UK

United Kingdom · Technology and data · Principal/Manager (12-16 years)

Director of Analytics

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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  • Experience bandPrincipal/Manager (12-16 years)
  • Direct reports3-8 reports
  • Reports toVP of Data & Analytics
  • UK framework levelUsually someone running a function, or a director

Also advertised as Head of Data & Analytics · Principal Analytics Lead · Analytics Department Manager

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 5 of 10 standards
Qualifi Level 7 Diploma in IT Qualifi Ltd · Level 7 · covers 1 of 10 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 10 standards
Level 6 Certificate in Professional Sales Institute of Sales Professionals · Level 6 · covers 1 of 10 standards
Level 6 Diploma in Professional Sales Institute of Sales Professionals · Level 6 · covers 1 of 10 standards
TQUK Level 6 Diploma in Digital Leadership (RQF) Training Qualifications UK Ltd · Level 6 · covers 1 of 10 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Data Analysis and Visualisation OTHM Level 7 Diploma in Data Science
Data Analytics Qualifi Level 7 Diploma in IT
Data-led Decision Making Level 6 Award in Data-led Decision Making
Data science TQUK Level 6 Diploma in Digital Leadership (RQF)

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
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Your Plan Illustration

Built for Director of Analytics

4 units that map to this job, from the qualifications that cover it.

  1. Data Analysis and Visualisation OTHM Qualifications · covers 5 of 10 standards Level 7
  2. Data Analytics Qualifi Ltd · covers 1 of 10 standards Level 7
  3. Data-led Decision Making Institute of Sales Professionals · covers 1 of 10 standards Level 6
  4. Data science Training Qualifications UK Ltd · covers 1 of 10 standards Level 6
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Director of Analytics?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • Prompt Engineering & LLM Integration (Strategic Oversight)
  • Ethical AI Governance & Auditing
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Director of Analytics plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

A Director of Analytics leads the analytics strategy for a business domain, turning data into decisions that move the business forward. The role covers people, budget, and the impact of data work across that domain.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

Enterprise Data Platforms (e.g., Snowflake, Databricks) Strategic

Leading platform selection, approving architecture, setting budget, and managing key vendor relationships. You'll define how we store and process our core data assets.

Cloud Data Services (e.g., AWS, GCP, Azure) Strategic

Defining the multi-cloud or single-cloud strategy, governing cloud spend, and ensuring the security posture for all data assets under your purview. You're thinking about scalability and cost-efficiency at a high level.

BI & Visualisation Tools (e.g., Tableau, Power BI) Strategic

Selecting the enterprise BI standard for your domain, focusing on adoption metrics, and ensuring a consistent 'source of truth' for executive reporting. You'll set the standards for how we visualise our insights.

Data Governance & Cataloguing (e.g., Collibra, Alation) Strategic

Championing and sponsoring the entire data governance programme within your domain. You'll report on data maturity and risk to senior leadership, ensuring our data is trustworthy and compliant.

MLOps & Advanced Analytics (e.g., MLflow, SageMaker) Strategic

Setting the AI/ML vision for your domain, approving investments in MLOps platforms and specialised talent. You're accountable for the ethical implications and ROI of AI solutions your team develops.

Executive & Board Reporting (e.g., Diligent, Nasdaq Boardvantage) Owner

Using these tools to securely distribute and present analytics insights to the Board of Directors and other executive committees. You'll be the one presenting the numbers that matter most.

Financial & Strategic Planning (e.g., Anaplan, Pigment) Partner

Collaborating closely with Finance to align business forecasts from your analytics domain with financial models and strategic company objectives. Your insights will feed directly into corporate planning.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Strategic Direction for Analytics Domain N/A N/A N/A
Budget Allocation (within domain) N/A N/A N/A
Team Hiring & Organisation Design N/A N/A N/A
Technology & Tool Selection N/A N/A N/A
Data Governance Policy Implementation N/A N/A N/A

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Business Value Influenced
The measurable financial impact (incremental revenue or cost savings) directly attributable to analytics initiatives led by your team.
Target · >£5M annually

Your team's churn prediction model led to a 10% reduction in customer churn for a specific segment, resulting in £2.5M in retained revenue. Or, an optimisation model reduced operational costs by £3M.

