Data Processing

By Progression

The ability to process data, typically with the help of software.

Level 1

Is able to input data, run queries, and understand the basics of data processing.

  • Data management: Understands the basics of what data is and how it can be manipulated

  • Data pipelining: Is able to use a range of data processing tools and techniques to manage datasets.

  • Data innovation: Can use basic data processing tools. No specialised knowledge of the subject matter.

Level 2

Understands the complexities of data processing, can assess quality, and assess financial implications.

  • Data management: Can handle large amounts of data, knows what tools to use to manipulate data, has a basic understanding of databases

  • Data pipelining: Is able to use the right tool for the job, and has a good grasp of the basics of machine learning.

  • Data innovation: Has a good understanding of the data processing tools available, and has good knowledge of the subject matter.

Level 3

Leads the team in understanding the intricacies of data processing. Has in-depth knowledge in assessing quality and financial implications.

  • Data management: Manages data across multiple departments, has expertise in databases and knowledge of how machine learning fits into the process

  • Data pipelining: Can assemble complex pipelines from a wide array of components, applying deep domain knowledge in real world contexts.

  • Data innovation: Has in depth knowledge of both the subject matter and the data processing tools available. Can innovate with data sets to create new market insights for the organisation.

Level 4

Works alongside the director in understanding the intricacies of data processing. Has in-depth knowledge in assessing quality and financial implications.

  • Data management: Is able to make recommendations for machine learning tools and applies them to the data

  • Data pipelining: Building and operating complex pipelines and machine learning models is second nature. Leads teams in building and maintaining models that process and analyse large datasets.

  • Data innovation: Responsible for driving innovation with data sets, collaborating with senior management to analyse opportunities to use data sets in new ways.

Level 5

Is an expert on data processing both at a technical level and can assess its impact to the organisation. Is able to identify new trends through analysis of data sets.

  • Data management: Has mastered all aspects of data management, understands the limitations and possibilities for machine learning

  • Data pipelining: Is recognised as an expert in data processing, with expertise across a range of domains. Leads team building and maintenance efforts for large datasets. Transforms problems into opportunities by understanding the underlying data.

  • Data innovation: Owns the team's innovation with data sets, bringing new insights to emerging opportunities in the market. Collaborates with senior management to drive innovation agenda.

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