Monitoring and Evaluation Data Analytics using Power BI, STATA and R Course

Course Introduction

Monitoring and Evaluation (M&E) professionals are increasingly required to manage large volumes of data, generate evidence-based insights, and support decision-making through advanced analytical techniques. Traditional reporting methods are no longer sufficient in environments where stakeholders demand real-time information, predictive insights, impact measurement, and data-driven accountability. This course equips participants with advanced skills in data analytics for Monitoring and Evaluation using three of the most powerful analytical tools available today: Power BI, STATA, and R. Participants will learn how to transform raw data into meaningful intelligence that supports program improvement and organizational performance.

The growing emphasis on evidence-based management, results-based monitoring, and impact evaluation has created a strong demand for professionals who can analyze complex datasets and communicate findings effectively. Organizations implementing development programs, humanitarian interventions, public sector reforms, and corporate social responsibility initiatives require advanced analytical capabilities to monitor performance, assess outcomes, and measure impact. This course provides participants with practical competencies to conduct sophisticated data analysis and create actionable insights using industry-standard software platforms.

Power BI has emerged as one of the leading business intelligence and data visualization tools, enabling organizations to develop interactive dashboards, automate reporting processes, and monitor key performance indicators in real time. Participants will learn how to connect multiple data sources, build analytical models, design dynamic dashboards, and communicate monitoring and evaluation findings through compelling visualizations. The course emphasizes practical applications of Power BI within M&E environments and performance management systems.

STATA remains one of the most widely used statistical software packages in monitoring, evaluation, research, economics, public policy, and impact assessment. The course provides comprehensive training on data management, statistical analysis, hypothesis testing, regression modeling, impact evaluation techniques, and survey data analysis using STATA. Participants will gain practical experience conducting advanced analyses that support evidence generation, program evaluation, and policy development.

R has become a global standard for advanced analytics, machine learning, predictive modeling, and reproducible research. Through practical exercises, participants will learn how to use R for data cleaning, transformation, visualization, statistical modeling, impact evaluation, and predictive analytics. The course introduces participants to modern data science approaches that enhance monitoring and evaluation systems while supporting innovation and organizational learning.

By the end of this course, participants will possess advanced analytical skills that enable them to manage complex datasets, perform sophisticated statistical analyses, develop interactive dashboards, automate reporting processes, generate evidence for decision-making, and strengthen monitoring and evaluation systems. They will be equipped to leverage Power BI, STATA, and R as strategic tools for improving accountability, learning, performance measurement, and sustainable development outcomes.

Duration

10 days

Who Should Attend

• Monitoring and Evaluation Specialists
• MEL Managers and Advisors
• Data Analysts and Data Scientists
• Research and Evaluation Officers
• Program and Project Managers
• Results-Based Management Professionals
• Development Practitioners
• Public Policy Analysts
• NGO and INGO Technical Staff
• Government Planning Officers
• Impact Evaluation Specialists
• Statistical Officers
• Performance Measurement Professionals
• Learning and Knowledge Management Specialists

Course Objectives

• Develop advanced competencies in managing, analyzing, and interpreting monitoring and evaluation datasets effectively.
• Strengthen practical skills in using Power BI to create interactive dashboards and automated reporting systems.
• Build expertise in STATA for statistical analysis, hypothesis testing, impact evaluation, and survey data management.
• Enhance analytical capabilities using R for advanced data science, predictive analytics, and visualization techniques.
• Develop proficiency in cleaning, transforming, validating, and preparing datasets for rigorous analytical processes.
• Strengthen capacity to conduct descriptive, inferential, and multivariate statistical analyses using modern tools.
• Improve skills in designing performance monitoring systems supported by advanced analytical methodologies.
• Build competencies in impact evaluation techniques including regression analysis and causal inference approaches.
• Enhance ability to communicate analytical findings through effective visualizations and decision-support dashboards.
• Develop expertise in automating reporting processes and integrating multiple data sources into unified systems.
• Strengthen evidence-based decision-making through practical application of analytical methods and technologies.
• Build organizational capacity to utilize advanced analytics for performance improvement, accountability, and learning.