Return on Analytics Spend (ROAS)
The ratio of business value influenced to the total cost of your analytics function (salaries, tools, infrastructure).
Target · 3:1 or greater

If your team's total cost is £1.5M, we'd expect to see at least £4.5M in attributable business value. Anything less means we need to rethink our investments or approach.

Organisational Data Literacy Score
The improvement in the company-wide data literacy assessment score within your domain, reflecting how well non-analysts can understand and use data.
Target · Increase by 15% year-over-year

After implementing a new training programme, the average score for Product Managers in your domain on the data literacy quiz went from 60% to 70%.

Data Asset Adoption
The percentage of key, governed datasets ('Certified Gold' tables) used in departmental BI dashboards or operational applications within your domain.
Target · Used in >80% of relevant dashboards/applications

The 'Customer 360' certified dataset is now the primary source for customer data in 9 out of 10 marketing and sales dashboards, up from 5 last year.

Strategic Influence & Partnership
How effectively you and your team are seen as trusted strategic partners, not just report generators. Are you proactively consulted on major business decisions?
  • You're regularly invited to strategic planning meetings for your domain. Business leaders seek your team's input before launching new initiatives. You're seen as a thought leader, not just a service provider. Your team's recommendations are frequently adopted by senior leadership.
Team Health & Development
The overall health, engagement, and professional growth of your direct reports and the wider analytics team within your domain.
  • Low voluntary turnover rates within your team. High scores on internal engagement surveys for your direct reports. At least 1-2 team members promoted or taking on significantly expanded responsibilities annually. You're known for developing strong talent who are sought after for other roles internally.
Data Governance & Quality Maturity
The progress made in improving data quality, establishing clear data lineage, and increasing the adoption of the data catalogue within your domain.
  • Fewer critical data quality incidents reported. Clear, documented data lineage for key datasets. Increased usage and positive feedback on the data catalogue from business users. You're seen as a champion for data integrity, not just a consumer of data.
Innovation & Capability Building
Your ability to introduce new analytical techniques, tools, or approaches that enhance our capabilities and solve problems in novel ways.
  • Successful pilot projects for new AI/ML applications. Adoption of new data visualisation standards. Introduction of new experimentation methodologies. Your team is seen as pushing the boundaries of what's possible with data, not just maintaining the status quo.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Driving Business Impact

You'll feel a real buzz from seeing your team's analytics directly influence a major product launch, optimise a marketing campaign, or uncover significant cost savings. It's about solving real-world business problems with data.

Knowing that a dashboard your team built helped the Sales Director reallocate resources, leading to a 15% increase in deals closed that quarter.

Building High-Performing Teams & Capabilities

You'll get satisfaction from mentoring your managers, seeing your team members grow, and building a truly world-class analytics function. It's about creating an environment where talent thrives and genuinely enjoys their work.

Seeing a junior analyst you hired years ago now leading their own team and delivering critical projects.

Shaping Strategic Direction

You'll love being at the table with senior leadership, helping to define the future of the business by bringing data-driven insights to strategic discussions. You're not just executing; you're influencing the 'what' and 'why'.

Contributing directly to the annual company strategy, with your insights on market trends and customer behaviour shaping key initiatives.

What frustrates people
  • The 'Single Source of Truth' is a Myth: You'll spend years fighting political battles to centralise data, only to have new business units spin up their own 'shadow IT' spreadsheets and databases, undermining all your work.
  • Garbage In, Garbage Out is Your Daily Reality: Expect to spend more time arguing for budget to fix legacy data quality issues at the source than you do on exciting AI projects. The business wants a crystal ball, but they're giving you foggy data to work with.
  • You're the Scapegoat for Bad News: When your forecast predicts a downturn, you're accused of being too pessimistic. When the business misses the forecast you were pressured to inflate, you're blamed for being inaccurate.
  • The HiPPO (Highest Paid Person's Opinion) Trumps Data: You will present a statistically significant, data-backed recommendation only to be overruled by a senior executive's 'gut feeling.' This will happen, and you'll need to learn how to navigate it.
  • ROI for Infrastructure is a Hard Sell: Securing a multi-million pound budget for foundational work like a data catalogue or governance platform is a brutal fight, as the benefits are long-term and not immediately visible on the P&L.
  • The Urgent 'Vanity Metric' Request: Your team's carefully planned sprint will be regularly derailed by an executive's 'urgent' request for a chart they need for a presentation in 30 minutes, which often has little to no real business value.
What this role does not give you
  • A quiet, purely technical role where you can just focus on coding and models. This is a leadership role, heavy on people, politics, and persuasion.
  • Predictable, routine work. You'll be dealing with novel, ambiguous, and often messy problems daily.
  • Immediate gratification on every project. Many of your strategic initiatives will take months, if not years, to show full impact.
  • An escape from budget battles. You'll be constantly justifying your team's existence and spend.

