The global skills and competency framework for the digital world

Data analytics DAAN


Enabling data-driven decision making by extracting, analysing and communicating insights from structured and unstructured data.

SFIA 9 is in development

  • SFIA 9 beta due in early July 2024
  • SFIA 9 planned for publication October 2024

This is a prototype for SFIA 9. It is subject to change before publication.

Disclaimer - prototypes/new skills may be substantially modified prior to launch or may never be released.

Guidance notes


Data analytics focuses on delivering actionable insights from data to drive better decision making. 

Activities may include, but are not limited to:

  • collecting, processing, and analysing data from various sources
  • identifying trends, patterns, and insights using a range of analytical and statistical techniques
  • developing and validating predictive models
  • communicating findings to stakeholders
  • ensuring data quality, integrity, and governance
  • collaborating with teams to align analytics initiatives with business objectives
  • designing and implementing data analytics solutions and processes
  • providing actionable recommendations based on domain expertise
  • staying current with emerging trends and techniques in data analytics
  • strategic leadership for data analytics and related disciplines such as data science
  • contributing to data governance policies, standards, and best practices

Data analytics has diverse applications across industries, including customer segmentation, sales forecasting, fraud detection, supply chain optimisation, predictive maintenance, healthcare analytics, financial risk management, HR analytics, social media analytics, and public sector analytics.

Understanding the responsibility levels of this skill

Where lower levels are not defined...

  • Specific tasks and responsibilities are not defined because the skill requires a higher level of autonomy, influence, and complexity in decision-making than is typically expected at these levels. You can use the essence statements to understand the generic responsibilities associated with these levels.

Where higher levels are not defined...

  • Responsibilities and accountabilities are not defined because these higher levels involve strategic leadership and broader organisational influence that goes beyond the scope of this specific skill. See the essence statements.

Developing skills and demonstrating responsibilities related to this skill

The defined levels show the incremental progression in skills and reponsibilities.

Where lower levels are not defined...

You can develop your knowledge and support others who do have responsibility in this area by:

  • Learning key concepts and principles related to this skill and its impact on your role
  • Performing related skills (see the related SFIA skills)
  • Supporting others with tasks (generic examples are provided by the essence statements for each level)

Where higher levels are not defined...

  • You can progress by developing related skills which are better suited to higher levels of organisational leadership.


Defined at these levels: 2 3 4 5 6 7

Show/hide extra descriptions and levels.

Level 1

Level 1 - Follow: Essence of the level: Performs routine tasks under close supervision, follows instructions, and requires guidance to complete their work. Learns and applies basic skills and knowledge.

Data analytics: Level 2

Level 2 - Assist: Essence of the level: Provides assistance to others, works under routine supervision, and uses their discretion to address routine problems. Actively learns through training and on-the-job experiences.


Assists in data preparation and analysis activities under direction.

Processes and validates data to support analytics.

Generates standard reports and insights using established tools and methods.

Data analytics: Level 3

Level 3 - Apply: Essence of the level: Performs varied tasks, sometimes complex and non-routine, using standard methods and procedures. Works under general direction, exercises discretion, and manages own work within deadlines. Proactively enhances skills and impact in the workplace.


Supports data analytics by gathering and preparing data from multiple sources.

Applies analytical and statistical methods and software tools to analyse data and develop reports.

Assists in identifying trends and patterns that inform business decisions.

Collaborates with team members to refine analysis techniques and ensure data quality.

Data analytics: Level 4

Level 4 - Enable: Essence of the level: Performs diverse complex activities, supports and supervises others, works autonomously under general direction, and contributes expertise to deliver team objectives.


Conducts end-to-end data analysis, defining data requirements and ensuring data integrity.

Applies advanced analytical and statistical techniques to extract meaningful insights and develop predictive models.

Communicates complex findings to stakeholders in an understandable manner.

Contributes to the development of data analytics processes and standards. Identifies opportunities for improving data analytics practices.

Data analytics: Level 5

Level 5 - Ensure, advise: Essence of the level: Provides authoritative guidance in their field and works under broad direction. Accountable for achieving workgroup objectives and managing work from analysis to execution and evaluation.


Manages data analytics activities, establishing frameworks and methodologies aligned with business objectives and data governance policies.

Translates business needs into analytics requirements and identifies data-driven solutions.

Guides the selection and application of advanced analytical techniques.

Communicates insights and recommendations to senior stakeholders, influencing strategic decisions.

Leads the implementation of data analytics solutions.

Data analytics: Level 6

Level 6 - Initiate, influence: Essence of the level: Has significant organisational influence, makes high-level decisions, shapes policies, demonstrates leadership, fosters organizational collaboration, and accepts accountability in key areas.


Develops organisational strategies and roadmaps for data analytics.

Sets policies, standards, and best practices for the use of data and data analytical techniques. Leads initiatives to build data analytics capabilities and develop a data-driven culture.

Oversees the delivery of analytics projects and programmes. Promotes the ethical use of data and data analytics.

Data analytics: Level 7

Level 7 - Set strategy, inspire, mobilise: Essence of the level: Operates at the highest organisational level, determines overall organisational vision and strategy, and assumes accountability for overall success.


Directs the creation and review of a cross-functional, enterprise-wide approach and culture for generating value from data analytics and data science.

Drives the identification, evaluation and adoption of data analytics and data science capabilities to transform organisational performance. Leads the provision of the organisation’s data analytics and data science capabilities.

Ensures that the strategic application of data analytics and data science is embedded in the governance and leadership of the organisation.

Aligns business strategies, enterprise transformation and data analytics and data science strategies.

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