United Kingdom · Technical roles · Entry Level (0-2 years)

Junior Regional Data Visualisation Assistant

Here is the whole job, in plain words. What it is, a real day, 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.

Experience bandEntry Level (0-2 years)
Direct reportsNo direct reports
Reports toSenior Regional Data Visualisation Assistant
UK framework levelUsually someone starting out, or keeping a process running

Also advertised as Associate Data Visualisation Analyst · Junior BI Report Developer · Entry-Level Dashboard Builder

Built on an analysis of 43,079 real UK job descriptions · grounded in qualifications employers recognise

Start with a free Future Fluency check, tuned to Junior Regional Data Visualisation Assistant

Ten quick questions, one per Future Fluency, asked against this role rather than a generic one. About five minutes, and no card.

Start the check, free

1What this role really is

This role is for someone just starting out in data visualisation. You'll be the hands-on support, helping the team build and maintain dashboards that actually make sense to people. Think of it as learning the ropes, getting your hands dirty with data, and turning numbers into clear pictures that help the business make better decisions. It's a foundational role, meaning you'll get a broad introduction to how we use data to tell stories.

2What you'd actually use

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

Tableau / Power BIIntermediate

Building and updating standard dashboards from clean data sources using predefined templates. Creating calculated fields and setting up basic filters and actions.

SQL (PostgreSQL, MS SQL Server)Basic

Writing `SELECT` statements with `WHERE`, `JOIN`, and `GROUP BY` clauses to query and validate data from well-structured tables. You'll be pulling the data you need.

ExcelAdvanced

Proficient with PivotTables, VLOOKUP/XLOOKUP, and Power Query for data cleaning and ad-hoc analysis. Creating basic charts and tables for static reports.

Python (pandas, Matplotlib/Seaborn)Awareness

Reading and understanding simple data manipulation scripts in pandas. May use it for basic data cleaning tasks with guidance, but it's not a core daily driver yet.

Jira / ConfluenceUser

Managing your personal tickets for dashboard requests and bugs. Documenting your work and findings on Confluence pages following existing templates.

Snowflake / BigQueryAwareness

Connecting BI tools to existing tables and views in the cloud data warehouse. Understanding basic concepts of cloud data architecture, but not directly managing it.

3What 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 choice	Coming in	Where you are now	The step above
Data Source Selection	Use pre-approved data sources and tables as directed by your supervisor. Do not connect to new sources without explicit instruction.	Can propose new data sources for review by a senior analyst, but final approval rests with the Lead Analyst or Manager.	Selects appropriate data sources for projects within their workstream, consulting with Data Engineering for new integrations.
Dashboard Design & Layout	Follow existing templates and design guidelines strictly. Propose minor layout tweaks to your supervisor for review.	Designs dashboards independently for routine requests, adhering to best practices and corporate branding. Seeks feedback from stakeholders.	Defines new design standards and templates for the team. Makes architectural decisions on dashboard structure for complex projects.
Data Validation & Error Correction	Identify potential data errors and escalate them to your supervisor with clear examples. Do not correct source data yourself.	Independently validate data and perform minor cleaning/transformation within the BI tool or ETL process. Escalate major data quality issues.	Leads data quality investigations, working with Data Engineering to implement long-term solutions. Defines data validation processes.
Project Prioritisation	Work on tasks as assigned by your supervisor. Do not re-prioritise your work without discussion.	Manages own task queue for routine requests, escalating conflicts or resource constraints to their manager.	Prioritises workstreams within their domain, balancing stakeholder needs with team capacity. Negotiates deadlines.

4How you'll be judged

The scoreboard, honestly: the hard targets, how often each one is actually looked at, and the quiet human signals that never make it onto a dashboard.

Report Accuracy

The percentage of reports and dashboards you build or update that are error-free when compared to the source data.

Target · >99.0% accuracy on all data points

You build a new sales performance dashboard. During testing, a senior analyst finds a calculation error that misstates regional revenue by £50K. That counts as an error. We'd expect very few of these after your initial training period.

Delivery Time for Ad-Hoc Requests

How quickly you complete smaller, routine data requests or dashboard updates.

