Bucketing: meaning, definitions and examples
๐
bucketing
[ หbสkษชtษชล ]
data organization
Bucketing is a method of data organization in which data points are grouped into distinct categories or 'buckets'. This technique is often used in data analysis to simplify large datasets by segmenting them into manageable parts for better analysis and interpretation.
Synonyms
categorization, grouping, segmentation.
Examples of usage
- The sales team used bucketing to categorize their leads based on potential revenue.
- In the analysis, we applied bucketing to streamline the processing of customer feedback.
- Bucketing customer age groups helped us tailor our marketing strategies effectively.
organizing data
To bucket means to sort or categorize items into specific groups or classifications. This action is commonly used in programming and data management to facilitate more efficient processing of information.
Synonyms
Examples of usage
- We need to bucket the responses for better analysis.
- The software allows users to bucket the data according to different criteria.
- She decided to bucket the tasks based on priority.
Translations
Translations of the word "bucketing" in other languages:
๐ต๐น agrupamento
๐ฎ๐ณ เคฌเคเฅเคเคฟเคเค
๐ฉ๐ช Bucketisierung
๐ฎ๐ฉ pengelompokan
๐บ๐ฆ ะณััะฟัะฒะฐะฝะฝั
๐ต๐ฑ grupowanie
๐ฏ๐ต ใใฑใใใฃใณใฐ
๐ซ๐ท regroupement
๐ช๐ธ agrupamiento
๐น๐ท gruplama
๐ฐ๐ท ๋ฒํทํ
๐ธ๐ฆ ุชุฌู ูุน
๐จ๐ฟ skupovรกnรญ
๐ธ๐ฐ zhromaลพฤovanie
๐จ๐ณ ๅๆกถ
๐ธ๐ฎ grupiranje
๐ฎ๐ธ flokkun
๐ฐ๐ฟ ัะพะฟัะฐััััั
๐ฌ๐ช แฏแแฃแคแแแ
๐ฆ๐ฟ qruplaลdฤฑrma
๐ฒ๐ฝ agrupamiento
Etymology
The term 'bucketing' derives from the word 'bucket', which originally referred to a, typically round container used for carrying liquids or other materials. The term has evolved in various contexts, particularly in computing and data science. In the context of data analysis, 'bucketing' began to be used in the late 20th century as more businesses started to utilize databases and large datasets. The concept of grouping or categorizing data into 'buckets' became a way to enhance data processing, as it allowed analysts to look at data chunks rather than overwhelming full datasets. Over time, this term has solidified its place in jargon related to data organization and analysis, becoming essential in discussions about handling large-scale data and drawing insights from it.