Free job simulation · AI and data
Data analyst job simulation: clean messy data and present the answer
A data analyst job simulation is a self-paced set of workplace tasks that mimic the first weeks of the role. You receive a vague question, profile and clean messy files, reconcile two sources that disagree, analyse the result and present a recommendation. It is practice evidence, not employment. This version uses an online retailer's order and customer files, and ends with a pack you can show.
You join Fernhollow Home Ltd (simulated company), a online homeware retailer in Manchester. Days 1 to 5 are free, with about 9 h 50 min of tickets. Premium continues to day 20. It is practice, not employment.
Days 1 to 5 are free. You need a free account and no card. Create an account.
- Free days
- 1 to 5
- Free tickets
- about 9 h 50 min
- Project documents
- 7
- Certificate, optional
- £14.99
The project
You join Fernhollow Home Ltd (simulated company)
Fernhollow Home Ltd (simulated company) is a online homeware retailer in Manchester. You help its team deliver a project for Customer Growth team, at Fernhollow Home head office (internal client, ticket DATA-142).
You are the junior analyst in the insight team at Fernhollow Home, an online retailer. The Head of Customer Growth wants to know why repeat orders fell in September before deciding where to spend the autumn retention budget. You get four real-looking data files with planted problems, a data dictionary with gaps, a query that nobody has reviewed and tickets with acceptance criteria. Over four weeks you profile and reconcile the data, log its quality, meet a stakeholder who changes a definition mid-way, find that a CRM merge has inflated the problem, test what is real, build a bridge from the dashboard to finance, resist two requests that would harm the work, and hand over a pack. Some pressure comes from senior people. Your job is to be useful and honest at the same time.
What you will do
- Profile real-looking files and log data quality problems with exact counts
- Reconcile two sources that disagree and explain the gap to the last order and the last pound
- Handle a stakeholder who redefines a KPI, a CRM merge that duplicates customers and a tracking outage
- Test whether a fall is real, say plainly when it is not significant, and refuse to overclaim
- Hand over a pack of method, definitions, memo and dashboard review that someone else can repeat
The people you deal with
- Head of Analyticscompany
- Senior Data Analystcompany
- Data Engineercompany
- Head of Customer Growthclient
- Finance Analystclient
- CRM Ownerclient
- Operations Managerclient
- Data Protection Leadcompany
The company, client and site are fictional. The people are fictional too.
Look inside
What the simulator looks like
The workplace, your tickets, the documents and the team chat, as a learner sees them.
Start in the workplace, with the team around you. 
Today: the morning email and your tickets for the day. 
Work: every ticket, by day, with its status. 
A ticket, written the way a colleague would write it. 
A project document with its number, revision and status. 
Ask a colleague. They are AI colleagues: they help you think, they do not hand out answers.
Screenshots from the simulator. Company, people and data are fictional. Portraits are AI-generated.
Meet the team
The colleagues you work with
You can read their messages and ask them questions. They are AI colleagues, clearly labelled. They help you think a ticket through; they do not hand out its answer.
- HSHarpreet SandhuHead of AnalyticsSimulated colleague, company side
- AOAmara OkoroSenior Data AnalystSimulated colleague, company side
- PWPiotr WisniewskiData EngineerSimulated colleague, company side
- KVKit VasquezFormer analystSimulated colleague, company side
- EPEsther PlummerData Protection LeadSimulated colleague, company side
- FRFrancesca RossettiHead of Customer GrowthSimulated colleague, client side
- DPDominic ParryFinance AnalystSimulated colleague, client side
- RSRuth SutcliffeCRM OwnerSimulated colleague, client side
Fictional people. Portraits are AI-generated.
What you get
What you walk away with
Answer a real business question with messy data: profile, reconcile, check queries, test a change and write the pack.
What you produce
Data profile of the four source files
Data profile
Reconciliation of orders: shop system against finance
Reconciliation
Review comments on the repeat-rate SQL query
Code review
Data quality checks logged
Data quality log
End-of-week status email
Stakeholder update
Impact note for a metric change request
Change controlPremium
Final KPI definition sheet
Metric definitionsPremium
Analysis pack for the retention question
CapstonePremium
Skills you practise
- Analysis and statistics
- Data cleaning and quality
- Written communication
- SQL and querying
- Data protection and privacy
- Presenting findings
- Working with clients and stakeholders
- Applying standards
Roles to look for
- Data Analyst
- Junior Data Analyst
- Insight Analyst
- Reporting Analyst
- Business Intelligence Analyst
50 live openings on the UK jobs board, checked 24 Oct 2026. See the jobs
Your proof
- A certificate anyone can verify. Optional, and included in Premium.