8Who you work with

This role directly shapes how a significant part of our business uses data to make decisions and achieve its goals. You're not just supporting strategy; you're helping to create it. Your work will influence everything from product roadmaps and marketing spend to operational efficiencies and customer retention, ultimately impacting our P&L and market position. You're building a capability that gives us a real competitive edge.

Inside the business
  • VP of Data & Analytics (your direct line)
  • Other Directors (e.g., Product, Marketing, Finance, Engineering)
  • C-Suite members (for strategic updates or specific initiatives)
  • Heads of Business Units (the people you're helping to make better decisions)
  • Legal and Compliance teams (especially for data governance and ethics)
Outside the business
  • Key technology vendors (e.g., Snowflake, Tableau, Databricks)
  • External consultants or partners (for specialised projects)
  • Industry bodies or professional networks (for best practices and talent)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven track record of leading and managing teams of data professionals (at least 5+ years of management experience, including managing managers).
  • Extensive experience (12+ years) in data analytics, business intelligence, or data science roles, with a clear progression through senior and lead positions.
  • Demonstrable experience owning and managing a significant budget (e.g., £500K+) for an analytics or data function.
  • Strong experience in developing and executing data strategies that delivered measurable business impact.
  • Deep understanding of at least one major cloud data ecosystem (AWS, GCP, or Azure) at an architectural level.
  • Experience presenting complex analytical insights and recommendations to executive leadership and/or board members.

10What to practise next

Where the job is going, and what to do about it starting this week.

Data Product Management & Strategy

Organisations are increasingly treating data and analytics as products, not just services. You'll need to think like a Product Manager for your data assets and analytical solutions, focusing on user needs, adoption, and measurable value. This means a shift from 'build it and they will come' to 'understand the user, then build what they need'.

Data Product Lifecycle · User-Centric Design for Data · Value Proposition & Monetisation · Roadmapping & Prioritisation

  • This month: Read up on 'Data Mesh' principles and how they relate to data product thinking. It's a hot topic for a reason.
  • Next quarter: Identify one key dataset or analytical model within your domain and formally define it as a 'data product' with a clear owner, users, and roadmap.
  • Month 4-6: Implement a feedback loop with your key business stakeholders, treating them as 'users' of your data products.
  • Ongoing: Attend data product management conferences or webinars to learn from industry leaders.

Quick win: Start by creating a simple 'product brief' for your most important dashboard, outlining its purpose, audience, and key metrics. It's a small shift in mindset with big implications.

11Staying current once you are in

What people here do to keep up
  • Active participation in industry conferences (e.g., Data + AI Summit, Gartner Data & Analytics Summit) to stay abreast of emerging trends and network with peers.
  • Regularly reading leading data science and business publications (e.g., Harvard Business Review, MIT Sloan Management Review, Towards Data Science) to inform strategic thinking.
  • Mentoring junior data professionals, which not only gives back but also sharpens your own leadership and communication skills.
  • Pursuing executive education programmes focused on AI strategy, digital transformation, or organisational leadership.
  • Contributing to internal knowledge sharing sessions, presenting on new techniques or successful projects.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering & LLM Integration (Strategic Oversight)

Competitors are already using Large Language Models (LLMs) to draft reports in minutes that used to take hours. Your team's productivity, and by extension your domain's analytical output, will depend on how effectively you can integrate and govern these tools. Your value shifts to validating, interpreting, and knowing when NOT to trust the output.

