Data Cleaning.

Clean, connected data — so every decision starts with complete confidence.

Clean data. Confident decisions.

If your teams can’t trust the data they’re working with, every decision feels like a guess. Our data cleaning services bring clarity and confidence back to your data — removing errors, filling gaps, and ensuring every record gives you the complete picture you need.

What we cover.

Eliminate errors, reduce risk and gain confidence in every record.

Deceased flagging

We flag deceased individuals to prevent distressing communications and protect your brand’s reputation.

Goneaway identification

We detect people who no longer live at the listed address — saving costs and improving deliverability.

Movers suppression

We flag individuals who’ve moved and provide new address details where available — helping you stay connected.

Deduplication

We remove duplicate records to cut down on unnecessary contacts and ensure a cleaner, more efficient database.

Validation

We verify and correct key contact fields — like name, address and phone — for better accuracy and reliable segmentation.

Wealth profiling

We help you identify high-value supporters or prospects — giving you the insights to target your premium campaigns more effectively.

Compliance screening

We screen your database against suppression lists like MPS and TPS, helping you stay compliant and avoid contacting those who’ve opted out.

Why choose us for data cleaning?

We have access to the UK’s best cleaning files sourced from trusted, reliable providers, ensuring your data is accurate and up to date. Our team specialises in working with charities, non-profits, and commercial clients, bringing sector-specific expertise to every project.

You’ll benefit from a seamless, user-friendly experience, with the entire process managed by us, from start to finish. Our friendly and flexible service is tailored to fit your timelines and individual needs.

Don't just take our word for it...

"Before working with Migrate Data, we struggled to fully leverage our data ahead of a planned campaign, making it difficult to allocate resources effectively. Their data cleansing services have significantly improved our data quality, strengthening departmental confidence and enabling us to build a ‘donor pyramid’ using wealth-tags. Since partnering with Migrate Data, we've seen improved accuracy and better decision-making. The team is incredibly easy to work with— flexible, always adaptable, and quick to implement changes. Their responsiveness and efficiency make them a valuable partner, and we would highly recommend their services."

"Trussell used Migrate Data Ltd to migrate all data when implementing a new CRM in 2016 and then on various projects, most recently on regular data cleaning. We have always found them very efficient, reliable and responsive to any questions. They are always our go to for any migration or data cleaning jobs and we would recommend them unreservedly."

"We have been using Migrate Data to clean our supporter data for many years. They have a reliable portfolio of cleaning files and other products that cater for our requirements. We have always found them to be friendly, efficient, and very helpful. More importantly, they can be very adaptable as our timings can often present a challenge. Children With Cancer would not hesitate in recommending Migrate Data wholeheartedly for any data cleaning or data migration services. "

Unsure where to start with cleaning your data?

Get expert advice on what to clean — and how to make it stick.

Frequently asked questions.

What is data cleaning?

Data cleaning, also known as data cleansing is the process of identifying and correcting (or removing) inaccurate, incomplete, incorrect, or irrelevant data from your data.

Why is data cleaning important?

Clean data is essential for making reliable business decisions. Poor quality data can lead to inaccurate analysis, flawed insights, and costly mistakes.

Cleaning data improves:

Data accuracy – so reports and dashboards reflect the truth.
Efficiency – by reducing time spent manually correcting errors.
Compliance – especially in industries with strict data regulations.
Customer experience – through more accurate communication and personalization.

What types of data issues does cleaning address?

Data cleansing tackles a wide range of common problems in datasets, including:

Duplicates: Multiple records that refer to the same entity (e.g., the same customer entered twice).
Missing values: Fields with no data, which can cause errors in analysis or reporting.
Inconsistent formats: Different ways of recording the same data (e.g., “NY” vs “New York” or date formats like “2025-07-08” vs “08/07/2025”).
Typos and spelling errors: Human-entered mistakes in names, addresses, etc.
Outliers and anomalies: Unusual values that may indicate entry errors or special cases needing attention.
Incorrect values: For example, a negative age or an email address with no “@” symbol.