About the Course
Organizations increasingly expect people outside analytics teams to demonstrate data literacy in everyday reporting, planning, and problem solving. That means you need to read charts accurately, distinguish trend from noise, question the source of a metric, understand basic data quality checks, and explain what the numbers mean in a business context. This course is aligned with practical data literacy expectations drawn from approaches such as MIT Sloan’s four-part view of reading, working with, analyzing, and arguing with data, and it draws on the kind of persona-based assessment and learning-path design described in enterprise data literacy programs.
The course turns scattered spreadsheet habits into a structured working method. You will practice cleaning and organizing data in Excel and Google Sheets, build simple summaries with formulas and pivot tables, interpret visualizations and summary statistics, apply a data quality checklist, and draft a concise insight note for managers. What you will learn: you will learn to assess your current data literacy baseline, use spreadsheet tools to prepare and explore data, and communicate findings in a form that supports decisions. In practical terms, you will practice hands-on data cleaning, chart reading, and basic analysis, while being introduced at overview level to program design ideas such as skills-gap assessment, persona mapping, and learning metrics for wider organizational adoption.
This course is built for professionals who need usable results under real constraints such as limited time, mixed data quality, and competing reporting demands. It is especially relevant when teams must produce reliable dashboards, monthly reviews, and management updates without depending entirely on data specialists. You will work with realistic business examples so the course stays practical for people who need to deliver accuracy, clarity, and speed in the same workflow.
Target Audience
This Data Literacy Training Course is designed for professionals who need to interpret, question, and present data in everyday business settings. It fits roles that rely on reports, dashboards, spreadsheets, and management summaries to make defensible decisions.
- Project Coordinator reviewing operational KPI packs and status reports
- Operations Supervisor tracking performance trends and exception data
- HR Business Partner interpreting workforce dashboards and headcount metrics
- Finance Officer validating budget reports and variance summaries
- Business Analyst translating business questions into spreadsheet analysis
- Procurement Specialist reviewing supplier performance and spend reports
- Customer Service Team Lead monitoring service metrics and escalation trends
- Sales Operations Analyst cleaning pipeline data and forecasting inputs
- Quality Assurance Specialist checking defect trends and root-cause charts
- Department Manager presenting monthly results to leadership
Course Objectives
This course equips you to read, clean, analyze, and report data initiatives that improve decision quality, support accurate reporting, and strengthen evidence-based communication.
- Assess your current data literacy baseline using a persona-based skills map and spreadsheet diagnostic.
- Apply data cleaning techniques in Excel and Google Sheets to improve dataset reliability.
- Design a simple data interpretation checklist for charts, tables, and summary statistics.
- Build a pivot-table summary and chart pack for operational reporting.
- Calculate key metrics such as averages, percentages, variances, and trend changes from business data.
- Evaluate data quality issues using completeness, consistency, and accuracy checks.
- Implement a repeatable workflow for reviewing dashboards and validating source data before reporting.
- Synthesize findings into a concise insight brief for managers using clear data narratives.
Requirements & Prerequisites
Prerequisites: no coding is required, but you should have everyday experience using spreadsheets and business reports. A working knowledge of Excel or Google Sheets, the ability to read basic charts, and access to a laptop during class will help you complete the exercises. This is an intermediate course, so you should already be comfortable entering data, sorting simple tables, and using basic formulas such as SUM and AVERAGE.
Recommended preparation: bring a recent report, dashboard screenshot, or spreadsheet from your role so you can apply the exercises to a familiar dataset. Participants who regularly review performance dashboards, KPI packs, or operational reports will gain the most from the hands-on exercises.
Local Application and Business Return in Trinidad and Tobago
How participants can apply the training in local operating conditions, and the return their organisation can plan for.
How participants apply this
Expected ROI
Training Methodology
This is a practical, outcome-driven course designed to turn data literacy aspiration into measurable action and credible reporting.
Methodology includes:
- Hands-on calculation using variance, percentage change, and summary statistics in Excel datasets.
- Scenario simulation on a management report review with missing and conflicting KPI values.
- Assessment exercise using a data quality checklist based on completeness, accuracy, and consistency.
- Stakeholder mapping of report owners, dashboard users, and decision-makers in the reporting chain.
- Case study analysis from finance, operations, HR analytics, and customer service reporting contexts.
- Group workshop to produce a one-page insight brief within a fixed time and data scope.
- Reflection exercise comparing current reporting habits against persona-based data literacy benchmarks.
Upcoming Sessions
Next available dates worldwide
No international sessions scheduled
Certification
Recognized credentials that advance your career
Participants who complete the Data Literacy for Non-Data Professionals Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Effective Learning & Skill Development
- Build expertise with structured, outcome-driven learning.
- Equip individuals and teams with skills that grow with industry needs.
- Reinforce learning through real-world scenarios, case studies and practical exercises.
Career Growth & Professional Advancement
- Apply what you learn with a proven methodology that ensures lasting impact.
- Develop immediately usable skills that translate directly into workplace success.
- Gain the expertise needed for career advancement and leadership roles.
Training Optimization & Learning Excellence
- Tailor training to industry-specific challenges and organizational goals.
- Use data-driven insights and automation to enhance training effectiveness.
- Evaluate progress and ensure long-term learning success.
Tools and platforms relevant to this field
Examples Trinidad and Tobago teams may encounter, and that may be featured in training where they support the confirmed course scope.
These are field-relevant examples, not a promise that every tool will be covered. Exact coverage depends on the confirmed course scope, participant needs, and delivery format.
-
Microsoft Excel MicrosoftUsed for cleaning, summarising, checking formulas, and building simple charts that non-data professionals can maintain.
-
Google Sheets GoogleUsed for collaborative reporting, lightweight analysis, and shared working files when teams need real-time editing.
-
Power BI MicrosoftUsed to review dashboards, compare measures consistently, and turn operational data into visuals that managers can scan quickly.
