Enginuity Future Skills Hub

The engineering and manufacturing sector is rapidly evolving, making it challenging for employers to identify the skills necessary to stay ahead. Future Skills Hub offers a comprehensive collection of resources on various technologies and their impact on skills demand, all presented in an accessible, bite-sized format.

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What is data analysis and visualisation?

Data analysis and visualisation involves collecting, examining and presenting data to derive actionable information and business insights. 

Data analysis uncovers patterns, trends, or correlations, while data visualisation uses graphs or charts to communicate findings effectively. 

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Data analysis and visualisation explained

How is data analysis and visualisation used?

Data analysis and visualisation is used in many ways, including production analysis, supply chain and market analysis, workforce productivity, and safety monitoring. Examples include: 

  • Identifying production patterns related to product quality, and equipment and machinery performance  
  • Evaluating demand patterns, inventory levels, and lead times  
  • Analysing energy consumption and compliance with regulations  
  • Supporting cost analysis and budgeting  
  • Analysing customer feedback and satisfaction, tracking market trends, and evaluating competitor performance. 
  • Assessing workforce productivity and safety metrics.

Benefits of analysis and visualisation

Data analysis and visualisation applies to various aspects of engineering and manufacturing processes, enhancing efficiency, and supporting strategic decision-making in small to medium-sized enterprises.

Analysis and visualisation and Industry 4.0

Data analysis and visualisation are fundamental to , providing insights into complex datasets and driving data-driven decision-making. They enable real-time monitoring, predictive analytics, and prescriptive insights, empowering organisations to optimise processes, improve quality, and drive innovation in environments. 

Analysis and visualisation and sustainability

Data analysis and visualisation can support sustainability by optimising production processes, identifying energy-efficient strategies and waste reduction opportunities, and monitoring environmental performance metrics. This leads to resource efficiency, reduced waste, and improved overall sustainability in data-driven operations.

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What skills might you need?

Skills needed for data analysis and visualisation include proficiency in data manipulation, statistical analysis, and data visualisation tools such as Tableau or Power BI. Additionally, expertise in programming languages such as SQL, Python, or R, and domain-specific knowledge in engineering or manufacturing processes are useful for deriving actionable insights from large datasets and communicating findings effectively to stakeholders. 

Other specific skills include:  

  • Data analysis 
  • Data management 
  • Data modelling 
  • Data mining 
  • Data science 
  • Data warehousing 
  • Database design 
  • Information security 
  • Problem management 
  • Project management 
  • Change management 
  • Visualisation 
  • Stakeholder relationship management 

Who might need them?

While not everyone in the organisation may need advanced skills in data analysis and visualisation, there are certain roles and functions where these skills are particularly valuable, including: 

  • Data analysts and scientists 
  • Business intelligence (BI) and analytics specialists 
  • IT and database professionals 
  • Project managers and leaders 
  • Quality control and process improvement specialists 
  • Operations and supply chain management 
  • Decision-makers and executives  
  • Frontline workers.

Useful resources

Person working at Barrs Court Engineering

Barrs Court Engineering

Discover how this precision engineering company developed the skills needed in the workforce to adopt digitalisation in the factory.

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Colleagues walking around factory together.

Dig a bit deeper?

Visit Skills for the Information Age (SFIA), the global skills and competency framework for the digital world.

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