WHY ENGLISH?
Turn validation checks into a transparent data-quality report that tells readers what was tested, which rules failed, what the failures mean and what happens next
Writing a data validation report means defining the dataset and intended use, naming the validation rules, measuring completeness, validity, consistency and uniqueness where relevant, documenting exceptions, preserving evidence and assigning remediation. English matters because a result such as 98% complete is useful only when the denominator, required fields, exclusions, date and acceptable threshold are clear.
The UK Government Data Quality Framework describes data quality as fitness for purpose and distinguishes completeness, uniqueness, consistency, timeliness, validity and accuracy. Its supporting guidance recommends rules aligned with user needs, baseline assessment, suitable metrics and clear communication of quality issues. A validation report should therefore explain the decision context as well as the check output.
This guide follows a fictional export of course-enrolment records used to prepare an internal planning summary. It does not alter source data, decide legal retention, approve access, certify every value as true, infer missing facts or promise that one clean run makes a dataset permanently fit for every use.
Article contents
Open all chapters
- 1. Name the Dataset Snapshot and Intended Decision
- 2. Translate Requirements Into Explicit Validation Rules
- 3. Define Population, Exclusions and Denominators
- 4. Measure Completeness Without Confusing It With Accuracy
- 5. Test Validity Against Formats, Ranges and Allowed Values
- 6. Check Consistency Across Fields, Records and Sources
- 7. Assess Uniqueness With a Defined Entity Key
- 8. Separate Accuracy, Timeliness and Other Checks
- 9. Present Exceptions With Reproducible Evidence
- 10. Prioritise by User Impact and Risk
- 11. Assign Remediation, Ownership and Revalidation
- 12. Conclude Fitness for Use With Dated Limits
ORIENTATION
What this guide covers
Current fact check
Checked on 9 November 2026, the UK Government Data Quality Framework defined six dimensions—completeness, uniqueness, consistency, timeliness, validity and accuracy—and stressed user needs, lifecycle assessment, clear communication, documentation and continuous improvement. Its official guidance advised defining realistic data-quality rules, measuring priority checks with suitable metrics, reporting missingness and duplicates, describing unresolved inconsistencies and informing users about validity, accuracy and trade-offs.
What this guide does not cover
This article covers planning, writing, reviewing and updating a data validation report for an authorised dataset and named use. It does not cover collecting personal data, granting access, changing master records, data cleaning execution, statistical analysis, database migration, security certification, regulatory advice, records disposal or claiming accuracy without an appropriate reference.
Worked example
Every chapter returns to a fictional dated export of course-enrolment records checked before an internal capacity-planning summary, with required student identifiers, allowed status codes, date-order rules and duplicate-record checks. It is fictional, low-stakes and educational; it does not report a real school, clinical decision or guaranteed outcome.
Did You Know? For data validation report, precise communication makes appraisal possible but does not perform the appraisal, remove bias or guarantee transfer.
Warm up with eduKate’s guides to explaining scientific evidence and asking better questions in class.
CHAPTER 1 OF 12
1. Name the Dataset Snapshot and Intended Decision
Why this move matters
Record the source, extraction time, version, row and field scope, authorised owner and the decision the data will support.
Did You Know? Scope prevents a local result from travelling too far.
Define the data, decision and rule authority
Record the source, extraction time, version, row and field scope, authorised owner and the decision the data will support. For The report identifies a 9 November enrolment export used only for next-term capacity planning., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. A later export or a different purpose requires a new assessment.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. A later export or a different purpose requires a new assessment. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Record the source, extraction time, version, row and field scope, authorised owner and the decision the data will support.
- Boundary: A later export or a different purpose requires a new assessment.
- Application: The report identifies a 9 November enrolment export used only for next-term capacity planning. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Name the Dataset Snapshot and Intended Decision” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 2 OF 12
2. Translate Requirements Into Explicit Validation Rules
Why this move matters
Give each rule an identifier, rationale, field or relationship, expected condition, severity and authoritative source.
Did You Know? Rules make checking inspectable.
