Data Cleansing Service UK

Bad data is costing you more
than you realise.

Duplicate records. Inconsistent formats. Figures that do not reconcile. Bad data breaks reports, undermines automation, and costs UK businesses an average of 20% of their annual revenue. We fix it — fast, properly, and with a process to keep it clean.

Book a free scoping call →See pricing →
2-5
Days to delivery
Free
Scoping call
48h
Quote turnaround

Automation built on bad data fails. Every time.

The most common reason an automation or reporting project underdelivers is not the tool — it is the data feeding into it. A Power BI dashboard connected to inconsistent data shows inconsistent numbers. An Excel automation built on duplicated records produces duplicated outputs. The fix is not a better tool. It is cleaner data.

Reports that show different numbers depending on who runs them
Duplicate customers, contacts, or records across systems
Dates, postcodes, or values in inconsistent formats
Figures that do not reconcile between your systems
Automation that breaks because the source data changed format
Decisions made on data nobody quite trusts

Data cleansing for every type of problem

From a single messy spreadsheet to a full multi-system data quality project — scoped and priced before any work begins.

🗂️

Duplicate Removal

Identify and merge duplicate records across your datasets — customers entered twice, products with multiple codes, contacts duplicated across systems. Clean once, reliable forever.

📅

Date & Format Standardisation

Dates in six different formats, phone numbers with and without country codes, postcodes in inconsistent cases. We standardise everything so your data behaves predictably.

🔗

Cross-System Reconciliation

Data that lives in multiple systems and does not match up. We identify the discrepancies, resolve the conflicts, and set up processes to keep them in sync going forward.

🧹

Missing Data Handling

Blank fields that break your reports and formulas. We identify what is missing, fill what can be inferred, flag what needs manual input, and validate what remains.

Validation & Rules

Build validation logic into your data entry process so bad data cannot enter the system in the first place. The right fix for recurring data quality problems.

📊

Pre-Automation Cleansing

Before any automation project, we audit and clean the source data. Automation built on bad data produces wrong outputs fast. We fix the foundation first.

Data cleansing is not glamorous. It is foundational.

Every automation project we build starts with a data audit. Before writing a single line of code or building a single query, we look at the source data and ask: is this clean enough to build on? In around half of all projects, the answer is no — and the cleansing work happens first.

This is not a problem. It is just part of the process. A business that has been running for several years on manual data entry will almost always have inconsistencies that have built up over time. Cleaning them properly — once, with a structured approach — gives you a foundation that everything else can be built on reliably.

We use Power Query for Excel and Power BI data, Python for large datasets and complex logic, and SQL for database-level work. In every case the cleaning steps are documented so they can be reapplied automatically when new data arrives — not just done once and forgotten.

Our data cleansing process

1
Data audit — we assess the scale of the problem and identify exactly what needs fixing.
2
Fixed price quote — you know the full cost before any work begins.
3
Cleansing — we clean the data using the right tool for the job.
4
Validation — we check the output against your business rules to confirm it is correct.
5
Documentation and handover — we explain what was done and how to keep the data clean.

Read our guide to what data cleansing is and why it matters for UK businesses — including the real cost of bad data.

Hairdressing group: scattered data consolidated and working

Health & Beauty · Owner-managed business

The situation

Financial data scattered across multiple disconnected spreadsheets. Inherited macros from a previous consultant that either failed entirely or took so long to run nobody used them. The owner had no reliable view of business performance.

What we did

Full data cleanse and restructure across all spreadsheets — standardising formats, removing inconsistencies, and connecting the data properly. Then rebuilt every macro from scratch: faster, reliable, and documented so the team could understand and maintain it.

100%
Macros rebuilt and working
1 file
Single source of truth
0
Manual reconciliation required

Questions about data cleansing

Anything not covered here — just ask us directly.

How do I know if my data needs cleansing?

The most common signs are reports that produce different results depending on who runs them, formulas that break when data is updated, duplicate customers or records in your system, figures that do not reconcile between systems, and automation projects that fail because the data is inconsistent. If any of these sound familiar, a data audit will tell you exactly what needs fixing.

What tools do you use for data cleansing?

We use Power Query for Excel and Power BI data, Python with Pandas for large datasets and complex logic, and SQL for database-level cleansing. The right tool depends on where your data lives and the scale of the problem. We will tell you which approach makes sense for your situation during the scoping call.

Can you clean data in any format?

Yes — Excel, CSV, SQL databases, Google Sheets, and exports from most common business software including Xero, Sage, Salesforce, and HubSpot. If the data is accessible digitally, it can be cleaned.

Will the data stay clean after the project?

A one-time clean without fixing the process that created the bad data will accumulate problems again over time. We always recommend addressing the root cause — whether that is validation rules at the point of entry, integration between systems, or a structured data entry process — alongside the cleansing work itself.

How long does data cleansing take?

A single dataset with straightforward issues is typically delivered in 2-5 working days. Larger, more complex cleansing projects involving multiple systems or significant reconciliation work take longer. We scope every project and give a fixed price before any work begins.

Do you work remotely?

Yes — all work is delivered remotely. We work with businesses across the UK and internationally.

Not sure how clean
your data actually is?

Book a free 30-minute call. We will look at your data, tell you exactly what the quality issues are, and give you a fixed price to fix them before any work begins.

Book your free scoping call →

Delivered in 2-5 days · Full documentation included