Course Overview

Data Analytics for SDGs Monitoring is a comprehensive professional training program designed to equip policymakers, statisticians, researchers, monitoring and evaluation specialists, development practitioners, government officials, data analysts, and program managers with advanced skills in collecting, managing, analyzing, and reporting data for monitoring progress toward the United Nations Sustainable Development Goals (SDGs). As countries and organizations increasingly prioritize SDG Monitoring, Sustainable Development Data Analytics, SDG Indicators, Development Data Management, Results-Based Monitoring, Evidence-Based Policymaking, Development Analytics, Data-Driven Decision Making, Sustainable Development Reporting, and SDG Performance Measurement, there is a growing demand for professionals who can transform complex development data into actionable insights. This course provides participants with practical expertise in applying analytics to measure, track, and accelerate sustainable development outcomes.

The training explores the complete SDG monitoring lifecycle, including indicator selection, data collection, data quality assessment, statistical analysis, visualization, dashboard development, reporting, and policy evaluation. Participants will learn how to monitor progress across the 17 SDGs, assess development trends, identify implementation gaps, and support strategic interventions through data-driven insights. The course combines theoretical foundations with practical applications using real-world national, regional, and global SDG datasets.

Participants will gain hands-on experience in SDG indicator frameworks, data integration, statistical analysis, GIS and geospatial analytics, predictive modeling, dashboard design, impact assessment, and performance reporting. The course emphasizes transparency, accountability, inclusiveness, data quality, sustainability, and evidence-based development planning. Through practical exercises and case studies, participants will develop confidence in designing and implementing SDG monitoring systems that support national development agendas and international reporting obligations.

The training further addresses emerging trends in sustainable development analytics, including artificial intelligence for SDG monitoring, big data analytics, citizen-generated data, remote sensing applications, real-time development intelligence, digital monitoring platforms, climate and sustainability analytics, integrated development information systems, and advanced forecasting tools. Participants will develop competencies required to strengthen SDG reporting, improve resource allocation, enhance policy effectiveness, and support the achievement of sustainable development goals.

Course Objectives

1. Understand the principles and frameworks of SDG monitoring and evaluation.

2. Develop and manage SDG indicators and performance measurement systems.

3. Collect, integrate, and manage data from multiple SDG-related sources.

4. Apply statistical and analytical techniques to monitor SDG progress.

5. Utilize GIS and geospatial tools for SDG mapping and spatial analysis.

6. Design dashboards and visualization tools for SDG reporting.

7. Conduct SDG performance assessments and gap analyses.

8. Support evidence-based policy development and sustainable planning.

9. Improve national and organizational SDG reporting capabilities.

10. Apply emerging technologies to enhance SDG monitoring and analytics.

Organizational Benefits

1. Improved capacity to monitor and report SDG progress.

2. Enhanced evidence-based development planning and policymaking.

3. Better identification of development gaps and priority areas.

4. Improved transparency and accountability in development programs.

5. Enhanced data quality and management systems.

6. Stronger alignment with national and international development frameworks.

7. Improved resource allocation and program effectiveness.

8. Enhanced monitoring and evaluation capabilities.

9. Better stakeholder communication through data-driven reporting.

10. Increased institutional capacity to support sustainable development initiatives.

Target Participants

· Government planners and policymakers

· National statistics office personnel

· Monitoring and Evaluation (M&E) specialists

· Development practitioners and project managers

· Researchers and academic professionals

· Data analysts and statisticians

· International development organization staff

· NGO and civil society professionals

· SDG coordinators and reporting officers

· Public sector performance managers

· GIS and geospatial specialists

· Anyone involved in sustainable development planning, monitoring, and reporting

Course Outline

Module 1: Introduction to Sustainable Development Goals and Data Analytics

1. Overview of the 2030 Agenda for Sustainable Development

2. Understanding the 17 Sustainable Development Goals

3. SDG monitoring and reporting frameworks

4. Role of data analytics in sustainable development

5. National and global SDG monitoring systems

6. Emerging trends in SDG analytics

Case Study:
Developing a national SDG monitoring framework to support evidence-based development planning.

Module 2: SDG Indicators and Performance Measurement

1. SDG indicator framework and classifications

2. Global and national indicator systems

3. Indicator selection and adaptation

4. Performance measurement methodologies

5. Indicator metadata development

6. SDG benchmarking techniques

Case Study:
Designing a performance measurement system for tracking progress toward multiple SDGs.

Module 3: SDG Data Sources and Management

1. Official statistics and administrative data

2. Survey and census data integration

3. Open data and international development databases

4. Data governance and management frameworks

5. Data quality assurance techniques

6. Metadata standards and documentation

Case Study:
Building an integrated SDG data repository using multiple national and international data sources.