Target · Fulfill 85% of standard ad-hoc requests within 48 hours

A regional manager asks for a simple chart showing last month's product returns. You deliver it within a day. If it takes three days for a similar request, that's something we'd look at.

Documentation Adherence

The completeness and quality of the documentation you create for your work, following our existing templates.

Target · 100% of new dashboards or major updates have complete documentation

You finish building a new dashboard. We check that you've filled out the data dictionary, explained the calculations, and noted the data sources in Confluence. If any of that's missing, it's not meeting the target.

Proactive Learning & Tool Adoption

How eager you are to learn new tools and techniques, and how quickly you start applying them in your work.

You'll be asking questions about Tableau's LOD expressions or how to write a more efficient SQL query. You'll be bringing up new features you've seen in Power BI. You'll actively participate in team learning sessions and share what you've discovered, even if it's just a small trick. We'd see you trying out a new chart type you learned about in a course.

Feedback Incorporation

Your ability to take on board feedback from senior colleagues and stakeholders, and use it to improve your work.

When a senior analyst suggests a different way to structure a dashboard, you'll genuinely try it out and understand why. If a stakeholder says a chart is confusing, you'll ask clarifying questions and iterate on the design, rather than just defending your original idea. We'd see fewer repeated mistakes and a clear improvement in your dashboard designs over time based on past comments.

Contribution to Team Knowledge

How you share your learnings, document processes, and help the team improve its collective understanding.

You might add a useful tip to our Confluence page about a tricky Excel function. You'll share a common data cleaning problem you solved and how you did it. You'll contribute to team discussions, even if it's just asking a good question that makes others think. It's about being part of the collective brain, not just working in isolation.

5Would you like it

The honest version. What people enjoy, and what grinds them down.

What people enjoy

Solving Puzzles

You love the challenge of taking a messy dataset and figuring out how to clean it, combine it, and then make it tell a clear story. It's like a daily detective game where the clues are numbers and the solution is a beautiful dashboard.

You're given a spreadsheet with inconsistent date formats and missing values. You enjoy the process of writing the Power Query steps or Python script to make it usable, then seeing the clear picture emerge.

Making an Impact

You get a real kick out of seeing your work actually being used by people to make decisions. You want to know that the charts you build are genuinely helping someone understand their business better.

A regional sales manager emails you to say the new dashboard helped them identify a key trend and adjust their strategy, leading to a noticeable improvement in sales figures. That's what motivates you.

Continuous Learning

You're always looking for new ways to do things, whether it's a more efficient SQL query, a new visualisation technique in Tableau, or a better way to structure data in Excel. You enjoy picking up new tools and skills.

You spend some personal time exploring a new feature in Power BI, then bring it up in a team meeting, suggesting how it could improve one of our existing reports.

What frustrates people

The 'Garbage In, Garbage Out' Reality: Spending 60% of your time cleaning, validating, and restructuring messy source data before you can even begin to build a visualisation. It's often not glamorous.
Endless 'Just One More Thing' Requests: Stakeholders who treat dashboards like a PowerPoint slide, requesting endless cosmetic tweaks and minor changes that derail your planned work.
Vague Requirements: The constant struggle of translating ambiguous requests like 'I need to see our sales trends' into a concrete, actionable dashboard, often involving multiple painful revision cycles.
Performance Bottlenecks: Building a brilliant dashboard that works instantly on your sample dataset, but then grinds to a halt and takes minutes to load when deployed with millions of rows of production data. It's frustrating when the tech doesn't keep up.

What this role does not give you

Complete autonomy from day one – you'll have guidance and check-ins.
A perfectly clean, ready-to-use dataset for every project – expect to get your hands dirty.
A role where every single piece of your work makes it to production and is celebrated – some work will be exploratory or get deprioritised.

6Who you work with

You're directly supporting the regional teams by giving them the data they need to do their jobs better. Your work helps them understand performance, spot trends, and make quicker, smarter decisions. Think of yourself as a crucial link in getting information from our databases into the hands of the people who need it most, helping them hit their targets and improve efficiency.