Define the data, decision and rule authority
Give each rule an identifier, rationale, field or relationship, expected condition, severity and authoritative source. For RULE-ENR-04 requires every active record to contain one permitted programme code., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. A plausible rule is not authoritative merely because an analyst wrote it.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. A plausible rule is not authoritative merely because an analyst wrote it. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Give each rule an identifier, rationale, field or relationship, expected condition, severity and authoritative source.
- Boundary: A plausible rule is not authoritative merely because an analyst wrote it.
- Application: RULE-ENR-04 requires every active record to contain one permitted programme code. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Translate Requirements Into Explicit Validation Rules” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 3 OF 12
3. Define Population, Exclusions and Denominators
Why this move matters
State which records entered each check, which were excluded and why, and how non-applicable values are handled.
Did You Know? Every percentage needs a population story.
Define the data, decision and rule authority
State which records entered each check, which were excluded and why, and how non-applicable values are handled. For Archived records are excluded from the active-contact check but remain in uniqueness testing., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. Do not hide failed records by changing the denominator after seeing results.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. Do not hide failed records by changing the denominator after seeing results. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: State which records entered each check, which were excluded and why, and how non-applicable values are handled.
- Boundary: Do not hide failed records by changing the denominator after seeing results.
- Application: Archived records are excluded from the active-contact check but remain in uniqueness testing. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Define Population, Exclusions and Denominators” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 4 OF 12
4. Measure Completeness Without Confusing It With Accuracy
Why this move matters
Report expected records and required values separately, including intentional blanks and patterns of missingness.
Did You Know? Completeness asks whether expected data are present.
Define the data, decision and rule authority
Report expected records and required values separately, including intentional blanks and patterns of missingness. For Contact-number completeness is 294 of 300 expected active records, while correctness remains unverified., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. A populated field can still contain the wrong value.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. A populated field can still contain the wrong value. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Report expected records and required values separately, including intentional blanks and patterns of missingness.
- Boundary: A populated field can still contain the wrong value.
- Application: Contact-number completeness is 294 of 300 expected active records, while correctness remains unverified. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Measure Completeness Without Confusing It With Accuracy” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 5 OF 12
5. Test Validity Against Formats, Ranges and Allowed Values
Why this move matters
Describe syntax, type, range, reference-list and conditional rules and show failed counts by rule.
Did You Know? Validity checks conformance to expectations.
Define the data, decision and rule authority
Describe syntax, type, range, reference-list and conditional rules and show failed counts by rule. For Three programme codes fall outside the approved reference list and one date is in the future., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. Valid format does not prove that a value matches reality.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. Valid format does not prove that a value matches reality. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Describe syntax, type, range, reference-list and conditional rules and show failed counts by rule.
- Boundary: Valid format does not prove that a value matches reality.
- Application: Three programme codes fall outside the approved reference list and one date is in the future. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Test Validity Against Formats, Ranges and Allowed Values” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 6 OF 12
6. Check Consistency Across Fields, Records and Sources
Why this move matters
Test logical relationships and compare equivalent facts only where source authority and timing are understood.
Did You Know? Consistency reveals contradictions, not automatic corrections.
Define the data, decision and rule authority
Test logical relationships and compare equivalent facts only where source authority and timing are understood. For An enrolment end date precedes its start date, while two systems disagree on programme status., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. A disagreement must be investigated before choosing a winner.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. A disagreement must be investigated before choosing a winner. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Test logical relationships and compare equivalent facts only where source authority and timing are understood.
- Boundary: A disagreement must be investigated before choosing a winner.
- Application: An enrolment end date precedes its start date, while two systems disagree on programme status. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Check Consistency Across Fields, Records and Sources” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 7 OF 12
7. Assess Uniqueness With a Defined Entity Key
Why this move matters
Explain the identifier or matching logic, distinguish exact from suspected duplicates and preserve false-positive review.
Did You Know? Uniqueness depends on entity definition.
Define the data, decision and rule authority
Explain the identifier or matching logic, distinguish exact from suspected duplicates and preserve false-positive review. For Two records share an enrolment ID, while a name similarity is only a review candidate., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. People who share names are not duplicates by default.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. People who share names are not duplicates by default. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Explain the identifier or matching logic, distinguish exact from suspected duplicates and preserve false-positive review.
