data granularity

USAGE SUMMARY

The phrase "data granularity" is correct and usable in written English.
It is typically used in contexts related to data analysis, databases, or information systems to describe the level of detail or precision of the data being analyzed or stored. Example: "The data granularity in this report allows us to identify trends at a very detailed level, which is crucial for our analysis."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

11 human-written examples

However, even with this level of data granularity, Airdna said it couldn't tell which units were taken out of the market or not.

TechCrunch

The evaluated load profiles cover a time span of about 1 year with 96 measurements per day, i.e., 15-min data granularity.

EURASIP Journal on Information Security

To provide the maximal efficient informational stream between the producer and consumer, we have to consider data granularity and timing of transmitting values [23].

EURASIP Journal on Wireless Communications and Networking

They are usually structured according to the multidimensional structure (also called a cube), which facilitates a rapid navigation within different levels of data granularity (from coarser to finer level and vice versa).

Human-centric Computing and Information Sciences

In this case study, the automation of data processing and geoprocessing of projects data was complicated by a myriad of data quality issues; including missing data, inaccurate data, asymmetric data granularity, and semantic interoperability issues.

Visualization in Engineering

Given the diversity of biobanking practices and workforce roles, efforts have been made consistently to maintain robust data granularity while aiding user accessibility, data discoverability, and security within and across applications by providing a lower learning curve in using OpenSpecimen.

Journal of Biomedical Informatics

Human-verified similar examples from authoritative sources

Similar Expressions

49 human-written examples

Currently available anonymization methods, however, are not capable of accommodating the big data scalability, granularity, and performance in efficient manners.

Journal of Big Data

Note that not every paper was forthcoming with a standard error in the Curie temperature measurements since they are typically compiled along with other material data with granularity being sacrificed in the name of a broader view of material properties.

EPJ Techniques and Instrumentation

The retrospective nature of the data, and granularity of the information were not sufficient to discriminate these types of factors.

BMJ Open

No such information or further granularity of data is available for the subgroup with physical complaints.

BMC Public Health

"There really is no-one else trying to gather data in the granularity we are.

TechCrunch

Expert writing Tips

Best practice

When discussing "data granularity", clearly define the specific level of detail to ensure effective communication and avoid ambiguity.

Common error

Avoid mixing different levels of "data granularity" within the same analysis or report without proper justification and clear indication of the changes.

Linguistic Context

The phrase "data granularity" functions as a noun phrase, typically used as a subject or object in sentences related to data management, analysis, and quality. As Ludwig AI confirms, the phrase is grammatically sound. Examples in Ludwig demonstrate its role in describing the level of detail in data.

Expression frequency: Uncommon

Frequent in

Science

75%

News & Media

15%

Formal & Business

10%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

In summary, "data granularity" is a noun phrase denoting the level of detail in data, commonly used in scientific, technical, and analytical contexts. Ludwig AI confirms its grammatical correctness. It appears frequently in scientific publications and news media, emphasizing its relevance in both research and reporting. When using this term, ensure clarity regarding the specific level of detail to avoid ambiguity. Alternatives such as "data resolution" or "level of detail in data" can be used to vary expression while maintaining semantic accuracy. Understanding and appropriately applying "data granularity" enhances precision in data-related discussions and analyses.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

data granularity level

More explicitly mentions the existence of different grades or levels of data.

data resolution

Focuses on the precision with which data can be measured or represented.

level of detail in data

Specifies the extent to which data is broken down into smaller components.

degree of data detail

Highlights the extent or measure of the data's detailed nature.

data specificity

Highlights how precisely the data defines what it represents.

fineness of data

Emphasizes the delicate or precise nature of the data's detail.

data depth

Implies how deeply the data explores a topic or dimension.

data segmentation

Refers to how the data is divided into smaller segments, impacting granularity.

data breakdown

Focuses on how data is broken down into smaller, manageable parts.

data refinement

Suggests the process of making data more precise or detailed.

FAQs

How can I improve the "data granularity" in my reports?

To enhance "data granularity", ensure that you collect data at the most detailed level possible, allowing for aggregation at higher levels if needed. This provides flexibility in analysis and reporting.

What does "data granularity" mean in the context of databases?

In databases, "data granularity" refers to the level of detail at which data is stored. Finer granularity means more detailed data, while coarser granularity implies more aggregated or summarized data.

What are the trade-offs between fine and coarse "data granularity"?

Fine "data granularity" provides more detailed insights but can increase storage requirements and processing time. Coarse "data granularity" reduces these burdens but may sacrifice analytical depth. Choose the level that best suits your specific needs and resources.

How does "data granularity" affect data analysis?

The level of "data granularity" directly impacts the types of analyses you can perform. Finer granularity allows for more detailed and nuanced analysis, while coarser granularity is suitable for high-level overviews and trend identification.