Name the capability your team needs and decide how people will actually learn it. The apprenticeship levy is there to fund it. We scope and deliver a programme that changes what your team can do.
Upskill Your Team in Data Analytics: Scope It, Then Fund It
By James Cotton · Last updated · 10 min read
Part of our topic guide on AI Skills for Business.
By James Cotton, Founder, iO-Sphere
The first decision is about capability
When an L&D lead hears there is unspent levy money, the question quietly becomes "how do we use the funding" instead of "what should the team be able to do that it can't do now". Only the second question changes anything. A programme chosen because a budget existed, rather than because an outcome was named, spends your team's working time and hands back a completion certificate.
So the first decision is not a funding one. It comes down to two plain questions. What capability does the team need: a report that doesn't exist today, a pipeline someone in-house can maintain, a decision made faster, an analysis the business currently buys in? And how will each person actually build that capability?
Our answer to the second question is settled. People get good at data by doing the work, coached by someone who has done the job, on problems that look like the ones they face. Funding decides who pays. It says nothing about whether anyone gets better, which is why the delivery model deserves as much scrutiny as the funding line. A year of lectures and a passed exam can produce a completion rate of 100% while the team's actual output does not move, so when you judge any programme, funded or not, ask what learners will be doing each week and who is coaching them.
If you are still weighing whether to upskill the people you have or hire new ones, we work through that trade-off in our guide to upskilling your data team. This page assumes you have decided to build capability in the team you have, and it covers how to scope and fund it.
How we build a team's capability
Live project work is the ideal, but most teams can't absorb the mistakes that teach in production. The safest place to learn is often exactly the place you cannot let people fail. We resolve that with our Prism method: realistic business case studies and simulations built on real data, for the scenarios a workplace can't safely or practically supply.
Learners break things that teach without touching anything live, on data with the messiness and scale they will meet on the job, so no part of the standard goes unpractised just because your day-to-day work happened not to throw it up. The people correcting the work are practitioner coaches on every route.
Open and closed cohorts are a choice of shape
A programme can take one of two shapes, and the difference is composition, not price.
In an open cohort, your people learn alongside people doing the same job in other companies and industries. If you have one or two people to upskill, they join an open cohort and there is no minimum on your side. The cross-company mix is the point of it: our cohorts run on professional discussion, peer challenge and networking rather than self-study, so a lone analyst in a company with no other data people meets people doing the same work elsewhere, builds best practice between them, and brings that back. That is the thing their own workplace cannot supply.
A closed cohort is built solely around your organisation. For that we look for ten to twelve people, so the group works on your context, your systems and your data throughout. It trades the cross-company breadth for depth in one business. Both are real choices, and neither is a cut-price version of the other.
The working time to plan for
Our apprenticeship programmes run fifteen months of training followed by a three-month end-point assessment. That is the timeline to plan around. The training happens in protected, paid working hours: the off-the-job requirement for the Data Analyst standard is around 370 hours across the programme, which works out at roughly six hours a week over the fifteen months (a 187-hour figure is an absolute floor that applies only after prior learning is recognised, never the starting requirement).
Line managers need to release that time and be on board before you start, and it is the commitment employers most often underestimate.
The doors for a mixed team
A team is rarely all at one level, so people join the same domain through different doors depending on where they start and what they need to do.
The anchor for core data analytics is our Advanced Data & AI programme, delivered on the Level 4 Data Analyst standard (ST0118), which carries a maximum funding band of £15,000 per learner (Skills England). It builds working SQL, Python and Power BI on real problems. Around it sit the routes for different starting points:
- Data & AI Essentials (Level 3, Data Technician standard ST0795, £13,000) for people newer to data.
- Data Engineering (Level 5, Data Engineer standard ST1386, £19,000) for the people who build and maintain the pipelines.
- AI Transformation (Level 4, standard ST0117, £18,000) for applying AI to business processes. This is the funded route into AI-for-business capability, and it is the space we most want to be in.
- Data & AI Strategy and Data & AI Governance (both Level 4, £10,000), one for leadership-level, data-driven decision-making and the other for data quality, compliance and stewardship. Both run on the same standard, ST0967, with a strategy or a governance emphasis.
Every one of these is built with AI integrated from the ground up rather than bolted on, so building data capability and building AI capability happen on the same programme. Matching your people to the right doors is part of scoping, and it is quick to do with us: start with our employer team on funded programmes.
The levy is there to fund it
For team-wide data upskilling in England, "government funding" almost always means the apprenticeship levy, and once you have named the capability the funding is usually the straightforward part.
If your annual pay bill is over £3m you already pay the levy: 0.5% of the pay bill through PAYE, offset by a £15,000 allowance, figures unchanged since the levy began in 2017. That money is yours to spend on approved training, and the funds to upskill your team are likely already sitting in your digital apprenticeship service account.
From April 2026 the levy is becoming the Growth & Skills Levy (formerly the Apprenticeship Levy), which keeps the same 0.5%-over-£3m mechanic and starts funding some shorter, more flexible training alongside full apprenticeships. We deliver full apprenticeships rather than the short units, because genuine capability-building is what we are for.
If your pay bill is under £3m you do not pay the levy, and you are not shut out. Any start you plan now lands in the 2026-27 funding year (starts from 1 August 2026), where apprentices aged 16 to 24 are 100% government funded at every employer, and the government co-invests 95% of the cost for those aged 25 and over at a non-levy employer, leaving you paying 5%. A smaller employer can also receive a levy transfer: a levy payer can pass up to 50% of its unused funds (raised from 25% on 22 April 2024) to another employer, often a supply-chain partner, and that can cover a programme in full.
