Category Analyse, Use, Share

Level 1 - Foundation

• Is familiar with organisational data assets relevant to their work.
• Understands how those assets contribute value to the organisation.
• Actively looks for opportunities to use data to support decision making, advice and research.
• Uses insights from data to make informed, evidence-based decisions and recommendations, and act accordingly.

Level 2 - Intermediate

• Knows about various organisational data assets and understands their value to the organisation.
• Promotes opportunities for using data to support decision making, advice and research.
• Considers the broader environment and context when drawing or interpreting insights from data.

Level 3 - Advanced

• Has a comprehensive understanding of the data assets available to the organisation and understands how these assets contribute strategic value.
• Looks for new ways to obtain value from organisational data assets.
• Can advise how organisational data assets contribute value in broader data contexts.
• Has expert knowledge on the broader and strategic environment when drawing insights from data. Uses this expertise to make informed, evidence-based decisions and recommendations and acts accordingly.

Level 1 - Foundation

• Can develop and deliver a simple narrative to communicate insights related to their data.
• Can ask and answer a range of questions relating to their data, relevant to the audience.
• Can communicate effectively with a range of stakeholders during data production, management, or use.

Level 2 - Intermediate

• Can develop and deliver effective narrative to communicate insights drawn from a range of data sources and outputs.
• Can comfortably question data and results they are presented, and answer technical questions relating to their data, relevant to the audience.
• Can communicate effectively between technical and non-technical experts across data production, management, or use, including clients, managers and data professionals.
• Can effectively communicate the relationship between the data and the context in which it is used.

Level 3 - Advanced

• Can develop and deliver advanced level narrative to communicate insights drawn from complex data sources and outputs.
• Maintains understanding of new trends and innovations relating to data communication (including Artificial Intelligence-based technologies) and develops skills in these where relevant.
• Understands the importance of translating technical concepts into non-technical language and can adapt communication effectively for a range of audiences.
• Can use innovative approaches to improve the process of summarising data into meaningful narratives.
• Uses high quality analytics and visualisation to communicate insights from data.
• Can effectively listen to technical and business stakeholders and understand and interpret their data needs.

Level 1 - Foundation

• Can identify a successful process system or tool/process/product.
• Can identify deficiencies in current processes/systems or tools/products.
• Can support systems testing under guidance and following test plans.

Level 2 - Intermediate

• Can identify deficiencies in current processes/systems and tools/products, gain the required approval to make changes, and lead the implementation of those changes.
• Can identify and harness opportunities to create efficiencies and effective new processes/systems and tools/products.
• Can develop a test scenario and lead systems testing, following organisational procedures and protocols and analyse the results.

Level 3 - Advanced

• Thinks strategically to assess current processes/systems and tools/products across a broad context.
• Develops improvements where needed and encourages others to think critically about processes/systems and tools/products relevant to them.
• Advises those leading changes to processes/systems and tools/products, measures resultant benefits, and makes recommendations.
• Understands the impact of new trends and innovations on organisational data processes, systems and tools, and products.
• Maintains understanding of new trends and innovations relating to data processes, systems and tools, and products within the organisation and externally.
• Provides technical expertise for systems testing, including validating the quality of the testing approach and results.

Level 1 - Foundation

• Is aware of the data obtained from administrative sources and the use of administrative data.
• Knows where to obtain advice about administrative data sources and use as required.
• Understands what administrative data is, including its benefits and limitations.

Level 2 - Intermediate

• Is knowledgeable about various sources of administrative data and can explain their limitations.
• Can assess the utility of different sources of administrative data for a particular purpose.
• Has a strong understanding of the advantages and disadvantages of using administrative data, including in relation to survey data.
• Understands and can amend existing code (programming language) to source and combine administrative data.

Level 3 - Advanced

• Is knowledgeable about multiple sources of administrative data.
• Provides expertise to identify new sources of administrative data as well as uses for that data.
• Maintains understanding of new trends and innovations relating to sourcing of administrative data (including Artificial Intelligence-based technologies) and develops capabilities in hese where relevant.
• Can advise how the data has been used to produce new insights.
• Can write custom scripts and code (programming language) to source and combine administrative data.

Level 1 - Foundation

• Has a general understanding of the subject matter area associated with data use (for example, small business, healthcare, rural sector etc).

Level 2 - Intermediate

• Has knowledge of the subject matter area associated with the data use and can readily identify the parameters of the subject matter that influence the use of the data.

Level 3 - Advanced

• Has expertise on the subject matter area associated with data use, including understanding, and influencing the effective use of the data within that subject matter area and the relationship between that use and other data use contexts.

Level 1 - Foundation

• Can formulate research questions with guidance and consider the appropriate approaches and measures to resolve those questions.

