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Data Analyst job simulation

Join the insight team of an online retailer as a junior analyst: reconcile two sources, clean the data, handle a changing KPI and present honest findings.

Data Analyst job simulation
  • Free: days 1 to 5, about 9 h 50 min of tickets
  • Premium: days 1 to 20
  • Checked as you go
  • Reviewed 19 Oct 2026

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 (simulated company), 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.

The people in the story are roles, such as Lead Engineer, not real people.

What you will do

By the end you will have

  • 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

Day by day

The plan, ticket by ticket

Self-paced. A day opens when you hand in the previous day's tickets.
Data Analyst job simulation plan
DayTicketKindTimeEdition
1Induction: working standards and personal dataQuiz45 minFree
1Profile the four filesTable1 h 10 minFree
2Reconcile August orders: shop system against financeCalculation1 h 15 minFree
2Review the repeat-rate queryDocument review1 h 20 minFree
3Count active customers: v1 and v2Calculation1 hFree
3The definition changes: what happens to the dashboard?Decision30 minFree
4Run the eight data quality checksTable1 h 20 minFree
4How much damage did the CRM merge do?Calculation1 h 10 minFree
5Fill the blank sources with "email"?Decision35 minFree
5End-of-week status emailWriting45 minFree
6"Just give me the number by noon"Decision30 minPremium
6Repeat customer rate by region, August and SeptemberTable1 h 50 minPremium
7Conversion rate and the tracking outageCalculation1 h 15 minPremium
8Impact note for change request CR-02Writing1 h 40 minPremium
9Recalculate the repeat customer rate under v3Calculation1 h 30 minPremium
10Is the London fall real? A two-proportion z-testCalculation1 h 20 minPremium
11Bridge the dashboard revenue to the finance figureTable1 h 40 minPremium
12Do January and March customers come back?Calculation1 h 30 minPremium
13The agency wants the customer list in the next hourDecision35 minPremium
14Review the dashboard specification before go-liveDocument review1 h 20 minPremium
15Finalise the KPI definition sheetTable1 h 10 minPremium
16Check the draft findings memoDocument review1 h 30 minPremium
17The one-page note for the Head of Customer GrowthWriting1 h 20 minPremium
18Capstone: the analysis pack for DATA-142Hand-in4 hPremium
19Handover email to the Head of Customer GrowthWriting1 hPremium
20A conversation about your own workViva50 minPremium

Real documents

The documents you will work with

Project documents
NumberDocumentRevEdition
DATA-TKT-142Ticket DATA-142: why did repeat orders fall in September?AFree
DATA-STD-001Insight team working standards (one page)BFree
DATA-DDC-001Data dictionary for the retention analysis0.3Free
DATA-KPI-001KPI definition sheetAFree
DATA-KPI-001KPI definition sheet, with active customer v2BFree
DATA-SQL-001q_repeat_orders_v2.sqlBFree
DATA-DQL-001Data quality logAFree
DATA-CHG-002Change request CR-02: repeat customer rate v3APremium
DATA-KPI-001KPI definition sheet, with repeat customer rate v3CPremium
DATA-FIN-001Finance monthly revenue summary, SeptemberAPremium
DATA-DSH-001Dashboard specification: customer healthAPremium
DATA-MEM-001Findings memo: repeat customers in SeptemberAPremium
DATA-HOV-001Handover pack requirementsAPremium
DATA-DEC-001Decision logCPremium

Tools

In the industry, and here

In the industryHere
SQL client or a database toolYour 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 statisticsYour own notebook; every answer can also be found with SQL or a spreadsheet
Dashboard tool and a ticket trackerA dashboard specification you review, and numbered tickets in the inbox

Standards

The standards the work follows

  • CRISP-DM
  • DAMA data quality dimensions
  • UK GDPR

Prepare

Labs and study materials

Free, and linked where a ticket needs them.

Study before you start

What you get

Free, certificate and Premium

Free

Days 1 to 5, every ticket checked, model answers, the 3D lab and a profile entry.

Free

Certificate (optional)

  • 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
  • A Verified mark on your profile entry

₹499

Premium

Premium job simulation

  • The full four-week project: change requests, site work, faults and handover
  • A capstone deliverable reviewed by an engineer
  • An AI viva on your own work
  • The graded certificate and a work record PDF with your skill scores
  • Priority help from our team
₹1,499The certificate is included. If you bought it, its price is credited.

On your profile

How it shows on your profile

It shows on your EDWartens profile under Work experience, marked as a job simulation.

Work experience

Data Analyst (job simulation)

Fernhollow Home Ltd (simulated company)

9 h 50 min active hours logged · Your dates

Verified, with the certificate

A job simulation is a realistic training project at a simulated company. It is not employment, an internship or a work placement. Hours are active hours the learner logged on EDWartens.

Questions

Quick answers

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 and the Premium edition are optional and are priced on this page in your currency.

Does it count as work experience?

It shows on your EDWartens profile under Work experience, marked as a job simulation. It is not employment. A job simulation is a realistic training project at a simulated company. It is not employment, an internship or a work placement. Hours are active hours the learner logged on EDWartens.

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Last reviewed 19 October 2026.