- Boundary: People who share names are not duplicates by default.
- Application: Two records share an enrolment ID, while a name similarity is only a review candidate. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Assess Uniqueness With a Defined Entity Key” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 8 OF 12
8. Separate Accuracy, Timeliness and Other Checks
Why this move matters
Where evidence allows, compare with an authorised reference and report whether values are current enough for the stated use.
Did You Know? Some quality dimensions require more than schema rules.
Define the data, decision and rule authority
Where evidence allows, compare with an authorised reference and report whether values are current enough for the stated use. For A sampled contact record is checked against a dated verified source and the update lag is recorded., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. Validation alone cannot establish truth without a suitable reference.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. Validation alone cannot establish truth without a suitable reference. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Where evidence allows, compare with an authorised reference and report whether values are current enough for the stated use.
- Boundary: Validation alone cannot establish truth without a suitable reference.
- Application: A sampled contact record is checked against a dated verified source and the update lag is recorded. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Separate Accuracy, Timeliness and Other Checks” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 9 OF 12
9. Present Exceptions With Reproducible Evidence
Why this move matters
For each material failure, include rule ID, affected count, redacted example, location, observed value and expected condition.
Did You Know? Evidence lets owners reproduce the issue safely.
Define the data, decision and rule authority
For each material failure, include rule ID, affected count, redacted example, location, observed value and expected condition. For The report shows a masked record key and the precise failed date-order rule., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. Do not expose personal or confidential data in examples.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. Do not expose personal or confidential data in examples. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: For each material failure, include rule ID, affected count, redacted example, location, observed value and expected condition.
- Boundary: Do not expose personal or confidential data in examples.
- Application: The report shows a masked record key and the precise failed date-order rule. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Present Exceptions With Reproducible Evidence” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 10 OF 12
10. Prioritise by User Impact and Risk
Why this move matters
Explain how failures affect the intended decision, distinguish blocking from warning conditions and document accepted exceptions.
Did You Know? Priority connects quality to purpose.
Define the data, decision and rule authority
Explain how failures affect the intended decision, distinguish blocking from warning conditions and document accepted exceptions. For Missing programme codes block capacity totals; a display-only capitalisation issue is lower priority., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. Severity is context-dependent and should not be inflated for attention.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. Severity is context-dependent and should not be inflated for attention. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Explain how failures affect the intended decision, distinguish blocking from warning conditions and document accepted exceptions.
- Boundary: Severity is context-dependent and should not be inflated for attention.
- Application: Missing programme codes block capacity totals; a display-only capitalisation issue is lower priority. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Prioritise by User Impact and Risk” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 11 OF 12
11. Assign Remediation, Ownership and Revalidation
Why this move matters
Name the source-level correction route, accountable owner, due date, verification evidence and rule to rerun.
Did You Know? Remediation closes a traceable loop.
Define the data, decision and rule authority
Name the source-level correction route, accountable owner, due date, verification evidence and rule to rerun. For The registrar corrects reference mappings, then the analyst reruns RULE-ENR-04 on a new snapshot., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. Do not repair a report copy while leaving the source defect untouched.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. Do not repair a report copy while leaving the source defect untouched. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: Name the source-level correction route, accountable owner, due date, verification evidence and rule to rerun.
- Boundary: Do not repair a report copy while leaving the source defect untouched.
- Application: The registrar corrects reference mappings, then the analyst reruns RULE-ENR-04 on a new snapshot. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Assign Remediation, Ownership and Revalidation” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
CHAPTER 12 OF 12
12. Conclude Fitness for Use With Dated Limits
Why this move matters
State which use is supported, which conditions remain, what was not tested and when revalidation is required.
Did You Know? A bounded conclusion is more useful than a green badge.
Define the data, decision and rule authority
State which use is supported, which conditions remain, what was not tested and when revalidation is required. For The export is usable for provisional totals after blocking codes are fixed, but not for individual contact decisions., identify the snapshot, owner, intended use, rules, thresholds and authorised exceptions before calculating anything.