- An entry on your EDWartens profile under Work experience, marked as a job simulation.
- A work record with your skill scores, with Premium.
Free courses that go with it
What you can talk about at interview
- You can explain how you profiled four messy files and what you found before you trusted any of them.
- You can walk through reconciling two sources and why you reported the gap instead of picking one.
- In Premium, you can talk through a changed KPI definition, a significance test and a request to share a customer list.
Day by day
Days 1 to 5, ticket by ticket
Self-paced. A day opens when you hand in the previous day's tickets. Every ticket is checked, and you see the model answer after it.
Day 1
about 1 h 55 min- Induction: working standards and personal dataQuiz · 45 min
- Profile the four filesTable · 1 h 10 min
Day 2
about 2 h 35 min- Reconcile August orders: shop system against financeCalculation · 1 h 15 min
- Review the repeat-rate queryDocument review · 1 h 20 min
Day 3
about 1 h 30 min- Count active customers: v1 and v2Calculation · 1 h
- The definition changes: what happens to the dashboard?Decision · 30 min
Day 4
about 2 h 30 min- Run the eight data quality checksTable · 1 h 20 min
- How much damage did the CRM merge do?Calculation · 1 h 10 min
Day 5
about 1 h 20 min- Fill the blank sources with "email"?Decision · 35 min
- End-of-week status emailWriting · 45 min
Premium: days 6 to 20about 23 h more
After day 5 the project goes on with a change request, site work, faults, a handover and a capstone reviewed by an engineer.
Day 6
about 2 h 20 min- "Just give me the number by noon"Decision · 30 min
- Repeat customer rate by region, August and SeptemberTable · 1 h 50 min
Day 7
about 1 h 15 min- Conversion rate and the tracking outageCalculation · 1 h 15 min
Day 8
about 1 h 40 min- Impact note for change request CR-02Writing · 1 h 40 min
Day 9
about 1 h 30 min- Recalculate the repeat customer rate under v3Calculation · 1 h 30 min
Day 10
about 1 h 20 min- Is the London fall real? A two-proportion z-testCalculation · 1 h 20 min
Day 11
about 1 h 40 min- Bridge the dashboard revenue to the finance figureTable · 1 h 40 min
Day 12
about 1 h 30 min- Do January and March customers come back?Calculation · 1 h 30 min
Day 13
about 35 min- The agency wants the customer list in the next hourDecision · 35 min
Day 14
about 1 h 20 min- Review the dashboard specification before go-liveDocument review · 1 h 20 min
Day 15
about 1 h 10 min- Finalise the KPI definition sheetTable · 1 h 10 min
Day 16
about 1 h 30 min- Check the draft findings memoDocument review · 1 h 30 min
Day 17
about 1 h 20 min- The one-page note for the Head of Customer GrowthWriting · 1 h 20 min
Day 18
about 4 h- Capstone: the analysis pack for DATA-142Hand-in · 4 h
Day 19
about 1 h- Handover email to the Head of Customer GrowthWriting · 1 h
Day 20
about 50 min- A conversation about your own workViva · 50 min
Real documents
The documents you will work with
Each one has a number, a revision and an approver, the way a project document does. You read them, check them and write your own.
DATA-TKT-142
Ticket DATA-142: why did repeat orders fall in September?
