useless data

USAGE SUMMARY

The phrase "useless data" is correct and usable in written English.
It can be used to describe information that is not helpful or relevant to a particular context or situation. Example: "After analyzing the results, we found that the survey provided us with a lot of useless data that did not contribute to our research."

✓ Grammatically correct

News & Media

Science

Academia

Human-verified examples from authoritative sources

Exact Expressions

32 human-written examples

But somebody (probably the operations manager's assistant) spent a lot of time compiling that useless data — because it was her job.

The New York Times

A prototype has been developed in order to search for multiple keywords at the same time and collect the required data automatically to eliminate the useless data.

Computers & Electrical Engineering

"Signal-to-noise ratio" is an engineering concept that focuses on the amount of useful information being received compared with false or useless data.

The Washington Post

The trick, of course, is to get rid of the useless data while keeping the useful stuff, something they manage using a machine learning approach.

MIT Technology Review

He said Haldane promised to deliver "hidden market" job leads, but instead provided a mostly useless "data dump" of company information, much of which could have been obtained free on the Internet.

The New York Times

Rather, he uses telephone lines to gain access to large computers linked to the Internet and then programs these computers to send the deluge of useless data, multiplying the congestion and masking the source of the attack.

The New York Times

Human-verified similar examples from authoritative sources

Similar Expressions

28 human-written examples

The expression 'signal-to-noise' is a ratio of useful to useless information in a data exchange, and the work consists of a circular structure that contains four horizontal rows of 128 split-flaps at eye level.

Vice

The simulation results demonstrate that transmission by the FBM is more efficient than that by other mechanisms, such as EDCA (Enhanced Distributed Channel Access), static mapping and adaptive mapping, suggesting that the energy of a device is not wasted in the transmission of useless video data in WLANs.

Journal of Network and Computer Applications

There's one more trend at play putting pressure on retailers to rapidly discard useless consumer data – or never collect it in the first place.

Forbes

"We were broken into and we thought it was useless employment data and we are slowly discovering what it was that they stole," says the former intelligence employee.

TechCrunch

On the other hand, messages transmitted by variable node s n are uniform distributions of the corresponding pilot symbol, which are useless for data symbol detection, thus, we can consider variable node s n as an idle node and disconnect from their neighbors.

EURASIP Journal on Wireless Communications and Networking

Expert writing Tips

Best practice

When dealing with large datasets, prioritize data cleaning to eliminate "useless data" early on. This streamlines analysis and improves efficiency.

Common error

Avoid the common mistake of retaining all collected data without assessment. Retaining "useless data" can obscure relevant insights and inflate storage costs.

Linguistic Context

The phrase "useless data" functions as a noun phrase where the adjective "useless" modifies the noun "data". It describes information that lacks value or relevance. Ludwig AI confirms this usage with examples across various contexts.

Expression frequency: Common

Frequent in

News & Media

36%

Science

32%

Academia

12%

Less common in

Formal & Business

4%

Wiki

4%

Reference

0%

Ludwig's WRAP-UP

The phrase "useless data" is a commonly used and grammatically correct expression referring to data that lacks value or relevance. As Ludwig AI confirms, it appears frequently in news, scientific, and academic contexts. Effective use of this phrase involves understanding the importance of data filtering and avoiding the retention of irrelevant information, which can hinder analysis and inflate costs. Consider related phrases like "irrelevant information" or "worthless information" to diversify your language. By focusing on high-quality, relevant data, you can improve the efficiency and accuracy of your analyses.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

Irrelevant information

Focuses on the lack of relevance to a specific context.

Worthless information

Emphasizes the lack of any value or benefit.

Trivial data

Highlights the insignificance or unimportance of the data.

Insignificant data

Underscores the lack of impact or importance of the data.

Unproductive data

Focuses on the data's failure to yield any useful results.

Unnecessary information

Highlights the data's redundancy or lack of need.

Redundant data

Emphasizes the duplicative nature of the data.

Meaningless data

Focuses on the lack of coherence or interpretability.

Spurious data

Suggests the data is false or misleading.

Inconsequential data

Highlights the lack of significant effect or outcome.

FAQs

How can I identify "useless data" in my research?

Identify "useless data" by assessing its relevance to your research questions, its accuracy, and its potential to contribute to meaningful insights. Data that doesn't meet these criteria can be considered "useless".

What are the consequences of including "useless data" in data analysis?

Including "useless data" can lead to skewed results, wasted resources, increased analysis time, and potentially incorrect conclusions. It's crucial to filter out irrelevant information to maintain the integrity of your analysis.

What's the difference between "useless data" and "irrelevant data"?

"Useless data" generally refers to data that lacks any value or applicability, while "irrelevant data" is data that is not pertinent to the current context or analysis. Both can hinder efficient decision-making and data processing.

What are some strategies for eliminating "useless data" from a dataset?

Strategies include data cleaning, filtering based on predefined criteria, removing duplicate entries, correcting errors, and employing feature selection techniques to focus on the most informative variables. Regular data audits can also help identify and remove "useless data".