data utility

USAGE SUMMARY

The phrase "data utility" is correct and usable in written English.
It is generally used to refer to a piece of software or a website that assists users in analyzing and manipulating data. For example, "This data utility allows us to visualize complex datasets in a more comprehensive way."

✓ Grammatically correct

Science

Academia

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Practical insights to balance disclosure risk, data utility, and other issues relating to operational feasibility, budget, and timelines.

Cornell University

To enhance data utility, we propose another generic tool called stratified pick-up.

Information Systems

We realized that order-preserving encryption is a tradeoff between data utility and practicability.

Future Generation Computer Systems

To efficiently analyze the data, a new metric for assessment of data utility, the combined classification quality measure, was developed.

Computers in Biology and Medicine

We describe the protocol development and illustrate data utility by comparing results across three trail surface types.

Journal of Outdoor Recreation and Tourism

Thus, improving this aspect will have a high impact on the data utility of anonymized social networks.

Expert Systems with Applications

We conduct extensive experiments to demonstrate the effectiveness of our tools in terms of data utility and efficiency.

Information Systems

Our efforts are focused on translating the theoretical promise of new measures for privacy protection and data utility into practical tools and approaches.

Massachusetts Institute of Technology

Besides, we design the operations on the system server side to exploit the data utility in measurements from large number of sensors.

Computer Networks

This performance improvement is in terms of data utility, for the exact same k-anonymity constraint, but does come at the expense of higher computational sophistication.

Information Sciences

This allows us to mask the original ratings to preserve k-anonymity-like data privacy, and enhance data utility (quantified using prediction accuracy in this paper).

Journal of Parallel and Distributed Computing

Expert writing Tips

Best practice

When discussing privacy, clearly define how improvements to algorithms can simultaneously enhance both privacy and "data utility".

Common error

Avoid assuming that more data automatically leads to greater "data utility". Focus on quality and relevance to ensure that the data serves its intended purpose effectively.

Linguistic Context

The phrase "data utility" primarily functions as a noun phrase. Ludwig indicates that it commonly refers to the usefulness and effectiveness of data for a specific purpose. It is used to describe the quality of data in enabling meaningful analysis and decision-making.

Expression frequency: Very common

Frequent in

Science

67%

Academia

21%

News & Media

6%

Less common in

Formal & Business

3%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "data utility" refers to the degree to which data is useful and effective for its intended purpose. Ludwig's analysis confirms its grammatical correctness and prevalence in academic and scientific domains, where it describes the quality of data enabling meaningful analysis and decision-making. When discussing data management, algorithms, and privacy, focusing on optimizing "data utility" ensures data is not just abundant but valuable.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

data usefulness

Highlights the degree to which data is helpful or valuable.

data effectiveness

Focuses on how effectively the data is used.

information usability

Focuses on how easy and effective it is to use the information derived from the data.

data value

Emphasizes the inherent worth or importance of the data.

data applicability

Considers how suitable the data is for a specific purpose.

data efficiency

Stresses the productivity and minimization of wasted effort in data usage.

data serviceability

Highlights the quality of the data for a specified use.

data exploitability

How easy is to take advantage of data in a given context.

data operability

Consider if data is ready for a given operation.

data leverage

Highlights ability to use the data in a advantageous way.

FAQs

How can I improve "data utility" in my project?

Enhance "data utility" by ensuring data accuracy, relevance, and accessibility. Proper data cleaning, validation, and standardization processes are crucial. Consider using appropriate tools and techniques for data analysis and visualization to extract meaningful insights.

What is the trade-off between privacy and "data utility"?

Balancing privacy and "data utility" often involves techniques like differential privacy and data anonymization. These methods add noise or modify data to protect individual privacy while preserving its overall statistical properties for useful analysis. The key is to minimize information loss while maximizing privacy protection.

What are some metrics for assessing "data utility"?

Metrics for assessing "data utility" include accuracy, completeness, consistency, and relevance. You can also evaluate the impact of data on specific tasks or models, such as prediction accuracy or classification quality. Information loss metrics can help quantify how much utility is retained after privacy-preserving transformations.

How does "data utility" relate to data governance?

Data governance policies should ensure that data is managed in a way that maximizes its "data utility" while adhering to ethical and legal standards. This involves defining roles and responsibilities for data quality, security, and access. Effective data governance helps organizations leverage data assets to achieve their objectives responsibly.