  • LLM Governance & Policy
  • Cost Optimisation of LLM Usage
  • Strategic Application Identification
  • Output Validation & Human-in-the-Loop

Ethical AI Governance & Auditing

With increasing regulatory scrutiny (e.g., EU AI Act) and public awareness, ensuring your AI models are fair, transparent, and unbiased isn't just good practice; it's a legal and reputational imperative. As Director, you're accountable for this. You need to move beyond 'trusting the model' to actively governing and auditing it.

  • Bias Detection & Mitigation
  • Model Explainability (XAI)
  • Fairness Metrics & Group Fairness
  • AI Risk Assessment & Impact Statements

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Data Governance Frameworks
  • Experimentation & Causal Inference
  • Predictive & Prescriptive Analytics
  • Data Monetisation & Productisation
  • AI Ethics & Responsible AI Frameworks
  • Organisational Data Literacy

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Lead Analyst / Analytics Manager (L4) within Zavmo

    3-5 years at L4

    Skills to master

    • Deepen your strategic thinking, take on broader cross-functional projects, mentor multiple junior team members, and start managing smaller budgets. Demonstrate consistent impact beyond your direct project scope.

    You're ready to move on when

    • Successfully led 2-3 major analytics programmes from inception to delivery, with clear ROI.
    • Consistently received feedback on strong leadership potential and ability to influence senior stakeholders.
    • Actively mentored 2+ junior team members who have shown significant growth.
    • Proactively identified and proposed new strategic analytics initiatives that were adopted by leadership.
  2. 2

    Senior Data Scientist / Principal Data Scientist (external)

    12-15 years total experience, with 3-5 years in a senior/principal IC role

    Skills to master

    • Transition from purely technical depth to broader strategic impact, team leadership, and stakeholder management. You'll need to show you can lead people, not just models.

    You're ready to move on when

    • Proven experience leading complex data science projects from end-to-end, including deployment and monitoring.
    • Demonstrated ability to translate highly technical concepts into clear business implications for non-technical audiences.
    • Experience informally mentoring or leading project teams, even without direct reports.
    • Strong commercial awareness and understanding of how data science drives business value.
  3. 3

    Analytics Consultant (from a top-tier consulting firm)

    10-15 years in consulting, with 3-5 years at Manager/Senior Manager level

    Skills to master

    • Adapt to an internal, long-term strategic role versus project-based consulting. Build internal relationships and navigate organisational politics, which can be different from client engagements.

    You're ready to move on when

    • Track record of advising C-suite clients on data and analytics strategy.
    • Experience leading large consulting engagements focused on data transformation.
    • Ability to build and manage client relationships, which translates to internal stakeholder management.
    • Strong understanding of various industry data challenges and best practices.

15Where this role leads

The long view: This role can lead to senior data leadership positions such as Chief Data Officer, Chief Analytics Officer, or Chief Technology Officer. Some directors move into board advisory or non-executive roles later on.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Director of Analytics is actually changing.

Where it leads

Roles this leads to

Also named as a next step, with no page in the catalogue yet:

  • Chief Data Officer (CDO) / Chief Analytics Officer (CAO) (L7)

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Data Analysis and Visualisation, worked against Director of Analytics.

Data Analysis and Visualisation Level 7

Applied to your work in Director of Analytics

1. To enable the learner to critically analyse the theoretical underpinnings of data analytics and their impact on decision-making in business management contexts. 2. To enable the learner to assess diverse data analysis activities, techniques, and tools applicable to business management scenarios. 3. To enable the learner to compare and contrast various predictive analytic techniques, evaluating their strengths and weaknesses in forecasting future business events. 4. To enable the learner to evaluate how predictive analytic techniques can be practically implemented for forecasting purposes within the business sector. 5. To enable the learner to evaluate prescriptive analytic techniques, illustrating their application with relevant examples from the business management domain. 6. To enable the learner to apply a suitable programming language or data analysis tool to conduct data analysis and visualisation tasks related to business management problems.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

Start my Director of Analytics plan, free
See Your Progress Grow Illustration
Director of Analytics
  • Data Governance Frameworks
  • Experimentation & Causal Inference
  • Predictive & Prescriptive Analytics
  • Data Monetisation & Productisation
  • AI Ethics & Responsible AI Frameworks
  • Organisational Data Literacy
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Director of Analytics is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. VP of Data & Analytics (L6)

    3-5 years in Director role

    Leading multiple analytics domains, setting enterprise-wide data strategy, managing larger budgets (£2M-£10M+), and reporting to the C-suite.

