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DataIQ Leaders primer – Data and analytics apprenticeships

Apprenticeships are an alternative route through higher education, but they are not well known or adopted within the data and analytics sector. This primer explains the basic principles of the scheme and the current options, as well as a few issues that have yet to be resolved.
Analytics Training

In England, any organisation with an annual pay bill over £3 million pays the Apprenticeship Levy. This is held in a credit account to fund the training part of any apprentices who are employed (companies are still liable for salaries). The allowance built up in this way must be spent within each tax year and can not be carried over.

To take on an apprentice, an employer must either hold a recognised and certified training qualification or, more usually, work with an external training provider. Apprenticeships operate to standards which have been developed by interested parties (known as Trailblazers) and approved by the Institute for Apprenticeships. Delivery against these standards has to be certified by an External Quality Assurance (EQA) organisation.

Standards reflect what employers and industry consider to be essential for a skilled worker while ensuring the training has academic rigour. New standards can be developed where none exist to fill emerging needs provided the appropriate procedure is followed.

Data and analytics apprenticeships

There are two current standards to support apprenticeships relevant to the data and analytics sector:

Data analyst 

The first standard to have been developed and available since 2016, this is intended to train individuals to “collect, organise and study data to provide business insight”. This is a level 4 qualification, which means candidates must have at least five GCEs and/or A-levels, or have completed a level 3 apprenticeship.

The standard covers technical competencies (data selection, manipulation, architecture), technical skills (governance, quality, integration) and soft skills (creative thinking, stakeholder engagement). Training lasts for 24 months.

It is notable that this apprenticeship seeks to cover a spread of roles – data analyst, data manager, data scientist, data modeller, data architect, data engineer – which many organisations might see as too divergent for a single standard. This may reflect the rather unusual mix of trailblazer organisations who developed the standard, which included HMRC, The Home Office, BT, IBM, Microsoft, John Lewis and others. 

Data scientist 

Only approved in 2018, this apprenticeship is level 6 (integrated degree) and is intended to equip candidates to “find information in diverse datasets to address complex problems and improve organisational processes”. Candidates need three A-levels (including one STEM) or to have completed a level 3 apprenticeships.

Training for this apprenticeship lasts for 36 months and provides candidates with a BSc in Data Science, It also has a more sophisticated view of how a data scientist works within an organisation, recognising the importance of behaviours (collaboration, hypothesis-driven thinking) alongside the formulation of problems and the data engineer required to address them. 

This undoubtedly reflects the much larger Trailblazer group involved in developing the standard – 68 organisations in total – covering public sector, national and local government, brands, technology vendors, associations and training institutes.

Two more standards are in the process of being developed – Data technician (level 3) and Artificial intelligence data specialist degree (level 7), which is still only in the proposal stage. Neither of these is yet available for employers to adopt.

Challenges for data and analytics apprenticeships

Awareness of the opportunity for data and analytics functions to employ apprentices is low. In part, this reflects the recency of the scheme (barely three years old). It is also the case that the concept of an apprentice is not as well understood in this sector as it is in others which have more of an established career structure, technical history or engineering base. 

As a result, other functions have had first call on the available training funds. They have also benefitted from better standards and more widely-available training providers. It is fair to say that the standards as noted above have some issues and also that existing providers tend not to be able to cover the entire spectrum of what is needed. Typically, technical training dominates, with the soft skills elements delivered via a more generic provider. 

DataIQ is currently undertaking the process to become a qualified apprenticeship training provider and hopes to be in a position to deliver training from 2020. At that time, it will also seek to have input to standards and to develop new apprenticeship roles in line with what industry requires.

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