data integrity

USAGE SUMMARY

"data integrity" is correct and usable in written English.
You can use it to refer to the accuracy and consistency of data stored in a database, system, or other digital format. For example, "The company instituted a new set of policies to ensure that data integrity was maintained."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Data integrity and delay management are integrated using the WFO scheduling algorithm.

EURASIP Journal on Wireless Communications and Networking

To Bloomberg officials, any questions about data integrity are infuriating.

The New York Times

The 21st-century networked sovereign, he says, is the guarantor of what he calls "data integrity".

The Guardian

The larger threat is data integrity: whether what looks secure has been changed.

The New Yorker

"It would certainly suggest that there's no real fundamental data integrity problem," he said.

The New York Times - Health

Data integrity and confidentiality.

EURASIP Journal on Wireless Communications and Networking

Figure 13 Data integrity test results.

EURASIP Journal on Advances in Signal Processing

Fig. 1 Steps ensuring data integrity.

EJNMMI Physics

Data integrity is of utmost importance.

Integration, the VLSI Journal

Using checksums and digital signatures, data integrity can be ensured.

EURASIP Journal on Wireless Communications and Networking

Measures to ensure data integrity were preventative, detective and corrective.

The Journal of Headache and Pain

Expert writing Tips

Best practice

In scientific writing, clearly outline the steps taken to ensure "data integrity" throughout the research process, including data collection, storage, and analysis.

Common error

Avoid assuming that data is inherently accurate. Implement thorough validation processes to catch errors early and maintain "data integrity".

Linguistic Context

The phrase "data integrity" functions as a noun phrase, typically serving as the subject or object of a sentence. It refers to the overall accuracy, consistency, and reliability of data. As Ludwig AI highlights, questions about "data integrity" can be infuriating to those responsible for maintaining it.

Expression frequency: Very common

Frequent in

Science

50%

News & Media

30%

Formal & Business

20%

Less common in

Academia

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "data integrity" is a crucial concept referring to the accuracy, consistency, and reliability of data. It's grammatically correct and commonly used in science, news, and business contexts. Ludwig AI confirms its proper usage in written English. To ensure effective communication, focus on implementing robust validation and security measures. When discussing alternatives, consider options like ""data accuracy"" or "information integrity", depending on the specific context.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

information integrity

A broader term that encompasses the accuracy and reliability of information, not just data.

data accuracy

Focuses specifically on the correctness and error-free nature of data.

data soundness

Focuses on the overall reliability and dependability of data.

database integrity

Specifically refers to maintaining the accuracy and consistency of data within a database system.

data validation

Emphasizes the process of ensuring data meets predefined criteria for correctness and completeness.

data reliability

Highlights the trustworthiness and consistency of data over time.

data verification

Stresses the process of confirming the accuracy and validity of data.

data authenticity

Concerns verifying the source and originality of data.

data security

Broadly refers to protecting data from unauthorized access and manipulation.

data protection

Emphasizes safeguarding data against loss, corruption, and misuse.

FAQs

How is "data integrity" ensured?

Data integrity can be ensured through various methods, including data validation, access controls, checksums, and encryption. These measures help prevent unauthorized modification or corruption of data.

Why is "data integrity" important?

Data integrity is crucial because it ensures that data is accurate, consistent, and reliable. This is essential for making informed decisions, maintaining regulatory compliance, and preventing errors or fraud. Maintaining "data accuracy" helps to prevent flawed analyses.

What are common threats to "data integrity"?

Common threats include human error, malware, hardware failures, and unauthorized access. Implementing robust security measures and data validation procedures can help mitigate these risks.

What is the difference between "data integrity" and "data security"?

"Data integrity" focuses on maintaining the accuracy and consistency of data, while "data security" involves protecting data from unauthorized access and breaches. Both are essential for a comprehensive data protection strategy.