Rev ATicket
DATA-STD-001
Insight team working standards (one page)
Rev BStandard
DATA-DDC-001
Data dictionary for the retention analysis
Rev 0.3Data dictionary
DATA-KPI-001
KPI definition sheet
Rev AKPI definitions
DATA-KPI-001
KPI definition sheet, with active customer v2
Rev BKPI definitions
DATA-SQL-001
q_repeat_orders_v2.sql
Rev BSQL query file
DATA-DQL-001
Data quality log
Rev AData quality log
Documents that arrive in Premiumchange requests, records, handover
DATA-CHG-002
Change request CR-02: repeat customer rate v3
Rev AChange requestPremium
DATA-KPI-001
KPI definition sheet, with repeat customer rate v3
Rev CKPI definitionsPremium
DATA-FIN-001
Finance monthly revenue summary, September
Rev AFinance reportPremium
DATA-DSH-001
Dashboard specification: customer health
Rev ADashboard specPremium
DATA-MEM-001
Findings memo: repeat customers in September
Rev AFindings memoPremium
DATA-HOV-001
Handover pack requirements
Rev AHandover indexPremium
DATA-DEC-001
Decision log
Rev CDecision logPremium
Tools
In the industry, and here
| In the industry | Here |
|---|---|
| SQL client or a database tool | Your own SQL tool, such as an in-browser or desktop SQL engine, on the downloaded files |
| Spreadsheet (pivot tables, lookups) | Your own spreadsheet, on the same CSV files |
| Python with pandas or R for cleaning and statistics | Your own notebook; every answer can also be found with SQL or a spreadsheet |
| Dashboard tool and a ticket tracker | A dashboard specification you review, and numbered tickets in the inbox |
Standards
The standards the work follows
- CRISP-DM
- DAMA data quality dimensions
- UK GDPR
In the UK
The Data Analyst role in a UK setting
Who employs this kind of engineer: Retailers, banks, insurers, utilities, the NHS, local and central government, consultancies and software companies.
Where: Analyst roles are advertised in every UK region, and many are hybrid or remote. This is context, not a statement about vacancies.
UK standards and regulations to know about
UK GDPR and the Data Protection Act 2018
The rules for personal data. The ICO publishes guidance, including on AI and data protection.
ICO guidance on anonymisation
How to share and analyse data about people without identifying them.
Government Analysis Function standards
Standards for analysis in UK government, useful context for public sector roles.
CRISP-DM
A common process model for data projects.
These are named so that you recognise them. A job simulation does not teach them as a qualification, the tasks use simplified data, and you should always read the current edition of anything you rely on.
Your proof, optional
A certificate you can verify
The free days are free. The graded, verifiable certificate is an optional extra, and it is included in Premium.
- A graded, verifiable certificate with your score and band
- A public verification page and QR code
- One-click add to LinkedIn as a licence or certification
- Issued by WARTENS LTD. It is a training certificate, not an accredited qualification, and the company is simulated
Optional: £14.99 including VAT, once you pass.
Job Simulation Certificate
Your name
completed the Data Analyst job simulation at Fernhollow Home Ltd (simulated company). Your score and band are shown on the real certificate.
- Number
- EDW-JS-0000
- Issued by
- WARTENS LTD
Not an accredited qualification. A verification page and QR code are printed on the real certificate.
Prepare
Free courses and labs that get you ready
Linked from the tickets that need them. You can read them before you start.
Free courses
- Excel for Engineers: Formulas, Data and Dashboards
- SQL for PLC and SCADA Engineers
- Python for AI and Engineering Data
- AI Essentials for Work: ChatGPT, Claude, Gemini and Copilot
- Industrial Data with Python
- Power BI for Manufacturing: OEE and Production Dashboards
- Power BI Data Analyst (PL-300 Prep)
- ISO 42001 and AI Governance
A course that goes with this role
AI Module
A paid, self-paced course in AI and machine learning for industry: 83 lessons, 5 graded projects and career sessions. It is a separate product: you do not need it to finish the job simulation, and it does not lead to a job. The certificate is a certificate of completion, not a regulated qualification.
- Price
- £2,688 including VAT (£2,240 + VAT); or start with a £100 deposit
- Format
- Self-paced online, 12 months' access
About the Data Analyst role
What the data looks like
Real data is untidy. The simulation gives you four files from a simulated online retailer with the kinds of problems analysts meet every week: duplicate customers after a CRM merge, a tracking outage that deflates conversion, and blank values someone wants to fill with a guess.
You profile the files and log the problems with exact counts, run eight data quality checks and measure how much damage the merge did. You can use a spreadsheet, SQL or Python, since every answer can be found with any of them.
The manager's question, and what a strong answer includes
The ticket asks why repeat orders fell in September. A weak answer reports a single number. A strong one defines the measure, shows the reconciliation, says what is uncertain and recommends an action.
You reconcile August orders between the shop system and finance, count active customers under two definitions, and later test whether a fall in one region is real with a two-proportion test. When a stakeholder wants a number by noon, or the KPI is redefined mid-project, the task is to protect the method and say so plainly.
Changing definitions, privacy and honest limits
Good analysts handle change without losing trust. A change request redefines the repeat customer rate, and you recalculate, update the definition sheet and note the effect on the dashboard.