Inside the business

Regional Sales Teams
Regional Operations Teams
Product Analysts
Marketing Analysts

7What you need before you start

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

A foundational understanding of data concepts: what a database is, what rows and columns mean, and how data is structured.
Proficiency in Excel, particularly with functions like VLOOKUP, PivotTables, and basic data cleaning techniques.
Some exposure to a BI tool like Tableau or Power BI (even if just from a course or personal project).
Basic SQL knowledge – enough to write a simple query to pull data.
A genuine interest in visualising data and telling stories with numbers.
Strong problem-solving skills and a methodical approach to debugging.

8What to practise next

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

Advanced Data Transformation with Power Query/Python

As data sources become more complex and varied, the ability to perform sophisticated cleaning, shaping, and combining of data *before* it hits the BI tool becomes crucial. This saves time and improves dashboard performance.

M Language (Power Query) · Advanced Pandas Operations · Data Type Optimisation · Error Handling in ETL

This quarter: Take an online course specifically on Power Query's M language or advanced pandas techniques.
Next quarter: Identify one manual data cleaning process you currently do in Excel and try to automate it fully using Power Query or Python.
Month 6: Present your automated solution to the team, highlighting the time saved and improved accuracy.
Month 8: Start contributing to shared data preparation scripts or templates for the team.

Quick win: Look for repetitive data cleaning tasks you do in Excel. Can you record a macro or build a few Power Query steps to automate the first 50% of that work? Even small wins add up.

Interactive Dashboard Design & Performance Optimisation

Users expect more from dashboards than ever before—they want interactivity, speed, and the ability to explore data themselves. Knowing how to deliver this, even with large datasets, will differentiate you.

LOD Expressions (Tableau) / Complex DAX (Power BI) · Dashboard Actions & Parameters · Query Performance Tuning · User Experience (UX) Principles for BI

This quarter: Pick one of our existing dashboards and identify 2-3 ways it could be more interactive or perform better.
Next quarter: Take an advanced Tableau or Power BI course focusing on performance optimisation and complex calculations.
Month 6: Implement one significant performance improvement or new interactive feature on a live dashboard.
Month 8: Start peer-reviewing other team members' dashboards, offering constructive feedback on design and performance.

Quick win: When you're building a new dashboard, always ask yourself: 'How could a user explore this data further?' Then try to add one simple interactive element, like a filter or a drill-down.

9Staying current once you are in

What people here do to keep up

Actively participate in online data visualisation communities (e.g., Tableau Public, Power BI Community forums).
Follow industry blogs and thought leaders (e.g., Edward Tufte, Cole Nussbaumer Knaflic) to stay updated on best practices.
Take online courses on platforms like Coursera, Udemy, or DataCamp to deepen your skills in SQL, Python for data, or advanced BI tool features.
Build a personal portfolio of data visualisation projects. This is a fantastic way to showcase your skills and passion.
Attend local data meetups or webinars to network and learn from others in the field.

10How the AI economy is changing work like this

Before we ask anything of you, here's what we can already say about AI and work of this kind:

The new skill this role is being asked for: Prompt Engineering for Data Analysis

Large Language Models (LLMs) are becoming incredibly powerful. Analysts who can effectively 'talk' to these AI models will be able to generate insights, draft code, and summarise data much faster than those who can't. This isn't just a 'nice to have'; it's critical within the next year.

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

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 for Data Analysis

Large Language Models (LLMs) are becoming incredibly powerful. Analysts who can effectively 'talk' to these AI models will be able to generate insights, draft code, and summarise data much faster than those who can't. This isn't just a 'nice to have'; it's critical within the next year.

