication

• Writing data-driven SDG reports
• Aligning with Voluntary National Review (VNR) templates
• Policy briefs and impact narratives
• Communicating data to non-technical audiences
• Ensuring transparency and accountability
• Case Study: Norway’s VNR and public SDG portal

Module 8: Building Sustainable Data Systems

• SDG data governance and coordination
• Financing SDG data ecosystems
• Partnerships for sustainable data
• Capacity building and institutional strengthening
• Open-source tools and open data platforms
• Case Study: Rwanda’s National SDG Monitoring System

Training Methodology

• Instructor-led live sessions
• Interactive group discussions
• Case study-based learning
• Hands-on practical exercises and assignments
• Quizzes, peer reviews, and final project presentation

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.