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Data analyst

Find out what a data analyst in government does and the skills you need to do the job at each level.

Last updated 30 August 2022 — See all updates

What a data analyst does

A data analyst collects, organises and studies data to provide business insight.

In this role, you will:

  • apply tools and techniques for data analysis and data visualisation (including the use of business information tools)
  • identify, collect and migrate data to and from a range of systems
  • manage, clean, abstract and aggregate data alongside a range of analytical studies on that data
  • manipulate and link different data sets
  • summarise and present data and conclusions in the most appropriate format for users

Data analyst role levels

There are 4 data analyst role levels, from associate analyst to principal data analyst.

The typical responsibilities and skills for each role level are described in the sections below. You can use this to identify the skills you need to progress in your career, or simply to learn more about each role in the Government Digital and Data profession.

1. Associate analyst

This role level is often performed at the Civil Service job grade of:

  • HEO (Higher Executive Officer)
Skill Description

Analysis and synthesis (data analyst)

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • show an awareness of the need for careful analysis of research data to produce clear findings

Communication

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • show an awareness of the need to translate technical concepts into non-technical language
  • understand what communication is required with internal and external stakeholders

Data management

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • show an awareness of organisational data governance, and how it works in relation to other organisational governance structures

Data modelling, cleansing and enrichment

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • show an awareness of different data models and tools, and understand when they could be used
  • show an awareness of industry-recognised data modelling patterns and standards

Data quality assurance, validation and linkage

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • understand basic data issues and can check that the data and analysis look right
  • understand the concept of data being fit for purpose
  • understand the context of the data
  • show that you know the right questions to ask, and apply a curious and analytical mindset when approaching a problem
  • perform data preparation and cleansing with guidance

Data visualisation

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • work under direction to use the most appropriate medium to visualise data to tell a story, relevant to the fully defined goals and able to be acted upon
  • present, communicate and disseminate analysis and recommendations appropriately, under direction

IT and mathematics

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • show an awareness of IT and mathematical skills
  • appreciate how they are applied in the environment

Logical and creative thinking

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • identify problems in databases, data processes, data products and services, with an understanding of the level of a problem (for example, strategic, tactical or operational)
  • contribute to the implementation of remedies and preventative measures

Project management

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • show an awareness of project management techniques, and an appreciation of how they are applied in the environment

Statistical methods and data analysis

Level: awareness

Awareness is the first of 4 ascending skill levels

You can:

  • understand the theoretical basis for applied practices
  • begin to apply the theory to practical examples

2. Data analyst

This role level is often performed at the Civil Service job grade of:

  • HEO (Higher Executive Officer)
  • SEO (Senior Executive Officer)
Skill Description

Analysis and synthesis (data analyst)

Level: working

Working is the second of 4 ascending skill levels

You can:

  • understand how to apply basic techniques for the analysis of research data and synthesis of findings
  • effectively involve your team in analysis and synthesis
  • present clear findings that colleagues can understand and use

Communication

Level: working

Working is the second of 4 ascending skill levels

You can:

  • communicate effectively with technical and non-technical stakeholders
  • support and host discussions within a multidisciplinary team, with potentially difficult dynamics
  • be an advocate for the team externally, and can manage differing perspectives

Data management

Level: working

Working is the second of 4 ascending skill levels

You can:

  • understand data governance and how it works in relation to other organisational governance structures
  • participate in or deliver the assurance of a service

Data modelling, cleansing and enrichment

Level: working

Working is the second of 4 ascending skill levels

You can:

  • produce data models and understand where to use different types of data models
  • understand different tools and can compare different data models
  • reverse-engineer a data model from a live system
  • understand industry-recognised data modelling patterns and standards

Data quality assurance, validation and linkage

Level: working

Working is the second of 4 ascending skill levels

You can:

  • identify appropriate ways to collect, collate and prepare data
  • decide if data is accurate and fit for purpose
  • prepare and cleanse data with limited guidance

Data visualisation

Level: working

Working is the second of 4 ascending skill levels

You can:

  • use the most appropriate medium to visualise data to tell compelling stories that are relevant to business goals and can be acted upon
  • present, communicate and disseminate data appropriately and with influence

IT and mathematics

Level: working

Working is the second of 4 ascending skill levels

You can:

  • apply your knowledge and experience of IT and mathematical skills, including tools and techniques
  • adopt those most appropriate for the environment

Logical and creative thinking

Level: working

Working is the second of 4 ascending skill levels

You can:

  • respond to problems in databases, data processes, data products and services as they occur
  • initiate actions, monitor services and identify trends to resolve problems
  • determine the appropriate remedy and assist with its implementation, and with preventative measures

Project management

Level: working

Working is the second of 4 ascending skill levels

You can:

  • apply your knowledge and experience of project management methodologies, including tools and techniques
  • adopt those most appropriate for the environment

Statistical methods and data analysis

Level: working

Working is the second of 4 ascending skill levels

You can:

  • understand how and when to practically apply existing best practice solutions

3. Senior data analyst

This role level is often performed at the Civil Service job grade of:

  • SEO (Senior Executive Officer)
  • G7 (Grade 7)
Skill Description

Analysis and synthesis (data analyst)

