SCF-30

Process data

Develop and use techniques, tools, and coding skills to store, combine, process, analyse, interpret, and present data efficiently to meet customer requirements, including applying statistical techniques like machine learning

Proficiency levels

Level Description
Aware
  • Can describe key terms and fundamental concepts related to storing, combining, processing, analysing, interpreting, and presenting data.
  • Can describe the general importance of data processing and the application of statistical techniques like machine learning.
Practitioner
  • Can use standard methods and tools to store, combine, process, analyse, interpret, visualise, and present data to meet customer requirements.
  • Can use coding in one language to help process, analyse, interpret, and visualise data.
  • Can select and apply appropriate techniques for data processing and explain why certain techniques are chosen for specific problems.
  • Can apply basic statistical techniques, including machine learning algorithms.
  • Can explain limitations in data, such as data quality or resolution, and how these impact analysis.
  • Can interpret the results of basic data analyses and present findings to non-technical stakeholders in an understandable way.
Senior Practitioner
  • Can develop and implement complex methods for data storage, combination, processing, analysis, interpretation, and presentation to address complex problems.
  • Can use coding in one or more languages to process, analyse, interpret, and visualise data efficiently.
  • Can apply advanced statistical techniques and machine learning models to solve complex data-related problems.
  • Can interpret complex data sets, explain trends, and develop models to predict future outcomes based on historical data.
  • Can analyse and address the limitations of data, such as biases, uncertainties, or incomplete datasets.
  • Can translate data insights into actionable recommendations.
Expert
  • Can mentor others to enhance their skills in data processing techniques and tools.
  • Can innovate and develop new methods for efficiently storing, processing, analysing, interpreting, and presenting large or complex datasets.
  • Can design and implement machine learning or statistical techniques to solve novel data problems or improve data processing workflows.
  • Can ensure that data analysis is aligned with customer requirements.

Other taxonomies

Equivalent or similar competencies in other taxonomies.

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Taxonomy Competency
ESCO process data
L6 Space Apprenticeship Mission Analysis techniques using numerical analysis and simulation tools such as AGI-Systems Toolkit or NASA-GMAT.
L6 Space Apprenticeship Use scientific and engineering data. For example, to support decision making during design, build and operations phases of a mission or project.