Clear Instruction Prompting
Context Windows & Token Limits
Output Validation
Iterative Prompt Refinement

What you’ll use

Skills this role draws on

Technical

Data Storytelling (Basic)
Visual Encoding & Best Practices (Basic)
Requirements Gathering (Support)
Dashboard Design & UI/UX (Support)
Data Modelling for Analytics (Awareness)
Statistical Literacy (Basic)

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
Graduate / University Leaver
0-1 year
Skills to master
- Core BI tool proficiency (Tableau/Power BI), basic SQL, data cleaning in Excel/Python, understanding of business metrics.
You're ready to move on when
- Successfully built and deployed 3-5 simple dashboards.
- Consistently delivers accurate data pulls and reports.
- Actively participates in team discussions and asks insightful questions.
2
Apprenticeship / Bootcamp Graduate
0-1 year
Skills to master
- Practical application of BI tools, data manipulation techniques, project-based learning, understanding of agile workflows.
You're ready to move on when
- Completed all assigned project work to a high standard.
- Demonstrates initiative in learning new tools and techniques.
- Can clearly articulate the business impact of their visualisation projects.
3
Junior Analyst (non-BI specific)
1-2 years
Skills to master
- Transitioning from general data analysis to visualisation-specific best practices, deepening SQL and Excel skills, learning a dedicated BI tool.
You're ready to move on when
- Successfully transitioned from Excel-only reporting to BI tool-based dashboards.
- Can independently troubleshoot minor data issues.
- Has a clear understanding of data storytelling principles.

11Where this role leads

The long view:Your journey starts here, but where it goes is really up to you. We'll give you the tools, the training, and the opportunities, but your curiosity and drive to learn will be your biggest assets. This role is a fantastic springboard into a rewarding career in data, with plenty of options to specialise or lead.

Pay & demand

Pay and demand for this role will appear here, each figure traced to a named authoritative source (e.g. the ONS Annual Survey of Hours and Earnings, under the Open Government Licence). We don’t show numbers we can’t attribute.

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 Junior Regional Data Visualisation Assistant is actually changing. In about two minutes, the free confidence check asks where you stand on each of the ten. That's the whole check, and it's what makes the plan yours rather than generic.

12The team that's yours

No two people are taught the same way. This is one-to-one, not one-to-many.

Zavmo is a hyper-personalised AI learning platform. Twelve virtual tutors, each with a different way of teaching, and one orchestration agent that picks the right one for the moment. So every single lesson is shaped around you, your role, and the way you learn. Not a course everyone sits through. A conversation built for you, and no one else.

…and nine more, matched to you after your first chat. Meet all twelve

Start free and meet yours

13What it feels like

A conversation, not a course

Because your tutor knows your role, your projects and your last session, learning sounds like this. And it's different for every single person:

Creating and Interpreting Visualisations in Data ScienceLevel 3

Applied to your work in Junior Regional Data Visualisation Assistant

This unit aims to equip learners with an understanding of the role and importance of data visualisation in data analysis and communication. Learners will explore the purpose and application of various plots and charts, and develop the ability to create and interpret visualisations to effectively represent and analyse data.

How the thinking builds

Remember
Understand
Apply
Analyse
Evaluate
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.

One to one, not one to many

No two people run this the same way

A course is written once and handed to everyone. This is assembled around you, and keeps changing as it learns you. Five things it reads, and what each one changes.

Your actual work Every lesson is taught against a live piece of your own work, not a worked example from a textbook.
What you already know The first conversation finds your starting point, so you skip what you can already do and spend the time on what you cannot.
The conditions you learn under Not a learning-styles quiz. The evidence does not support those. The dimensions the research does back, read once and used to shape the plan.
How far you got last time It picks up mid-thought. The tutor knows what you said, what you struggled with, and what it asked you to try.
Which tutor suits the moment Twelve of them, each for a different kind of thinking. The one who walks you through a first idea is not the one who stress-tests it.

See how you learn, free. Eight questions, no sign-up. A directional taster; the diagnostic inside Zavmo goes deeper and keeps adapting.

DemonstrateIllustration

Evidenced on your work in Junior Regional Data Visualisation Assistant

You do not finish by watching something. You finish by showing it on the work you already do, against the measures this job is judged on.

