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Research and Data Analysis
Data Literacy for Non-Analysts in Research Teams Training Course
Introduction
In today’s data-driven research environments, data literacy is no longer a skill reserved for analysts and data scientists. Non-analyst professionals—from project managers and administrators to subject-matter experts—must understand how to interpret, manage, and communicate data effectively. Data Literacy for Non-Analysts in Research Teams Training Course empowers participants with essential data skills, enabling them to contribute meaningfully to evidence-based decisions, data storytelling, and collaborative analysis within interdisciplinary research teams.
This hands-on, interactive training is tailored for professionals who work closely with data but lack formal training in data analysis. By leveraging real-world research case studies and user-friendly data tools, the course demystifies concepts like data quality, visualization, data ethics, and interpretation. Participants will gain confidence in understanding datasets, identifying patterns, questioning findings, and communicating insights with clarity and purpose.
Programme Curriculum
Data Literacy for Non-Analysts in Research Teams Training Course
Introduction
In today’s data-driven research environments, data literacy is no longer a skill reserved for analysts and data scientists. Non-analyst professionals—from project managers and administrators to subject-matter experts—must understand how to interpret, manage, and communicate data effectively. Data Literacy for Non-Analysts in Research Teams Training Course empowers participants with essential data skills, enabling them to contribute meaningfully to evidence-based decisions, data storytelling, and collaborative analysis within interdisciplinary research teams.
This hands-on, interactive training is tailored for professionals who work closely with data but lack formal training in data analysis. By leveraging real-world research case studies and user-friendly data tools, the course demystifies concepts like data quality, visualization, data ethics, and interpretation. Participants will gain confidence in understanding datasets, identifying patterns, questioning findings, and communicating insights with clarity and purpose.
Course Objectives
Understand foundational data literacy concepts in a research context.
Identify relevant datasets and assess data quality for non-technical users.
Develop skills to interpret basic data visualizations and statistical summaries.
Use data storytelling techniques to enhance communication in research teams.
Recognize common data pitfalls and misinterpretations.
Explore data ethics, privacy, and compliance in research projects.
Collaborate effectively with analysts and technical experts using data-informed dialogue.
Apply Excel and online tools for non-complex data analysis and reporting.
Understand the role of metadata and documentation in research datasets.
Evaluate the impact of data literacy on research outcomes and credibility.
Translate research findings into actionable recommendations using data.
Engage in critical thinking and questioning when presented with data.
Empower non-analysts to take a proactive role in data governance and usage.
Target Audience
Research project managers
Public health workers
Academic researchers without data backgrounds
Policy analysts
NGO staff involved in research programs
Program coordinators and administrators
Nonprofit communication officers
Undergraduate and graduate students in research roles
Course Duration: 5 days
Course Modules
Module 1: Introduction to Data Literacy in Research
What is data literacy?
Importance of data understanding for non-analysts
Components of a data-literate research team
Common myths about working with data
Key terminology explained in simple terms
Case Study: Miscommunication in a Public Health Study
Module 2: Understanding Research Data
Types of data: qualitative vs. quantitative
Identifying relevant and reliable datasets
Reading basic dataset structures
Introduction to metadata and documentation
Recognizing data limitations
Case Study: Educational Research Dataset Evaluation
Module 3: Basic Data Analysis for Non-Analysts
Introduction to descriptive statistics (mean, median, mode)
Exploring frequency tables and cross-tabulations
Using Excel for simple calculations
Recognizing outliers and anomalies
Making sense of numerical findings
Case Study: Survey Results in Community Research
Module 4: Visualizing Data for Insight
Introduction to charts: bar, pie, line, scatter plots
Choosing the right visualization
Data dashboards for quick understanding
Identifying misleading visuals
Creating visuals using Excel and Canva
Case Study: Presenting Research Findings to Stakeholders
Module 5: Data Ethics and Compliance
Principles of ethical data usage
Data privacy laws and research protocols
Informed consent and data usage
Understanding bias in data collection
Responsible sharing and storage of data
Case Study: Data Breach in a Clinical Research Project
Module 6: Collaborating with Analysts
Understanding analyst roles and tools
Framing research questions for data analysis
How to read and comment on analysis reports
Providing feedback without technical jargon
Building mutual respect in cross-functional teams
Case Study: Communication Gap in Environmental Study
Module 7: Communicating with Data
Data storytelling frameworks (e.g., What-So What-Now What)
Tailoring data stories to your audience
Using analogies to explain data insights
Avoiding technical overload in presentations
Enhancing message retention with visuals and narratives
Case Study: Convincing Funders with Data Stories
Module 8: Applying Data Literacy in Research Workflows
Integrating data literacy into everyday tasks
Building data review habits
Asking the right questions during meetings
Using checklists and templates for consistency
Advocating for better data practices in teams
Case Study: Embedding Data Review in Proposal Writing
Training Methodology
Interactive workshops with practical exercises
Hands-on tool demonstrations using Excel and Canva
Real-world case studies and group discussions
Downloadable templates and checklists
Knowledge checks and feedback loops
Register as a group from 3 participants for a Discount
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 FINESKILL TRAINING CENTER account, as indicated in the invoice so as to enable us prepare better for you.