Level 2 - Intermediate

• Can identify and structure relevant research questions for specific needs and develop the approach and specific measures to resolve those questions.

Level 3 - Advanced

• Uses a range of techniques to assess data needs and identify gaps, towards the formulation of appropriate research questions.

Level 1 - Foundation

• Is aware of the steps of the data output, product or data service and understands the decisions made at each of those steps.
• Knows where to obtain advice on data outputs, products and/or services as required.

Level 2 - Intermediate

• Is responsible for the production of a data output, product, or service.
• Can create data outputs or products and deliver data services in accordance with established processes and systems and can explain decisions made at all stages.

Level 3 - Advanced

• Has expert knowledge about the production of a data output, product or service.
• Provides expertise in developing new products or data services to meet evolving requirements, needs and opportunities.
• Can build the capability of others in the delivery of data outputs, products or services.

Level 1 - Foundation

• Understands the concept of data quality and its importance.
• Knows where to access data quality measures for the data they use.
• Can follow guidelines and procedures to determine the quality of data.

Level 2 - Intermediate

• Can describe and produce data quality measures for the outputs they produce.
• Can use knowledge of relevant data quality measures to make accurate assessment of data fitness for purpose.

Level 3 - Advanced

• Has expertise in the use of measures for data quality, the interaction of those measures, and their application in conjunction with one another.
• Can advise others on the use of data quality measures to make accurate assessments of data fitness for purpose.

Level 1 - Foundation

• Is familiar with statistical methodologies relevant for their work.
• Has a basic understanding of the concepts underpinning the statistical methods relevant to own work.

Level 2 - Intermediate

• Understands a range of statistical concepts, methods, and their application.
• Can explain the proper use of a range of statistical concepts and methodologies.

Level 3 - Advanced

• Has comprehensive understanding of a range of statistical concepts and methods and can advise on their proper use.
• Leads efforts to apply good statistical practice.
• Can build capability of others in understanding and applying statistical concepts and methods.
• Can understand and apply new or emerging methods

Level 1 - Foundation

• Can access and comply with data and information management principles and associated guidelines. This includes requirements relating to data access, data security, privacy and ethics.
• Knows where to obtain advice on the application of good data and information management practice.
• Knows what data is and how it can be used.

Level 2 - Intermediate

• Has knowledge of an organisation’s data and information management principles and guidelines.
• Can apply knowledge to support good data practice. This includes requirements relating to data access, data security, data disposal, privacy and ethics.

Level 3 - Advanced

• Can advise others on the proper application of data and information management concepts.
• Can advise others on the strategic use of data management good practice.
• Can implement and shape the organisation’s strategic use of data and information management good practice.
• If applicable, acts as a point of contact for data and information management leads in other organisations.
• Has expertise in implementing and shaping the organisation’s strategic use of data and information management good practice and can advise others. This includes requirements relating to data access, data security, data disposal, privacy and ethics.

Level 1 - Foundation

• Is aware of relevant data classifications and coding protocols, and their proper application to data in general.
• Knows who to consult for expert knowledge.

Level 2 - Intermediate

• Has a comprehensive knowledge of data classifications and coding protocols.
• Knows where to obtain expert advice about coding and classifications where needed.

Level 3 - Advanced

• Has expertise in data classifications and coding protocols and advises others.
• Can employ conceptual frameworks in support of data classification and coding.

Level 1 - Foundation

• Has a basic understanding of how data can be linked with other data.
• Understands what data integration is, including its benefits and limitations.
• Understands what types of data can be combined for analysis.

Level 2 - Intermediate

• Can perform data integration using standard tools and can implement quality controls.
• Knows where to obtain expert advice on data integration as needed.
• Is able to understand and amend existing code (programming language) to integrate data.
• Can assess datasets' suitability for linkage and extract appropriately prepared datasets.

Level 3 - Advanced

• Can perform and provide expert advice on data integration.
• Can build capability of others in understanding and applying good data integration practice and principles.
• Can write custom scripts and code (programming language) to integrate data.
• Maintains understanding of new trends and innovations relating to integrating data (including Artificial Intelligence-based technologies) and develops skills in these where relevant.

Level 1 - Foundation

• Understands there are different ways to summarise data and has a basic understanding of commonly used metadata options.
• Understands the concept of metadata, including its purpose and benefits.

Level 2 - Intermediate

• Can use various summary options to effectively describe data and explain and justify those choices.
• Follows organisational standards and procedures relating to metadata creation, storage, and use.
• Can access metadata and use the descriptors to better understand existing data and effectively use it.

Level 3 - Advanced

• Has expertise in metadata. Can establish standards for metadata and provide oversight and advice to others.
• Maintains knowledge of metadata best practice, including standards and applications.
• Can use a range of tools for storing and working with metadata. Keeps metadata refreshed and updated and can repair items that are incorrect or out of date.