Existing employees are eligible, so you do not have to hire someone new to use the funding. The one constraint is that funding will not pay for skills a person already holds, so Recognition of Prior Learning reduces the content, duration and price to match what they still need to learn. It never disqualifies anyone, and it cannot take a programme below the eight-month minimum duration. Apprenticeship standards are maintained by Skills England, and the funding rules sit with the Department for Work and Pensions.
- Apprenticeship levy rate
- 0.5% of annual pay bill, on pay bills over £3m, with a £15,000 allowance (HMRC PAYE, unchanged since 2017)
- Levy transfer cap
- Up to 50% of unused funds, transferable to another employer (raised from 25% on 22 April 2024)
- Data Analyst standard funding band
- Maximum £15,000 per learner: Data Analyst, ST0118 (Skills England)
- Our delivery
- 15 months of training plus a 3-month end-point assessment
The mechanics run deeper than this: the transfer paperwork, the fund expiry clock, the co-investment rate for a levy payer who has exhausted its pot. Our Growth & Skills Levy explainer covers that ground. For scoping a programme, the summary above is enough. Funding rules change annually, so check the current DWP funding rules before you commit.
When a shorter or different route fits
An apprenticeship is the right shape for building durable capability across a team over time. Where it isn't, we run the alternatives rather than pointing you elsewhere.
- A fast, focused upskill under three months. When the eight-month apprenticeship minimum is more commitment than a specific need warrants, a Skills Bootcamp is the shorter route. Bootcamps are government-funded on headcount: an SME (fewer than 250 employees) pays 10% of the cost, a large employer (250 or more) pays 30%, and an unemployed or self-referred individual is fully funded. We run Skills Bootcamps in windows, so check what is currently open.
- An individual retraining into data without an employer to sponsor them. Our Applied Diploma is a fourteen-week bootcamp that ends in a regulated Level 4 qualification. It is fee-paying rather than levy-funded, so it fits a person investing in their own switch into data rather than a team being upskilled in post.
- Deep machine-learning or research capability. The Data Analyst standard is Level 4. If you are really after Level 6 or 7 data-science depth, that is a higher route, and our Level 4 Advanced Data & AI builds the foundation and the progression toward it rather than standing in for it.
- A team that already holds Level 4 competencies. Funding will not pay for skills people already have, so Recognition of Prior Learning would shrink the programme substantially, and for an already-competent group the remaining content may not justify the overhead. It is worth testing before you commit.
- A team outside England. Apprenticeship funding as described here is England-only. Scotland, Wales and Northern Ireland run their own skills funding systems with different rules, so start with those.
Scope it with us
The work that makes a data upskilling programme pay off is the scoping: naming the capability each person should build, matching people to the right doors, and protecting the working time so the learning lands in the business. That is the conversation to have before the funding one, and it is the conversation we run.
Tell us what your team needs to be able to do, and we will work back to the shape, the doors and the funding route that fit. Start with our employer team on funded programmes, or talk to us about a custom programme built around your organisation.
Frequently asked questions
Is government-funded data analytics training actually free for employers?
No. "Free" means the training cost is funded, not that it costs the business nothing. A levy payer spends money it has already contributed; a non-levy employer pays a small co-investment share (nothing for apprentices aged 16 to 24, and 5% for those aged 25 and over under the 2026-27 rules that apply to starts you plan now); and every employer commits paid working time for off-the-job training. The real cost is that working time, and it is worth spending only when the capability actually changes.
Can existing employees be funded, or only new hires?
Existing employees can be funded, so you do not have to hire someone new to use the levy. The one rule is that funding will not pay for skills a person already holds, so Recognition of Prior Learning reduces the content, duration and price to match what they still need to learn. That makes the levy a genuine route for upskilling a team already in post.
I only have two or three people to upskill. Is that too few for a funded programme?
No, and there is no minimum on your side. A team of one or two joins an open cohort, learning alongside people doing the same job in other companies and industries, on the same standard and the same funding as everyone else. For a small team, or a lone analyst with no other data people around them, that cross-company mix is often the most valuable part of the programme, because it is the peer challenge and shared practice their own workplace cannot supply. A closed cohort built solely around your organisation is where we look for ten to twelve people; below that, an open cohort is usually the better home anyway.
How much working time does a funded programme need?
Off-the-job training happens in protected, paid working hours, not evenings or weekends. The amount is set per standard: for the Data Analyst standard it is around 370 hours across the programme, which works out at roughly six hours a week over the fifteen months of training (a 187-hour figure is an absolute floor that applies only after prior learning is recognised, not the starting requirement). Securing line-manager buy-in for that time before you start is the commitment employers most often underestimate.
Does funding cover AI upskilling as well as data analytics?
Yes. The most common employer response to AI is to upskill the people already in post rather than replace them, and the levy funds that. Our AI Transformation programme (Level 4, standard ST0117) is the funded route into AI-for-business capability, and every programme in our data line is built with AI integrated from the ground up, so building data capability and building AI capability happen on the same programme.
Ready to build the capability rather than just spend the funding? Tell us what your team needs to be able to do, and we will start there. Talk to us about funded programmes for employers.
Build a data-literate workforce
Data apprenticeships funded through the Growth & Skills Levy: £0 for any apprentice under 25, and most of the cost covered for older starts.