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Quest Training

Data Literacy Program Design and Measurement Training Course

Shows HR, L&D and data office leads how to design and measure a data literacy program with skills frameworks, role-based learning paths and data champions.

DOPS · Data & AI Operating ModelsAll Levels#3036ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Sectors:Data, Analytics & Digital TransformationCategories:Data & AI Operating Models

Course Overview

This practical course shows how to design, launch and measure an organization-wide data literacy program, moving beyond data literacy as a stated goal of the data strategy to a structured program with defined skills, target audiences, learning paths and measurable results. It is built for the HR, learning and development, data office and transformation teams who are asked to turn that goal into a working capability-building plan. Participants will examine what data literacy means for different roles, from staff who read reports to managers who make decisions with data and specialists who produce analysis. The course covers building a data literacy skills framework with proficiency levels, assessing current literacy, segmenting the workforce into learner personas and designing role-based learning paths that combine formal training, on-the-job practice and peer learning. The program also addresses the human side of adoption: building and sustaining a network of data champions, engaging executive sponsors and line managers, creating communities of practice and communicating the program in ways that reduce anxiety about data and analytics. Through practical workshops, participants will build a skills framework, map learning paths for priority roles, design a champions network and develop a measurement model that links literacy gains to data adoption, the use of data in decisions and business outcomes.

Learning Objectives

  • Define data literacy and its dimensions for different organizational roles.
  • Build the business case for a data literacy program linked to data strategy priorities.
  • Assess current data literacy levels, skills gaps and attitudes toward data.
  • Develop a data literacy skills framework with clear proficiency levels and observable behaviors.
  • Segment the workforce into learner personas based on how each role uses data.
  • Design role-based learning paths combining formal training, practice and peer learning.
  • Select learning formats that suit adult learners and use real work data.
  • Establish and sustain a network of data champions across business functions.
  • Engage executive sponsors and line managers in reinforcing data use at work.
  • Measure literacy progress and link it to data adoption and business outcomes.
  • Set up program governance and a phased rollout plan.

Who Should Attend

This course is designed for HR Managers, Learning and Development Managers, Talent and Capability Development Leads, Data Office Managers, Data Governance Leads, Digital Transformation Leads, Change Management Professionals, and Analytics Managers responsible for building data skills across the workforce. It is also suitable for organizational development specialists, internal academy managers, HR business partners, data stewards, and data champion coordinators in banks, oil and gas companies, government ministries and agencies, utilities, telecommunications companies, and healthcare administration. The program is particularly relevant to organizations that have included data literacy in their data strategy or national digital agenda and now need a structured, measurable program to deliver it, as well as organizations creating internal data academies for their staff.

Learning Outcomes

  • Explain data literacy and its role-specific dimensions in clear business terms.
  • Build a business case and charter for an organization-wide data literacy program.
  • Assess current data literacy, confidence and attitudes across the workforce.
  • Develop a skills framework with proficiency levels and observable behaviors.
  • Map target proficiency levels to job families and priority roles.
  • Define learner personas based on how each role uses data.
  • Design role-based learning paths using blended and work-based learning.
  • Set up and sustain an effective data champions network.
  • Engage sponsors and line managers to reinforce data use in daily work.
  • Measure literacy gains and link them to data adoption indicators.
  • Report program results to sponsors through clear performance measures.
  • Plan program governance, piloting and phased rollout across the organization.

Course Outline

Day 1

Data Literacy Foundations & Current-State Assessment

  • Defining data literacy: reading, analyzing and communicating data.
  • Data literacy versus digital skills, analytics skills and AI literacy.
  • Why literacy programs fail: one-off training and generic content.
  • Linking the program to data strategy and governance priorities.
  • Identifying stakeholders, sponsors and target populations.
  • Building the business case and defining program outcomes.
  • Assessment methods: surveys, self-assessment and practical tests.
  • Measuring attitudes, confidence and data culture alongside skills.
  • Practical Application: Design a data literacy assessment and draft a program charter.
Day 2

Data Literacy Skills Frameworks & Proficiency Levels

  • Purpose and structure of a data literacy skills framework.
  • Core competency areas: concepts, interpretation, analysis, ethics and communication.
  • Data quality awareness, privacy and responsible data handling.
  • Defining proficiency levels from awareness to expert.
  • Writing observable behaviors and indicators for each level.
  • Mapping target proficiency to job families and roles.
  • Aligning the framework with existing HR competency models.
  • Using the framework in recruitment and performance reviews.
  • Practical Application: Build a skills framework and map it to five priority roles.
Day 3

