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Assist in developing data visualisations

URN: TECIS806301
Business Sectors (Suites): IT(Data Science)
Developed by: e-skills
Approved on: 29 Jan 2021

Overview

This standard identifies the competencies you need to assist in the development of data visualisations.

Data visualisation is about creating graphical outputs to present data in ways that are easy to understand and interpret, and which are appropriate for the audience.  There are a wide variety of data visualisation techniques including charts, graphs, infographics and other pictorial representations. These visual representations are used to help develop insights into datasets and aid the identification of  trends and patterns in the data.

Data visualisation tools and techniques are used to create and communicate information either internally within an organisation or externally for clients. To do this you are required to have appropriate domain knowledge of the data as well as the skills, knowledge and understanding necessary to deliver high quality data visualisations to describe and illustrate relationships in the data.

Data visualisation revolves around first understanding the data context, identifying and preparing the data and then selecting the most appropriate graphical outputs to best aid data interpretation and analysis. Your underpinning knowledge will provide an understanding of the principles of data visualisation along with the use of associated tools and techniques.

This activity is likely to be undertaken by all knowledge workers who need to prepare and present data visually to support data-driven decision making. It will also be required for those specifically working in roles as data professionals.

Performance criteria

You must be able to:

  1. interpret and evaluate data visualisation graphics in line with requirements

  2. identify visualisation and reporting requirements from functional requirements and use cases

  3. locate the datasets required for visualisation in line with requirements
  4. extract, blend and load the data in line with organisational procedures
  5. transform the data into structured datasets for visualisation
  6. select the most appropriate visualisation approach from suitable options
  7. produce data visualisation graphics that consider the target users needs and follow industry standard accessibility guidelines for content, layout, navigation and colour
  8. design the content and appearance of data visuals to produce the outputs required
  9. use specified tools and techniques to develop the required data visualisations
  10. review and document the data visualisation outputs appropriate for the target audience 
  11. publish data visualisations to make them accessible to the organisation and externally where required
  12. automate data visualisation activities to improve efficiency
  13. use storytelling methods to present the data in a meaningful way to a range of technical and non-technical audiences
  14. overlay and compare data visualisations with contextual and reference data to help the audience understand the data more clearly
  15. distribute data visualisations using relevant communications methods

Knowledge and Understanding

You need to know and understand:

  1. the potential benefits of data visualisation for organisations
  2. the terminology, concepts and basic techniques in data visualisation

  3. how to interpret data visualisation graphics to determine their meaning

  4. what makes a good visualisation, including avoiding misleading and hard to decipher graphics and those containing mistakes

  5. the industry standard data storage technologies and how to manage data with them
  6. the domain and context of the data being visualised
  7. the definitions and meaning of data to be visualised
  8. how people perceive data and why certain techniques can greatly enhance the effectiveness of any visualisation

  9. the main stages of a data lifecycle, including create, update and destroy

  10. how to identify, extract, transform, load and store data

  11. when to use each graphics type including for comparison, composition, distribution, and relationship
  12. the capabilities of different visualisation tools and how to apply them

  13. how to use standard data visualisation tools to create area plots, histograms, and bar charts

  14. how to design visualisations to convey insights clearly

  15. the benefits and constraints of creating accessible and inclusive data visualisation graphics
  16. how to critically analyse and evaluate data visualisation graphics against accessibility guidelines, policies and regulatory requirements
  17. the appropriate use of colour to convey insights and support accessibility
  18. the procedures used to extract and manipulate datasets for data visualisation
  19. how to use storytelling methods to relay an impactful data visualisation the audience
  20. how to communicate data, trends and patterns through both visual and oral methods

Scope/range

Scope Performance

Scope Knowledge

Values

Behaviours

Skills

Glossary

Links To Other NOS

External Links

Version Number

1

Indicative Review Date

31 Mar 2024

Validity

Current

Status

Original

Originating Organisation

ODAG Consultants Ltd.

Original URN

TECIS806301

Relevant Occupations

Data Wrangler, Data Operations

SOC Code

2139

Keywords

Data Science, Data Analytics, Data Visualisation