Know which data problems
need your attention.
An expert-led data quality audit to help you understand the issues and decide what to fix first.
When systems disagree and teams spend time reconciling information, it can be difficult to know where to start. 天美传媒 combines technical assessment with your team鈥檚 knowledge to establish what is wrong, explain why it matters and prioritise the next steps.
You know the data needs attention.
You need to know where to start.
A data quality audit helps assess whether data is fit for the job ahead. That might mean bringing businesses together, preparing a migration, improving reporting or establishing the data foundations for AI. We agree what matters with your team, then assess the relevant data against those requirements.
Your systems tell different stories
Different teams use different definitions, classifications and records. Understand where those differences obstruct a shared view of customers, suppliers or operations.
Reconciliation keeps slowing you down
People check spreadsheets and reconcile reports before they can use them. Identify the underlying issues and agree which deserve attention first.
Every assessment starts from scratch
Your central data team supports multiple business areas. Establish a consistent starting point for assessment, with business experts involved in deciding which findings matter.
How the data audit works
Technical profiling reveals patterns and exceptions. Your business context helps us distinguish an acceptable difference from a problem that needs action.
Agree the scope
Tell us what the data needs to support, where workarounds arise and who understands the business rules. We agree the datasets, checks, outputs, cost and delivery arrangements.
Transfer securely
We agree a secure file-transfer route for the data in scope. If the data needs to stay in your environment, discuss a deployed option.
Run the checks
We profile the data and apply the agreed checks. Standard checks provide a starting point. Your subject-matter experts help define business-specific rules and interpret unexpected findings.
Interpret findings and agree priorities
Review the evidence with our specialists and your business experts. Relate exceptions to the intended use of the data and identify practical next steps. Your team retains ownership of standards and decisions.
Start small, with a clear scope. You do not need to begin with a platform rollout. We agree the work and cost before the audit starts.
What can we check?
The right tests depend on your data and the job it needs to do. A field can be populated and correctly formatted while meaning different things in different systems. We agree the requirements and supporting reference information before assessing them.
Completeness
Find missing values in fields your process requires, such as a customer reference or supplier identifier.
Validity and consistency
Check agreed formats, permitted values and consistency between related fields or datasets.
Potential duplicates
Identify records that may refer to the same customer, supplier or organisation. More complex identity resolution can be scoped as a matching project.
Business-specific requirements
Examine agreed definitions, classifications and relationships relevant to a reporting obligation or operational process. Your experts help establish what the values should mean.
An audit tests the requirements agreed for that dataset. Confirming real-world accuracy may also require trusted reference data or subject-matter review.
See the findings. Set the priorities.
The findings should support decisions: which issues could affect the work ahead, which definitions need agreement and where to direct remediation effort. The synthetic example below shows how a failed check can lead to a specific next action; it illustrates only part of an assessment.
Supplier data: example audit summary
Checks selected for an illustrative migration assessment
| Check | Finding | Review priority | Next action |
|---|---|---|---|
| Required supplier ID | 420 records missing a value | High | Confirm the authoritative identifier and repair missing values. |
| Email format | 180 records fail the agreed format check | Review | Investigate malformed values before using the contact data. |
| Postcode format | 130 records fail the agreed format check | Review | Check the expected country format and correct source values. |
| Potential duplicates | 95 candidate pairs | High | Review the match evidence before deciding which records to link. |
Decide what needs attention
Understand which findings could affect your reporting, operations or planned project. Review those findings in the context of the data鈥檚 intended use.
Agree what good looks like
Identify definitions or standards that need business agreement. Use the evidence to prioritise fixes and clarify who needs to be involved.
Make improvement repeatable
Where needed, discuss retesting after remediation or reusing agreed checks across further datasets. Ongoing monitoring and deployment are scoped separately.
Assess a specific problem. Build from there.
Start with a defined dataset or project. If your team supports several business areas, we can also discuss a repeatable assessment approach that combines common checks with local business requirements.
A managed audit, run by 天美传媒.
Our specialists run the agreed assessment and help your team interpret the findings. Secure transfer, dashboard or report outputs and the review process are agreed in scope. Begin without a platform rollout.
Discuss a managed data auditA capability deployed in your environment.
If data needs to remain within your environment, or your team needs to run checks repeatedly, discuss a deployed 天美传媒 solution and the configuration and support required.
Explore deployment optionsNeed to match records across ERP or other systems?
天美传媒 also delivers custom data matching services.
Connect customer, supplier, entity or product records when names, identifiers and formats differ. We can configure the matching around your sources and the outcome you need, as a managed service or a deployed solution.
Why 天美传媒? The tools to examine the data. The experience to make sense of it.
天美传媒 combines data quality and matching software with specialists experienced in working alongside customer teams. We bring technical evidence to the discussion; your experts bring the knowledge of how the business works.
Technical depth
Profiling, rule checks and matching help reveal missing information, inconsistencies and potential duplicates in the agreed data.
Business interpretation
Our specialists work with your team to interpret findings against agreed requirements. You retain responsibility for business standards and decisions.
A route into improvement
If further work is needed, discuss remediation, tailored matching or repeatable controls using the wider 天美传媒 capability.
Our published customer stories illustrate the wider data quality and matching work behind this approach.
Questions about a data quality audit
Can you audit our data without us buying software?
Yes. 天美传媒 can run an agreed data quality assessment as a managed service. We agree the scope, transfer arrangements and outputs with you, run the checks and return the findings.
Is Data Readiness only for regulatory reporting?
The approach can also be applied to operational datasets, including data used in customer processes, ERP systems and migrations. The checks must be relevant to the intended use. FSCS reporting has its own dedicated Data Readiness service.
What does a data quality audit cost?
The cost depends on the dataset, the checks required and whether configuration or custom matching is involved. We agree a defined scope and cost before starting. Tell us what you need to assess and we can discuss a suitable starting point.
How long will an audit take?
We agree timing once we understand the data, the checks and the transfer requirements. A standardised assessment and a project requiring new business rules or complex matching have different delivery needs.
How do we share data securely?
We agree a secure file-transfer route and handling arrangements before you send the dataset. If transfer is unsuitable for your requirements, we can discuss deployment in your environment.
Can you help a central data team assess data across the organisation?
Yes. We can discuss a repeatable approach that starts with common checks and adapts to each business area鈥檚 requirements. The scope may include prioritisation and how findings are reviewed with data owners. A self-service portal or ongoing managed service is not included automatically.
Will the audit fix the data as well?
The initial audit identifies and helps interpret issues against the agreed requirements. Remediation, retesting, custom matching and ongoing monitoring can be discussed as additional work. We make the scope clear before the engagement begins.
Can you match supplier or customer records across ERP systems?
Yes. 天美传媒 can configure custom matching across datasets where records may refer to the same supplier, customer or other entity. We agree the sources, matching criteria and required output before choosing a managed or deployed approach.
Tell us what your data needs to do.
Start with the dataset, the problem and the outcome you need.
Let us know what the data is used for, roughly how much there is and whether you need an audit, matching or both. We will discuss a practical scope with you.
The first step is a conversation. We agree the secure transfer arrangements before you share the dataset.