    • Data Governance at Enterprise Scale Overseeing the entire company's data governance framework.
    • Advanced Vendor & Partner Ecosystem Management Managing strategic relationships with multiple key technology partners.
    • Global Data Strategy If applicable, defining and implementing a data strategy across different geographies.
    • Public Speaking & Industry Representation Representing the company externally at conferences or in media.

  2. Chief Data Officer (CDO) / Chief Analytics Officer (CAO) (L7)

    5-8+ years in Director/VP roles

    Accountable to the CEO and Board for all data assets, defining enterprise data strategy (3-5 year vision), investor relations, and market positioning.

    • Data Monetisation at Enterprise Scale Driving new revenue streams from data across the entire business.
    • Global Regulatory Compliance Navigating complex international data regulations.
    • Strategic M&A Leadership Leading data integration for major acquisitions.
    • Crisis Management (Data-related) Leading the company's response to major data breaches or incidents.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, as a Director, your time is precious. You're constantly juggling strategy, team leadership, stakeholder management, and budget oversight. What if you could reclaim a significant chunk of that time, not by working harder, but by working smarter with AI?

AI isn't just for data scientists anymore. For a Director of Analytics, generative AI and advanced automation tools are becoming indispensable. They won't replace your strategic thinking or your leadership, but they'll certainly free you up to do more of it. Think of AI as your executive assistant, research analyst, and first-draft writer, all rolled into one.

Automated Board Commentary Generation

Imagine feeding quarterly performance data into a fine-tuned LLM and getting a first draft of your board report narrative commentary back in minutes. The AI identifies key trends, highlights anomalies, and structures the story, leaving you to refine the strategic insights and polish the message. No more staring at a blank page on a Sunday evening.

Proactive Anomaly & Opportunity Detection

Deploy AI-powered monitoring across your domain's key business KPIs. Instead of manual digging, the system automatically surfaces statistically significant deviations and correlations—like 'Sales in Germany are down 15% week-over-week, strongly correlated with a new competitor marketing campaign.' You'll be proactive, not reactive, always ahead of the curve.

Strategic Intelligence Synthesis

Use AI agents to continuously scan and synthesise competitor earnings calls, industry reports, and market research relevant to your domain. The AI provides a weekly executive summary of key strategic threats and opportunities, preparing you for high-level strategy meetings and helping you spot trends your competitors are missing.

Data Strategy & Proposal Drafting

Leverage generative AI to create the initial framework and content for critical documents: your annual data strategy, budget proposals for new technology, or complex data governance policy documents. The AI handles the boilerplate structure and initial research, allowing you to focus your expertise on the high-level strategic input and critical decisions.

Common questions

Common questions

How do you become a Director of Analytics?

Common routes in include Lead Analyst / Analytics Manager within Zavmo (3-5 years at L4), Senior Data Scientist / Principal Data Scientist (external) (12-15 years total experience, with 3-5 years in a senior/principal IC role) and Analytics Consultant (from a top-tier consulting firm) (10-15 years in consulting, with 3-5 years at Manager/Senior Manager level). Times vary with prior experience.

Where can a Director of Analytics progress to?

This role can lead on to VP of Data & Analytics (3-5 years in Director role) and Chief Data Officer (CDO) / Chief Analytics Officer (CAO) (5-8+ years in Director/VP roles), depending on the skills you build.

What new skills matter most for a Director of Analytics?

Increasingly, Prompt Engineering & LLM Integration (Strategic Oversight) and Ethical AI Governance & Auditing. These are the skills our record of this role lists as growing.

Free tools

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Three free tools, no account needed. Each one ends with a role, a level and a way in.

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17Where to go from here

Other roles at Level 6

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in technology and data

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills built as a Director of Analytics carry across industries. Building data capabilities, driving strategic impact, and leading technical teams matters in FinTech, HealthTech, E-commerce, SaaS, and other data-heavy sectors.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Director of Analytics plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.