Data analyst

You can:

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

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

You can:

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

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

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

You can:

• describe how to choose the most appropriate medium to visualise data to tell compelling stories
• present, communicate and disseminate data appropriately, with supervision

You can:

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

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

You can:

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

You can:

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

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

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

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

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

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

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

You can:

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

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

You can:

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

You can:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Communicating between the technical and non-technical

Data modelling, cleansing and enrichment

Communicating between the technical and non-technical

Data management

Communicating between the technical and non-technical

Communicating between the technical and non-technical

Communicating between the technical and non-technical