Report AccuracyThe percentage of reports and dashboards you build or update that are error-free when compared to the source data.You build a new sales performance dashboard. During testing, a senior analyst finds a calculation error that misstates regional revenue by £50K. That counts as an error. We'd expect very few of these after your initial training period.>99.0% accuracy on all data points
Delivery Time for Ad-Hoc RequestsHow quickly you complete smaller, routine data requests or dashboard updates.A regional manager asks for a simple chart showing last month's product returns. You deliver it within a day. If it takes three days for a similar request, that's something we'd look at.Fulfill 85% of standard ad-hoc requests within 48 hours
Documentation AdherenceThe completeness and quality of the documentation you create for your work, following our existing templates.You finish building a new dashboard. We check that you've filled out the data dictionary, explained the calculations, and noted the data sources in Confluence. If any of that's missing, it's not meeting the target.100% of new dashboards or major updates have complete documentation

These are this job's own measures, with its own targets. Nothing is marked evidenced, because nobody has started this yet. Yours would fill in from the work you bring.

Your passport

This isn't a certificate you file away. It's a passport to the life you're designing.

Every credit you earn and every fluency you build adds up: evidence where it counts, carried with you. Zavmo keeps the map: where you are, where you're heading, and the next step, at your pace, around your life. From Junior Regional Data Visualisation Assistant to Regional Data Visualisation Assistant (Mid-Level), and whatever you decide comes after.

Level 2 · in progressAI Fluency→ Regional Data Visualisation Assistant (Mid-Level)→ your design

Where this takes you

Your journey starts here, but where it goes is really up to you. We'll give you the tools, the training, and the opportunities, but your curiosity and drive to learn will be your biggest assets. This role is a fantastic springboard into a rewarding career in data, with plenty of options to specialise or lead.

See Your Progress GrowIllustration

Junior Regional Data Visualisation Assistant

Data Storytelling (Basic)
Visual Encoding & Best Practices (Basic)
Requirements Gathering (Support)
Dashboard Design & UI/UX (Support)
Data Modelling for Analytics (Awareness)
Statistical Literacy (Basic)

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.

14The 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

Junior Regional Data Visualisation Assistant is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

Regional Data Visualisation Assistant (Mid-Level)
2-3 years
From OFQUAL Level 3-4 to 5-6
- Advanced SQL (CTEs, Window Functions): Writing more complex queries for data extraction and transformation.
- Dashboard Design (Independent): Designing and building dashboards from scratch for specific teams/functions.
- Data Modelling for BI (Intermediate): Understanding how to structure data for optimal BI tool performance.
- Python (Intermediate): Using pandas for more complex data wrangling and exploratory analysis.

Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a big chunk of data visualisation work can be repetitive or time-consuming. Imagine if you could cut down on those mundane tasks, freeing you up to focus on the really interesting stuff – like uncovering hidden insights or designing truly impactful dashboards. Good news: AI can help you do exactly that, even at a junior level.

In this role, you'll be encouraged to use AI tools to speed up your daily tasks. We're talking about getting the first draft of your SQL query written for you, generating summaries of your dashboards, or even figuring out the best chart type for your data without you having to manually experiment. This isn't about replacing you; it's about making you a super-efficient data visualisation assistant.

SQL & DAX Code Generation

Use tools like GitHub Copilot or specialised AI assistants to translate your natural language requests (e.g., 'Show me sales by region for last quarter') into complex SQL queries or DAX formulas. This means less time wrestling with syntax and more time getting to the data.

Automated Insight Narration

Leverage built-in AI features in Power BI ('Smart Narratives') or Tableau ('Data Stories') to automatically generate plain-language summaries of key findings and trends in your dashboards. This can save you hours writing executive summaries for standard reports.

Anomaly Detection & Root Cause Analysis

Use AI-powered 'explain the increase/decrease' functions within your BI tools to instantly analyse data points and surface the primary contributing factors. This means you can quickly investigate unexpected data spikes or dips without hours of manual digging.

Visualisation Best Practice Engine

Tap into AI assistants or plugins that recommend the most effective chart type for a given dataset and analytical goal. It can even check your dashboard design against accessibility standards (WCAG), helping you build better, more inclusive visualisations faster.

Common questions

How do you become a Junior Regional Data Visualisation Assistant?

Common routes in include Graduate / University Leaver (0-1 year), Apprenticeship / Bootcamp Graduate (0-1 year) and Junior Analyst (non-BI specific) (1-2 years). Times vary with prior experience.

