massive data

USAGE SUMMARY

"massive data" is correct and usable in written English.
You can use it when referring to very large amounts of data, such as a large database or body of information. For example, "This study relied on a massive data set of over 10,000 records."

✓ Grammatically correct

Academia

News & Media

Science

Human-verified examples from authoritative sources

Exact Expressions

58 human-written examples

Massive data.

The Guardian - Tech

Massive data breach at @Marriott.

The Washington Post

Algorithmic Techniques for Massive Data, COMS 6998-9 (Fall'15).

Massachusetts Institute of Technology

Algorithms for Massive Data, COMS 6998-9 (Spring'19).

Massachusetts Institute of Technology

"Sensors, networks, and massive data" (at Kavli FoS, November 2012).

Stanford University

This massive data file is called a raw point cloud.

Stanford University

But that's going to require some massive data crunching.

MIT Technology Review

It turns out that Google, with its collection of massive data centers, has just that.

The New York Times

Acxiom, a massive data broker based in Little Rock, Arkansas, helps campaigns upload the voter info.

The Guardian

Human-verified similar examples from authoritative sources

Similar Expressions

2 human-written examples

Google's ad-fueled business model absolutely requires massive data-mining of users.

TechCrunch

Spring 15 Spring 14. CS341, Project in Mining Massive Data Sets.

Stanford University

Expert writing Tips

Best practice

When discussing research or analysis involving significant datasets, use "massive data" to convey the scale and complexity of the data being handled.

Common error

Avoid using "massive data" when the dataset is only moderately sized. Ensure the scale genuinely warrants the term to maintain credibility.

Linguistic Context

The phrase "massive data" functions as a noun phrase, typically used as a subject or object in a sentence. It describes a large quantity of data, requiring specialized processing and analysis. Ludwig confirms its correct usage in English.

Expression frequency: Very common

Frequent in

Academia

32%

News & Media

42%

Science

15%

Less common in

Formal & Business

7%

Encyclopedias

2%

Wiki

2%

Ludwig's WRAP-UP

The phrase "massive data" is a grammatically correct and commonly used noun phrase to describe extremely large datasets. According to Ludwig, its usage is appropriate across diverse contexts, particularly in academia, news, and scientific research. When using this phrase, ensure the data's scale genuinely warrants the term and consider alternatives like "extensive dataset" or "large-scale data" for nuanced communication. Be mindful of ethical considerations and the challenges associated with processing and analyzing such large volumes of data. The frequency of use in different contexts highlights its broad applicability, but careful consideration should be given to the register and audience.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

Extensive dataset

Focuses on the completeness and comprehensiveness of the data.

Vast amount of information

Emphasizes the sheer quantity of information.

Large-scale data

Highlights the magnitude and scope of the data.

Big data analytics

Concentrates on the analysis and processing aspect of large data volumes.

Voluminous information

Underlines the abundant and plentiful nature of the data.

Substantial data resources

Focuses on data considered to be a valuable asset or resource.

Comprehensive data

Emphasizes the all-inclusive nature of the information.

Tremendous data collection

Highlights the immensity of the assembled data.

Immense data repository

Refers to the storage and archiving aspect of large data.

Bulk data

Indicates data that is undifferentiated and treated as a single unit.

FAQs

How is "massive data" used in technical contexts?

In technical fields, "massive data" refers to extremely large datasets that require specialized tools and techniques for processing and analysis, often involving machine learning and high-performance computing.

What are the ethical considerations when handling "massive data"?

Ethical considerations include ensuring data privacy, preventing bias in algorithms, and maintaining transparency about how the data is collected, stored, and used. Using "responsible data handling" practices is crucial.

What can I say instead of "massive data"?

You can use alternatives like "extensive dataset", "large-scale data", or "vast amount of information" depending on the specific nuance you want to convey.

What are some challenges associated with "massive data"?

Challenges include the computational resources required for processing, the complexity of data management, and the need for advanced analytical techniques to extract meaningful insights.