Course Outline

Module 1: Foundations of M&E Data Analytics

• Understanding the role of data analytics within modern monitoring and evaluation systems
• Exploring analytical frameworks that support evidence generation and organizational learning
• Examining key concepts in data management, performance measurement, and evaluation analytics
• Establishing analytical workflows that improve data quality and decision-making effectiveness

Module 2: Data Management and Preparation for Analytics

• Importing, organizing, cleaning, and validating datasets from multiple monitoring sources
• Identifying missing values, inconsistencies, and data quality issues affecting analysis outcomes
• Developing data management protocols that support reproducibility and analytical reliability
• Integrating datasets from surveys, administrative systems, and monitoring databases effectively

Module 3: Statistical Foundations for Monitoring and Evaluation

• Understanding descriptive statistics and measures of central tendency for performance analysis
• Applying probability concepts and statistical distributions within monitoring frameworks
• Conducting hypothesis testing and significance analysis for evidence-based conclusions
• Interpreting statistical outputs to support program performance and evaluation findings

Module 4: Introduction to Power BI for Monitoring and Evaluation

• Understanding Power BI architecture and its applications in monitoring and evaluation systems
• Connecting diverse data sources to create integrated analytical environments efficiently
• Building data models that support performance measurement and results tracking activities
• Designing foundational visualizations that communicate monitoring information effectively

Module 5: Advanced Power BI Dashboard Development

• Creating interactive dashboards for real-time monitoring and performance management systems
• Developing dynamic reports that support stakeholder engagement and strategic decision-making
• Utilizing advanced Power BI features including DAX calculations and analytical measures
• Automating reporting processes to improve efficiency and information accessibility

Module 6: Data Visualization and Storytelling with Power BI

• Applying visualization principles that improve interpretation of monitoring and evaluation findings
• Developing compelling data stories that communicate performance achievements and challenges
• Designing executive dashboards that support strategic oversight and governance requirements
• Enhancing stakeholder engagement through effective visual communication techniques

Module 7: STATA Fundamentals for M&E Professionals

• Navigating STATA environments and understanding statistical workflows for analytical projects
• Managing datasets and performing transformations using STATA data management tools
• Conducting exploratory data analysis to understand performance patterns and relationships
• Utilizing STATA commands for efficient data processing and analytical automation

Module 8: Advanced Statistical Analysis Using STATA

• Performing regression analysis to examine relationships between variables and outcomes
• Applying multivariate analytical techniques for comprehensive program performance assessment
• Conducting significance testing and advanced statistical procedures for evaluation studies
• Interpreting complex statistical outputs to support evidence-based recommendations

Module 9: Impact Evaluation Techniques Using STATA

• Applying quasi-experimental and experimental methods for impact assessment studies
• Conducting propensity score matching and difference-in-differences analytical approaches
• Measuring program effectiveness through rigorous causal inference methodologies
• Evaluating intervention outcomes using advanced econometric and statistical techniques

Module 10: Introduction to R Programming for M&E

• Understanding R programming environments and analytical workflows for evaluation projects
• Importing, managing, and transforming monitoring and evaluation datasets effectively
• Utilizing R packages designed for data analysis, visualization, and reporting applications
• Developing reproducible analytical scripts that improve transparency and efficiency

Module 11: Data Visualization and Reporting Using R

• Creating advanced visualizations that communicate analytical findings clearly and effectively
• Developing publication-quality charts, graphs, and analytical reports using R packages
• Automating reporting processes to streamline performance measurement activities
• Enhancing data communication through modern visualization and storytelling techniques

Module 12: Advanced Analytics and Modeling Using R

• Conducting predictive analytics to identify trends and forecast future performance outcomes
• Applying machine learning concepts within monitoring and evaluation analytical frameworks
• Utilizing advanced statistical models for complex evaluation and impact measurement studies
• Interpreting analytical outputs to support strategic planning and management decisions

Module 13: Integrating Power BI, STATA, and R

• Establishing integrated analytical workflows across multiple software environments efficiently
• Combining visualization, statistical analysis, and predictive modeling capabilities effectively
• Managing analytical projects that leverage complementary strengths of each platform
• Developing comprehensive evidence systems that support organizational learning objectives

Module 14: Performance Measurement and Indicator Analytics

• Analyzing performance indicators to assess progress toward strategic organizational goals
• Developing analytical frameworks for outcome measurement and impact assessment activities
• Measuring efficiency, effectiveness, sustainability, and organizational performance comprehensively
• Supporting adaptive management through continuous monitoring and analytical feedback systems

Module 15: Emerging Technologies and Advanced M&E Analytics

• Exploring artificial intelligence applications within monitoring and evaluation environments
• Utilizing predictive analytics and advanced modeling techniques for decision support
• Examining big data opportunities that strengthen evidence generation and performance management
• Leveraging digital innovations to improve monitoring, learning, and accountability systems

Module 16: Capstone Analytics Project and Practical Applications

• Designing comprehensive analytical projects addressing real-world monitoring challenges effectively
• Applying Power BI, STATA, and R tools within integrated performance measurement scenarios
• Developing actionable recommendations supported by rigorous analytical evidence and findings
• Presenting analytical outputs and dashboards to stakeholders for strategic decision-making

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.