Role-Based Learning Paths & Program Design

  • Segmenting the workforce into learner personas by data use.
  • Paths for executives, managers, analysts and frontline staff.
  • Applying the 70-20-10 model to data skills development.
  • Blended learning: workshops, e-learning, microlearning and coaching.
  • Using the organization's own data and reports as learning content.
  • Sequencing paths and defining completion criteria.
  • Designing for adult learners and reducing data anxiety.
  • Setting up an internal data academy model.
  • Practical Application: Design learning paths for three learner personas.
Day 4

Data Champions, Communities of Practice & Adoption

  • Role and profile of data champions in business units.
  • Selecting, onboarding, developing and recognizing data champions.
  • Building communities of practice and peer learning forums.
  • Engaging executive sponsors and line managers as role models.
  • Program communication, identity and engagement campaigns.
  • Managing resistance and fear of exposing skill gaps.
  • Embedding data use into meetings, reports and routine decisions.
  • Coordinating champions with data stewards and the data office.
  • Practical Application: Design a data champions network with roles, selection criteria and activities.
Day 5

Measuring Data Literacy, Adoption & Program Governance

  • Building a measurement model for data literacy programs.
  • Applying the Kirkpatrick model to data skills training.
  • Measuring proficiency gains through repeat assessments.
  • Linking literacy to adoption: report usage and self-service analytics.
  • Measuring data use in decisions and business outcomes.
  • Designing a program dashboard for sponsors and the data office.
  • Program governance, roles, budget and resourcing.
  • Piloting, phased rollout and scaling.
  • Practical Application: Develop a measurement model and phased rollout plan for the program.

Upcoming Dates

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Kuala Lumpur · 18 – 22 Oct 2027 · Classroom

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BerlinScheduled
2 – 6 Nov 2026€5,800—
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CairoScheduled
8 – 12 Nov 2026€3,300—
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Cape TownScheduled
16 – 20 Nov 2026€5,100—
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CasablancaScheduled
16 – 20 Nov 2026€4,300—
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DammamScheduled
22 – 26 Nov 2026€4,200€3,780until 2 Nov
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DohaScheduled
29 Nov – 3 Dec 2026€4,400€3,960until 9 Nov
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DubaiScheduled
6 – 10 Dec 2026€4,400€3,960until 16 Nov
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ErbilScheduled
6 – 10 Dec 2026€3,100€2,790until 16 Nov
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IstanbulScheduled
14 – 18 Dec 2026€4,700€4,230until 23 Nov
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JeddahScheduled
20 – 24 Dec 2026€4,200€3,780until 30 Nov
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KigaliScheduled
21 – 25 Dec 2026€5,100€4,590until 30 Nov
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Kuala LumpurScheduled
28 Dec 2026 – 1 Jan 2027€4,400€3,960until 7 Dec
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LisbonScheduled
4 – 8 Jan 2027€5,400€4,860until 14 Dec
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LondonScheduled
4 – 8 Jan 2027€5,600€5,040until 14 Dec
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MadinahScheduled
11 – 15 Jan 2027€4,200€3,780until 21 Dec
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MadridScheduled
18 – 22 Jan 2027€5,400€4,860until 28 Dec
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MakkahScheduled
25 – 29 Jan 2027€4,200€3,780until 4 Jan
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ManamaScheduled
25 – 29 Jan 2027€4,700€4,230until 4 Jan
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MarbellaScheduled
1 – 5 Feb 2027€5,400€4,860until 11 Jan
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OnlineScheduled
7 – 11 Feb 2027€1,700€1,530until 18 Jan
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MuscatScheduled
8 – 12 Feb 2027€5,300€4,770until 18 Jan
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ParisScheduled
15 – 19 Feb 2027€5,700€5,130until 25 Jan
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AbujaScheduled
22 – 26 Feb 2027€5,100€4,590until 1 Feb
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SalalahScheduled
22 – 26 Feb 2027€5,300€4,770until 1 Feb
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AccraScheduled
1 – 5 Mar 2027€5,100€4,590until 8 Feb
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AmmanScheduled
7 – 11 Mar 2027€3,100€2,790until 15 Feb
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AmsterdamScheduled
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15 – 19 Mar 2027€6,100€5,490until 22 Feb
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22 – 26 Mar 2027€5,400€4,860until 1 Mar
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BeirutScheduled
28 Mar – 1 Apr 2027€4,000€3,600until 8 Mar
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Kuala LumpurScheduled
18 – 22 Oct 2027€4,400€3,960until 27 Sept
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