Level 1 - Foundation

• Understands the data they work with can be used more widely and is aware of relevant data sharing legislation.
• Is familiar with basic data sharing guidelines and organisational procedures to support the re-use of their data by others.

Level 2 - Intermediate

• Understands and can articulate the value of data in terms of use and re-use.
• Implements a variety of techniques to ensure data is open and can be used beyond the specific purpose for which it was collected, in accordance with legislative requirements and organisational guidelines (includes data sharing legislation).
• Can advise others on approaches to make data re-usable.

Level 3 - Advanced

• Is a leading strategic adviser on the use of organisational data assets.
• Has expertise in the design and management of organisational data assets as open data. Promotes re-use and ongoing value of data across wider contexts, in accordance with legislative requirements and organisational guidelines (includes data sharing legislation).

Level 1 - Foundation

• Can choose from data analysis techniques.
• Can use (or learn how to use) appropriate analytical tools to investigate data.

Level 2 - Intermediate

• Can identify and implement suitable techniques and tools and assemble data visualisations for exploratory analysis on large/complex datasets.
• Can validate unexpected results.
• Is able to understand and amend existing code (programming language) to conduct exploratory data analysis.

Level 3 - Advanced

• Is highly competent at performing exploratory analysis on large/complex datasets.
• Can build capability of others in exploratory data analysis techniques.
• Can write custom scripts and code in a programming language to conduct complex analytical tasks.
• Maintains understanding of new trends and innovations relating to exploratory data analysis (including Artificial Intelligence-based technologies) and develops skills in these where relevant.

Level 1 - Foundation

• Can interpret basic data visualisations like standard charts and explain them to others.
• Can create basic visualisations such as tables and graphs.

Level 2 - Intermediate

• Can readily produce a range of data visualisation outputs (including complex graphs and map visualisations) and can critically assess and enhance those produced by others.
• Can select the most appropriate medium to visualise data.

Level 3 - Advanced

• Innovates the development of new approaches to, and options for, data visualisation, and can incorporate a range of techniques, including automation, interactivity, and animations.
• Can advise others on data visualisations options and the best options to present data results.
• Can build capability of others in creating and interpreting data visualisations.

Level 1 - Foundation

• Understands basic statistical measures and their application to data.
• Is aware of the analytical methodology being used in their work.
• Can use appropriate analytical tools.

Level 2 - Intermediate

• Can use statistical applications for statistical models.
• Is able to understand and amend existing code (programming language) to conduct analytical tasks.
• Can identify and implement suitable techniques and tools to explore data.
• Can validate unexpected results arising from data analysis.

Level 3 - Advanced

• Contributes to the development of novel statistical data analysis models.
• Can build capability of others in statistical data analysis techniques.
• Has expertise in multiple data analysis techniques and applications.
• Can write custom scripts and code in a statistical computing language to conduct complex analytical tasks.
• Maintains understanding of new trends and innovations relating to statistical data analysis (such as Artificial Intelligence-based technologies) and develops skills in these where relevant.

Level 1 - Foundation

• Understands the need for special data analysis methods and tools in some situations (for example, time series forecasting or geospatial analysis).
• Is aware of the analytical methodology being used in their work.

Level 2 - Intermediate

• Can develop, fit, diagnose, and troubleshoot a model in a new data analysis scenario that requires a specialist method (e.g. geospatial analysis or time series forecasting).
• Is able to understand and amend existing code (programming language) to conduct specialist data analysis.

Level 3 - Advanced

• Innovates in developing new methods in specialist areas (for example, new approaches to time series forecasting or geospatial analysis).
• Can write custom scripts and code in a programming language to conduct complex analytical tasks.
• Contributes to the development of novel statistical data analysis models.

Level 1 - Foundation

• Can use common applications to generate basic analysis outputs like tables with calculations and static charts.
• Understands reports and dashboards created with business intelligence tools.
• Is aware of the analytical methodology being used in their work.
• Can conduct basic analysis on simple data.

Level 2 - Intermediate

• Can use business intelligence applications to create complex reports and dashboards.
• Is able to understand and amend existing code (programming language) to conduct business intelligence data analysis.
• Can identify and implement suitable techniques and tools to explore data.

Level 3 - Advanced

• Has expertise in multiple business intelligence techniques and applications.
• Can build capability of others in developing outputs using business intelligence applications.
• Can write custom scripts and code in a programming language to conduct complex analytical tasks.
• Contributes to the development of novel statistical models.
• Maintains understanding of new trends and innovations relating to business intelligence data analysis (such as Artificial Intelligence-based technologies) and develops skills in these where relevant.