Module 4: Statistical Analysis for SDG Monitoring

1. Descriptive statistics for SDG indicators

2. Trend analysis methodologies

3. Comparative and benchmarking analysis

4. Development performance measurement

5. Data interpretation techniques

6. Statistical reporting for SDGs

Case Study:
Analyzing poverty, education, and health indicators to assess SDG progress.

Module 5: Data Integration and Interoperability

1. Multi-source data integration strategies

2. Data harmonization techniques

3. Interoperability frameworks

4. Data warehousing for SDG monitoring

5. Managing large-scale development datasets

6. Data exchange standards

Case Study:
Integrating survey, census, and administrative datasets for comprehensive SDG analysis.

Module 6: GIS and Geospatial Analytics for SDGs

1. GIS fundamentals for sustainable development

2. Spatial mapping of SDG indicators

3. Geographic disparities and inequality analysis

4. Remote sensing applications for SDGs

5. Geospatial decision-support systems

6. Spatial visualization and reporting

Case Study:
Mapping regional disparities in access to health, education, and infrastructure services.

Module 7: Monitoring and Evaluation for Sustainable Development

1. Results-based monitoring frameworks

2. SDG evaluation methodologies

3. Outcome and impact assessment techniques

4. Theory of Change applications

5. Learning and adaptive management

6. Performance review mechanisms

Case Study:
Evaluating the effectiveness of a development program aligned with SDG targets.

Module 8: Predictive Analytics and Forecasting for SDGs

1. Predictive analytics concepts

2. Forecasting development indicators

3. Scenario planning and modeling

4. Risk assessment methodologies

5. Development trend projections

6. Decision-support analytics

Case Study:
Forecasting progress toward SDG targets under different policy intervention scenarios.

Module 9: Dashboards, Data Visualization, and Reporting

1. SDG dashboard design principles

2. Data visualization techniques

3. Interactive reporting platforms

4. Executive and stakeholder reporting

5. Storytelling with development data

6. Communicating SDG progress effectively

Case Study:
Developing an SDG dashboard to monitor national development performance in real time.

Module 10: Artificial Intelligence and Big Data for SDG Monitoring

1. AI applications in sustainable development

2. Machine learning for indicator analysis

3. Big data and alternative data sources

4. Citizen-generated data applications

5. Automated monitoring systems

6. Ethical considerations in AI-driven development analytics

Case Study:
Using AI and big data analytics to improve SDG monitoring and development forecasting.

Module 11: Institutional Frameworks and Governance for SDG Data Systems

1. SDG governance and coordination mechanisms

2. National statistical systems strengthening

3. Multi-stakeholder data partnerships

4. Data sharing and collaboration frameworks

5. Institutional capacity development

6. Sustainable data ecosystem planning

Case Study:
Establishing a national SDG data governance framework to improve coordination and reporting.

Module 12: Strategic SDG Intelligence and Future Trends

1. Integrated SDG intelligence ecosystems

2. Sustainable development decision-support systems

3. Climate and sustainability analytics

4. Future trends in SDG monitoring

5. Building data-driven development institutions

6. Strategic roadmap for SDG data transformation

Case Study:
Designing an integrated SDG monitoring and analytics ecosystem that combines official statistics, administrative databases, GIS platforms, remote sensing technologies, AI-powered forecasting models, performance dashboards, monitoring and evaluation systems, citizen-generated data sources, policy analytics tools, and decision-support frameworks to improve sustainable development planning, resource allocation, accountability, SDG reporting, policy effectiveness, and achievement of the 2030 Agenda for Sustainable Development.

Essential Information

Our courses are customizable to suit the specific needs of participants.
Participants are required to have proficiency in the English language.
Our training sessions feature comprehensive guidance through presentations, practical exercises, web-based tutorials, and collaborative group activities. Our facilitators boast extensive expertise, each with over a decade of experience.
Upon fulfilling the training requirements, participants will receive a prestigious Global King Project Management certificate.
Training sessions are conducted at various Global King Project Management Centers, including locations in Nairobi, Mombasa, Kigali, Dubai, Lagos, and others.
Organizations sending more than two participants from the same entity are eligible for a generous 20% discount.
The duration of our courses is adaptable, and the curriculum can be adjusted to accommodate any number of days.
To ensure seamless preparation, payment is expected before the commencement of training, facilitated through the Global King Project Management account.
For inquiries, reach out to us via email at training@globalkingprojectmanagement.org or by phone at +254 114 830 889.
Additional amenities such as tablets and laptops are available upon request for an extra fee. The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a certificate of successful completion. Participants are responsible for arranging and covering their travel expenses, including airport transfers, visa applications, dinners, health insurance, and any other personal expenses.

Data Analytics for SDGs Monitoring Training Course