Databilities®
Databilities® Framework
DTTP's proprietary framework for measuring, benchmarking, and developing workforce data literacy.
Databilities® is DTTP's proprietary data literacy competency framework. It defines role-based data literacy competencies, measures workforce capability, benchmarks results, and guides targeted capability development.
DEFINITION
Databilities® is DTTP's proprietary data literacy competency framework. It defines the competencies required to use data effectively, measures workforce capability against those competencies, benchmarks results, and supports continuous capability development.
Data literacy becomes valuable when people can apply data with judgment in the work they actually do.
Why It Matters
Organizations need a structured approach to data literacy, but DTTP's implementation is Databilities®. It provides a consistent competency model, assessment methodology, benchmarking capability, and development pathways that allow leaders to measure and improve workforce data literacy using evidence.
KEY CONCEPTS
The Databilities® Framework has seven connected domains.
1. Data awareness. Understand what data is, how it is created, why it matters, and how it supports organizational outcomes.
2. Data discovery. Find, access, interpret, and use relevant data sources, definitions, metadata, and context.
3. Data quality. Evaluate whether data is accurate, complete, timely, consistent, relevant, and fit for purpose.
4. Data analysis. Interpret trends, patterns, comparisons, relationships, uncertainty, and limitations using role-appropriate methods.
5. Data communication. Explain data clearly, communicate insights, use visualizations responsibly, and adapt messages to the audience and decision context.
6. Data-informed decision-making. Use data alongside judgment, ethics, experience, risk, and organizational context to make better decisions.
7. Data responsibility. Understand governance, privacy, security, ethical, and accountability requirements for appropriate data use.
benefits
Creates a shared definition of data literacy across the organization.
Clarifies role-based expectations for data capability and proficiency.
Improves assessment by measuring data literacy against defined competencies.
Supports targeted learning pathways instead of generic data training.
Strengthens AI readiness by improving data interpretation, judgment, and responsible use.
Enables benchmarking and continuous improvement of workforce data capability.
Treating data literacy as a dashboard or analytics tool training program.
Using the same data literacy expectations for every role.
Measuring course completion instead of data capability.
Ignoring data quality, governance, ethics, and decision context.
COMMON PITFALLS
FREQUENTLY ASKED QUESTIONS
What is the Databilities® framework?
A Databilities® framework is a structured model that defines data capabilities, how they vary by role, how they are measured, and how they should be developed.
What does the Databilities® framework include?
It includes data awareness, discovery, quality, analysis, communication, decision-making, responsibility, role-based proficiency levels, assessment evidence, and development pathways.
How is the Databilities® framework used?
Organizations use it to define expectations, assess current data literacy, identify gaps, design learning pathways, benchmark progress, and strengthen data-informed decision-making.