data verification

USAGE SUMMARY

"data verification" is correct and usable in written English.
You can use it when you want to refer to the process of examining data to ensure accuracy and completeness. For example, "The company conducted data verification to make sure all the entries in the database were valid."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

We have made similar changes to the data verification APIs.

Stanford University

But as computers became more powerful and software more sophisticated — juggling multiple tasks and responding to changing data — verification grew harder.

The New York Times

The DEDMS contains data access, data verification, data statistics, index calculation, and index expression components.

Computers and Electronics in Agriculture

Patient-reported data would be confirmed with medical professionals, providing an intermediate level of data verification.

Neuromuscular Disorders

Following a data verification period, ISS released on November 21, 2016, the new QualityScore ratings for companies.

Columbia University

Our questioners seem to believe that good internal control is predicated on the controls themselves the cross-checking, the reconciliations, the data verification.

Harvard Business Review

Data verification mechanisms can solve this problem.

Journal of the Brazilian Computer Society

I learnt various key terms such as GCP (good clinical practice) and SDV (source data verification).

Science Magazine

Once data verification is completed, Nigeria is set to be dropped from the list of polio-endemic countries, leaving only Afghanistan and Pakistan.

BBC

Google hasn't said how it will handle data verification, only that those who submit false or misleading information could be banned from the program.

TechCrunch

As other states follow Texas and Californiaa's lead, they should publish the data in ways that allow for public engagement, greater transparency and data verification.

Huffington Post

Expert writing Tips

Best practice

When describing a process, specify the methods used for "data verification" (e.g., double entry, cross-referencing, statistical analysis) to enhance clarity.

Common error

Avoid using "data verification" as a catch-all term. Be specific about what aspects of the data are being verified (e.g., completeness, accuracy, consistency).

Linguistic Context

The phrase "data verification" functions primarily as a noun phrase, often acting as the object of a verb or following a preposition. It refers to the process of confirming the accuracy and reliability of data. Ludwig AI confirms this phrase is correct and usable in written English.

Expression frequency: Very common

Frequent in

Science

68%

News & Media

16%

Formal & Business

6%

Less common in

Academia

5%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "data verification" is a grammatically correct and widely used noun phrase that refers to the process of ensuring the accuracy and reliability of data. Ludwig AI confirms this. It's frequently used in scientific, news, and business contexts, with a formal to neutral register. The phrase is best used with specific descriptions of the verification methods and should not be overgeneralized. Alternatives include "data validation" and "accuracy confirmation". This comprehensive analysis highlights the importance of precise and trustworthy data across various domains.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

data validation

Focuses more on the process of ensuring data conforms to predefined rules and formats.

data integrity check

Highlights the process of confirming that the data remains complete and unaltered.

accuracy confirmation

Emphasizes the aspect of confirming the correctness of the data.

information validation

Broader term, applicable when "data" is understood as "information".

authenticity verification

Focuses on confirming the data is genuine and from a trusted source.

source data review

Emphasizes reviewing the original data source to confirm accuracy.

quality assurance of data

Highlights ensuring the data meets certain quality standards.

data authentication

Focuses on confirming the data is authentic and has not been tampered with.

error checking

More general term for detecting and correcting errors in data.

data scrutiny

Suggests a more detailed and critical examination of the data.

FAQs

How is "data verification" typically used in research?

"Data verification" is commonly used in research to ensure the accuracy and reliability of collected data before analysis. It often involves comparing data from different sources or repeating measurements to confirm consistency.

What's the difference between "data verification" and "data validation"?

"Data verification" ensures that data matches the original source and is accurate, while "data validation" checks if data conforms to a predefined format or set of rules. Validation focuses on format and structure, while verification focuses on accuracy.

What are some methods used for "data verification"?

Common methods for "data verification" include double data entry, source data verification (SDV), cross-referencing with other data sets, and statistical checks for outliers or inconsistencies.

Why is "data verification" important?

"Data verification" is crucial for ensuring data quality, which is essential for making informed decisions, conducting reliable research, and maintaining the integrity of databases and systems.