Data transformation framework: data personas report

Executive Summary

This project supports the development of a Data Transformation Framework to improve and enable data reuse in the Scottish Public Sector. Individuals and organisation will undertake data maturity assessments to measure their current maturity level and identify pathways to increase knowledge and skills. To support the pathway development a set of core personas are required to bring the framework to life for users.

This project has reviewed sets of existing personas in use both internally and externally to the public sector to identify a set of suitable potential personas that cover the end-to-end activities around data within the public sector. A survey and interactive workshops have then been carried out to validate these potential personas.

The output of this project is a set of final personas that cover the breadth of users of the Data Transformation Framework. 11 final personas have been identified and are documented below. 5 priority personas have been identified to provide initial focus. These are highlighted with **s below.

Final persona - Persona summary

Data novice**:

A public sector worker who is just beginning to understand the potential that data can bring to their role and their organisation. They are often users of systems that capture and create data.

Data consumer:

A non-technical data user that consumes visual information through reports or metrics to extract insights and support decision-making, research or planning activities.

Data analyst**:

A technical data user that manipulates data to create output analysis and visuals to extract insights, support decision-making, diagnose issues and answer questions. The types of data analysed can be general or specific, such as GIS data.

Data scientist:

A data professional who uses modern data science techniques, such as AI and machine learning, to develop analytical solutions to problems.

Data engineer:

A data professional who uses software engineering techniques to create data pipelines that support the automation and reproducibility of data solutions

Leader**:

A strategic business leader who wishes to use data to realise value for their organisation. Will be responsible for overall organisational strategic direction with access to budgets to deliver change.

Data transformation lead**:

A team (or department) leader who champions the effective use of data within their area of the organisation. They may be responsible for programmes of work, or leading teams to deliver change, but without the scope or budget align activities across the entire organisation.

Data product/service owner:

A solution innovator that is developing products or services that are data rich. Although they may not be highly data literate, they understand the importance of good data management in developing a scaleable solution.

Technology specialist**:

A technology professional who is responsible for the creation and maintenance of tools, systems and applications used to capture and store data. They also work to ensure the integrity, confidentiality, and security of all data assets within these systems and applications.

Data governance specialist:

A worker with responsibilities for the policies and processes that ensure data can be managed as an asset within an organisation. This includes ensuring compliance across legal and regulatory frameworks.

Data management specialist**:

A specialist responsible for one of many activities required to manage data as an asset. This includes the standards, structure, integration, quality and definition of data, including processes to manage these.

Further work is still required to validate these in detail and bring them to life with detailed needs, behaviours, and goals.