An agency asks for the customer list within the hour, which tests your handling of personal data under UK GDPR. A test of significance may show a fall is not significant, and the correct finding is to say that, not to overclaim. The data dictionary, KPI sheet and decision log are the documents that make your work repeatable.
What to write on your CV
List the simulation under Projects, Training or Job simulations, never under Work experience in a way that suggests employment. Name the task, the tools you used and the result.
A sample line: Reconciled two order sources and found a CRM merge that duplicated customers, then reported repeat customer rate under three definitions in a one-page memo. On your EDWartens profile it shows under Work experience, marked as a job simulation, with the simulated company named.
Keep it factual and short, and link to the pack if you publish it.
What to learn next
The usual next steps are SQL for joins and window functions, a dashboard tool, and Python or R for statistics. A related role, the machine learning engineer, builds on the same data discipline.
The linked free courses cover spreadsheet working, SQL, Python for engineering data and dashboard design. Pair the simulation with one project of your own on data you chose.
Choose one question of your own, such as why a local service is late, and repeat the method on public data. Two projects with different data show you can transfer the skill, not only follow a script.
Keep going
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Content reviewed 19 Oct 2026; UK context added 21 Oct 2026. Practice, not employment.
Questions
Quick answers
Is a data analyst job simulation worth doing?
It is worth it as practice evidence, not as a substitute for experience. Simulation providers generally say their programmes are not employment and belong in a projects or certifications section. The strongest version is one where you produce a deliverable you can show.
Can I put a job simulation on my CV?
Yes, under Projects, Training or job simulations, and not as employment. Name the task, the tools and the result, and name the simulated company.
Are free data analyst simulations enough to get hired?
On their own, rarely. A simulation shows you can follow a brief, and employers also look for SQL, Python or a BI tool and a documented project. Pair it with one project built on messy data and a written recommendation.
How long does the simulation take?
Days 1 to 5 are free and self-paced, and each ticket lists an honest time estimate, including the cleaning step. The role page shows the total for the free days.
What tools do I need?
A spreadsheet, SQL or Python or R will all do, and you work in your own tools on downloaded files. A dashboard tool helps for the specification review but is not required.
What is the difference between a job simulation and a virtual internship?
A simulation is a self-paced project with checked tasks. A virtual internship usually runs over weeks with several projects. Many learners do the simulation first, then the free four week internship in data science.
Where can I get messy real data to practise on?
Public sources include government and development agency open data portals. The simulation ships its own files with deliberate problems, so you do not need to hunt for them.
What do data analysts earn in the UK?
UK advertisements for data analyst roles show a median salary of £45,000, with the middle half between £35,000 and £60,000, for vacancies in the six months to 26 July 2026. This covers IT vacancies only, and pay varies by country, sector and experience.
Source: ITJobsWatch, Data Analyst (UK IT vacancies) (opens in a new tab), checked 19 Oct 2026.
Do I need to know SQL or Python first?
It helps, but you can do every task with a spreadsheet. The study links on each task point to free lessons on SQL, spreadsheets and Python. You work in your own tools on the files you download.
Is this a real company and real data?
No. Fernhollow Home is a made-up company and the data is synthetic, generated with planted problems. The documents, tickets and situations follow what a junior analyst meets on a real team.
How long does it take?
The free week is about ten hours of work spread over five days. The full Premium edition runs over twenty working days and roughly thirty to forty hours, at your own pace.
Which tools do I have to use?
None in particular. The answers are checked as numbers, so you can use a spreadsheet, SQL or Python, whichever you know.
What do I get at the end?
A work record with your scores by task and skill, which shows on your EDWartens profile under Work experience, marked as a job simulation.
Is the Data Analyst job simulation free?
Yes, to start. Days 1 to 5 are free. The certificate (£14.99) and the Premium edition (£53.99) are optional, and both prices include VAT.
Does it count as work experience?
No. It is a training project at a simulated company, not employment, an internship or a placement. A job simulation is a realistic training project at a simulated company. It is not employment, an internship or a work placement, and it is not a job offer. Hours are active hours the learner logged on EDWartens UK.
A job simulation is a realistic training project at a simulated company. It is not employment, an internship or a work placement, and it is not a job offer. Hours are active hours the learner logged on EDWartens UK.
Start the Data Analyst job simulation today
Days 1 to 5 are free. No card to start. Practice, not employment.