Where can a Junior Regional Data Visualisation Assistant progress to?

This role can lead on to Regional Data Visualisation Assistant (Mid-Level) (2-3 years), depending on the skills you build.

What level is a Junior Regional Data Visualisation Assistant in the UK?

This role aligns to RQF Level 2 on the UK framework, a guide to the depth of qualification it maps to, not a hard entry bar.

What new skills matter most for a Junior Regional Data Visualisation Assistant?

Increasingly, Prompt Engineering for Data Analysis. These are the areas where the higher-paid, future-proof work is heading.

The honest bit

You’ve started things before

Most of them were built for a room full of people who aren’t you. A cohort moves on whether or not your week allowed it, and by the third week the thing you’re behind on becomes the reason you stop opening it.

There’s no cohort here, and no timetable to fall behind. Before anything starts, Zavmo asks when you’re sharpest and how long you can realistically sit down for, then builds the sessions around those answers. A bad fortnight changes your pace. It doesn’t put you behind.

And you only pay once you start learning. Searching and planning are free, and you can cancel any time — so the cost of finding out is an afternoon, not a year.

What it costs

Less than one coaching session. Every month.

A single career-coaching hour costs more than a month of this, and it ends when the hour does. Zavmo doesn't. It's £70 a month, about £2.30 a day, for a companion that knows a Junior Regional Data Visualisation Assistant, works on the job you actually do, and keeps going at your pace rather than a timetable's.

Searching and planning stay free. You only pay when you start learning.
Your credits are yours. Regulated, and they don't vanish when a subscription ends.
Cancel any time and billing stops. No notice period, no minimum term.

Your path, personalised

You have the map. Walking it is the part we do together.

This route runs to 10 national skill standards. That is a real journey.

Zavmo shapes a learning experience as unique as you are. It fits how you learn, your pace and the work you already do. Every step stays benchmarked to recognised national standards. That’s the plan for becoming a Junior Regional Data Visualisation Assistant: personal to you, and it still counts. The first steps are free.

Independent research finds well-designed intelligent tutoring performs nearly as well as one-to-one human tutoring: VanLehn (2011), Educational Psychologist.

A private tutor in the UK averages £35–40 an hour . Zavmo is £70/month.

A Zavmo curriculum screen: a three-month plan built for a customer support lead, five Ofqual-regulated units and a hundred and ninety-six credits. — A real plan on learn.zavmo.ai: Ofqual-regulated units, credits, and a three-month run at your own pace.

Start free No commitment. See your first steps free.

15Where to go from here

Other roles at Level 2

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

Other roles in Technical roles

Stay in the field you know and move sideways rather than up.

If you leave this industry

The skills you'll gain here—data cleaning, SQL, BI tool proficiency, and data storytelling—are highly transferable across almost any industry. You could move into finance, marketing, healthcare, e-commerce, or even government. Every sector needs people who can make sense of their data.

Not sure this is the right direction?

Work out what you actually want from work first, then come back and see which roles fit it. Takes about ten minutes.

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. Build my plan, free Here's the first ten minutes: a 2-minute confidence check → your personalised roadmap → meet the tutors matched to you. No card, cancel any time. 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.

Junior Regional Data Visualisation Assistant

What's rising in its place

Prompt Engineering for Data Analysis

Skills this role draws on

Technical

How you actually get there, here

Graduate / University Leaver

Apprenticeship / Bootcamp Graduate

Junior Analyst (non-BI specific)

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

Roles this leads to

No two people are taught the same way. This is one-to-one, not one-to-many.

A conversation, not a course

No two people run this the same way

This isn't a certificate you file away. It's a passport to the life you're designing.

Everything else the record holds

The career path, and where it branches

Regional Data Visualisation Assistant (Mid-Level)

Where AI is starting to help

SQL & DAX Code Generation

Automated Insight Narration

Anomaly Detection & Root Cause Analysis

Visualisation Best Practice Engine

Common questions

You’ve started things before

Less than one coaching session. Every month.

You have the map. Walking it is the part we do together.