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • understand and help teams to apply a range of methods to analyse research data and synthesise findings
  • effectively engage sceptical colleagues in analysis and synthesis
  • advise on the choice and application of techniques, and can critique colleagues’ findings to assure best practice

Communication

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • listen to the needs of technical and business stakeholders, and interpret them
  • effectively manage stakeholder expectations
  • manage active and reactive communication
  • support or host difficult discussions within the team or with diverse senior stakeholders

Data management

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • advocate data governance and data management standards and guidelines within your team’s products and services
  • continually communicate and improve data management practices in your teams
  • help define and support the use of common toolsets
  • seek to automate data management activities where possible
  • develop processes to enable good data management practices and compliance with data governance policies

Data modelling, cleansing and enrichment

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • build and review complex data models, ensuring adherence to standards
  • use data integration tools and languages to integrate and store data, and advise teams on best practice
  • ensure data for analysis meets data quality standards and is interoperable with other data sets, enabling reuse
  • work with other data professionals to improve modelling and integration patterns and standards

Data quality assurance, validation and linkage

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • set up a system to get data ready for use and specify how data should be cleansed and prepared
  • bring data together from different sources
  • communicate the limitations of data
  • peer review colleagues’ outputs to ensure quality

Data visualisation

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • demonstrate skill in a number of data visualisation tools and techniques
  • apply standards and best practices to present, communicate and disseminate data appropriately and with influence
  • review, advise and support more junior members, and establish processes, standards and templates for others to follow, improving the efficiency and quality of visualisations

IT and mathematics

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • share your knowledge and experience of IT and mathematical skills with others, including tools and techniques
  • define those most appropriate for the environment

Logical and creative thinking

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • ensure that the most appropriate actions are taken to resolve problems as they occur
  • co-ordinate teams to resolve problems and implement solutions and preventative measures

Project management

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • share knowledge and experience of project management methodologies with others, including tools and techniques
  • define those most appropriate for the environment
  • oversee projects within a data analytics team

Statistical methods and data analysis

Level: practitioner

Practitioner is the third of 4 ascending skill levels

You can:

  • understand and apply a range of practices
  • develop deeper expertise in a narrower range of specialisms
  • start to apply emerging theory to practical situations

4. Principal data analyst

This role level is often performed at the Civil Service job grade of:

  • G7 (Grade 7)
  • G6 (Grade 6)
Skill Description

Analysis and synthesis (data analyst)

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • help an organisation to adopt a wide range of analysis and synthesis techniques, and to continually assure, improve and innovate their practices to generate clear and valuable findings

Communication

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • mediate between people and mend relationships, communicating with stakeholders at all levels
  • manage stakeholder expectations and moderate discussions about high risk and complexity, even within constrained timescales
  • speak on behalf of and represent the community to large audiences inside and outside of government

Data management

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • ensure data management and governance processes are in place and adhered to for the products and services your teams provide
  • ensure data management responsibilities are clearly defined and training is in place to enable the execution of data management practices
  • define strategies to enable continual improvement of data management practices and compliance with data governance policies

Data modelling, cleansing and enrichment

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • understand different ways to model data to maximise its use and value
  • ensure data is modelled appropriately, and modelling standards exist and are complied with
  • understand a number of data integration tools and patterns, and ensure your teams have the support and training needed to use the most appropriate methods
  • build relationships with other senior data professionals (in fields such as data architecture, data engineering and data science) to share best practice and continually improve data modelling and integration processes and standards

Data quality assurance, validation and linkage

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • show a deep understanding of relevant data sources, tools and systems
  • use appropriate approaches for verifying and validating data and analysis
  • influence senior stakeholders in data approaches
  • coach and mentor others

Data visualisation

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • set the strategy to enable your teams to produce effective and influential visualisations
  • ensure adherence to organisation-wide standards and guidelines, and suggest appropriate ways to improve them
  • ensure your team has the training, skills and support required to produce high quality data visualisations that are insightful and can be acted upon
  • implement feedback gathering to support continuous improvement

IT and mathematics

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • demonstrate knowledge and experience of the application of IT and mathematical skills
  • be a recognised specialist and adviser in these skills, including relating to user needs, generation of ideas, methods, tools, and leading or guiding others in best practice

Logical and creative thinking

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • anticipate problems and know how to prevent them
  • understand how problems fit into the larger picture
  • describe problems and help others to do so
  • build problem-solving capabilities in others

Project management

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • demonstrate knowledge and experience of the application of project management methodologies
  • be a recognised specialist and adviser in project management, including user needs, generation of ideas, methods and tools, and leading or guiding others in best practice
  • oversee projects within a data analytics team

Statistical methods and data analysis

Level: expert

Expert is the fourth of 4 ascending skill levels

You can:

  • understand, teach and supervise a wide range of practices, or may have deep expertise in a narrower range of specialisms
  • apply emerging theory to practical situations
Role Shared skills
Data governance manager

Data management

Updates

Published 7 January 2020

Last updated 30 August 2022

30 August 2022

  • There are updated skill descriptions at practitioner and expert level for 'data management', 'data modelling, cleansing and enrichment' and 'data visualisation'. These skills apply to the senior data analyst and principal data analyst role levels. The ‘analytical and problem-solving skills’ skill has been renamed ‘analysis and synthesis (data analyst)’ to ensure consistency across the DDaT Profession Capability Framework.

7 January 2020

  • First published.