Data analytics DAAN

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

Revision notes

Updates for SFIA 9

This is a new skill introduced in SFIA 9.
Theme(s) influencing the updates for this new skill: Continued refinement for data and analytics skills.
Previous SFIA assessments or skills mapping of other SFIA skills may be impacted by this new skill. See also Data science and Business intelligence

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
ensuring the validity and integrity of data being processed and analysed
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 good 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 responsibilities.

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 who are performing higher level tasks and activities

Where higher levels are not defined...

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

Click to learn why SFIA skills are not defined at all 7 levels.

Show/hide extra descriptions and levels.

Levels of responsibility for this skill

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, patterns and insights that inform business decisions.

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

Data analytics: Level 4

Level 4 - Enable: Essence of the level: Performs diverse complex activities, supports and guides others, delegates tasks when appropriate, 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 delivering significant work outcomes, from analysis through execution to evaluation.

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

Leads the implementation of data analytics solutions. 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.

Data analytics: Level 6

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

Develops organisational strategies and roadmaps for data analytics.

Sets policies, standards and recommended 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 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.

New skill