Report results by quality dimension and rule
Show evaluated counts, passes, failures, exclusions and examples for completeness, validity, consistency, uniqueness and other applicable dimensions. No dataset is perfectly fit for all purposes or all time.
Turn exceptions into traceable remediation
Assign an owner, severity rationale, correction route, recheck condition and due date without silently changing source records.
State fitness for use without pretending perfection
Conclude for the named use, date and scope, then preserve evidence and unresolved limits. No dataset is perfectly fit for all purposes or all time. A validation report supports a decision; it does not certify truth everywhere.
Practical reader check
- Evidence: State which use is supported, which conditions remain, what was not tested and when revalidation is required.
- Boundary: No dataset is perfectly fit for all purposes or all time.
- Application: The export is usable for provisional totals after blocking codes are fixed, but not for individual contact decisions. Name the next output and how it will be checked.
Student, parent and career transfer
Practise “Conclude Fitness for Use With Dated Limits” by separating evidence, interpretation, decision and next action. A parent, teacher, supervisor or teammate can ask what supports the sentence and which missing fact could change it. This discipline transfers to school investigations, spreadsheets, database operations, analytics, research, quality assurance, audit preparation, public administration, software delivery and responsible AI data work without guaranteeing grades, approval, conformance, software quality, data quality, safety, employment or future outcomes.
PRACTICE LAB
Build a data validation report decision trail
Student route
- Choose one real example or official document inside this guide’s scope.
- Copy its objective and underline actor, action, context, evidence and intended decision.
- Draw the specific reasoning chain used in this article.
- Mark each step reported, inferred, contested or unknown.
- Rewrite the conclusion so it preserves the narrowest important limitation.
Parent or teacher route
Ask the learner to explain turn validation checks into a transparent data-quality report that tells readers what was tested, which rules failed, what the failures mean and what happens next twice: once to a classmate and once to a method specialist. Praise a precise correction and a well-stated unknown; both show disciplined attention to evidence.
Early-career route
Create a one-page data validation report audit with source link, date checked, scope, method logic, decisive wording, contrary evidence, limit and next action. A colleague should be able to continue without guessing.
Decision rule
If a shorter explanation removes the condition that made the original claim true, it is not clearer yet. Restore the condition.
Continue with eduKate’s guides to reading course and career information and giving useful feedback in group projects.
USEFUL NEXT READING
Connect this narrow owner to its neighbour
Read the data-dictionary guide for a related but different reader job. Return here when the question is specifically how to turn validation checks into a transparent data-quality report that tells readers what was tested, which rules failed, what the failures mean and what happens next. Use each guide for the reader task named in its heading.
For English practice across research, school and career communication, visit the Singapore English Tuition Centre learning site.
FREQUENTLY ASKED QUESTIONS
Questions students and parents often ask
Is a data validation report the same as a data cleaning log?
No. The report communicates assessed quality and decisions; a cleaning log records authorised transformations.
Should every rule have the same threshold?
No. Thresholds should reflect user needs, risk and governing requirements, with reasons recorded before results are interpreted.
Can 100% validity prove accuracy?
No. Values can fit a format and still be wrong in the real world.
How should duplicates be reported?
Define the entity and key, separate confirmed from suspected duplicates, and preserve review evidence.
Should personal records appear in examples?
Use minimised or masked evidence and follow access, privacy and security requirements.
When should the report be rerun?
After material source changes, rule changes, remediation or before a decision whose required freshness exceeds the current assessment.
PRIMARY SOURCES
Read the primary guidance for this data validation report
Facts were checked against current official and primary sources on 9 November 2026. Follow the live source for later corrections, completed updates or companion material.
- UK Government Data Quality Framework
- UK Government Data Quality Framework guidance
- eduKate data dictionary guide
A cheerful final note
Precise English makes turn validation checks into a transparent data-quality report that tells readers what was tested, which rules failed, what the failures mean and what happens next more generous, not less. People can see how their evidence and values entered the work, where disagreement remains and what a responsible next step looks like.