---
title: "Attributes of Big Data"
subject: "Big Data Technologies"
chapter: 1
key: "semester_8/big_data_technologies:big-data-attributes"
source: https://www.bctengineer.com/q/semester_8/big_data_technologies/big-data-attributes
site: BCT Engineering
---

# Attributes of Big Data

Big Data Technologies · Chapter 1: Introduction to Big Data

- Asked in: year not given
- Video: [Characteristics Of Big Data || Easiest explanation](https://www.youtube.com/watch?v=Uk_iw1leY2s) — Adda For IT
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_8/big_data_technologies/big-data-attributes
- Whole chapter: https://www.bctengineer.com/md/semester_8/big_data_technologies/chapter-1

## Question

What are the attributes of Big Data?

## Short answer

Big data is characterised by the Vs: Volume (massive data size), Velocity (high speed of generation and processing), Variety (structured, semi-structured, unstructured types), Veracity (data quality and trustworthiness), and Value (business insights derived). Distributed technologies are needed to handle them.

## Answer

**Big data** is data that is so large, fast and varied that normal tools cannot handle it. Its attributes are usually described by the "V"s.

#### Main attributes (3 Vs, extended to 5 or more)
1. **Volume:** the amount of data is huge, from terabytes to petabytes and zettabytes. Sources are social media, sensors, transactions and logs. Example: Facebook stores petabytes of photos.
2. **Velocity:** the speed at which data is generated, collected and must be processed, often in real time. Example: stock market ticks, clickstreams, sensor streams.
3. **Variety:** many types and formats: structured (tables), semi-structured (JSON, XML, logs) and unstructured (text, images, audio, video).
4. **Veracity:** the quality, accuracy and trustworthiness of data. Big data often has noise, bias and missing values.
5. **Value:** the useful insight and business benefit that can be obtained. Data without value is only cost.
6. **Variability:** the meaning and flow of data change over time, e.g. the same word having different sentiment in different contexts, or seasonal peaks.

#### Summary table
| V | Question it answers |
|---|---|
| Volume | How much data? |
| Velocity | How fast? |
| Variety | What kinds? |
| Veracity | How reliable? |
| Value | How useful? |

#### Other attributes
- Needs distributed storage and processing (cannot fit one machine)
- Mostly generated by machines and users continuously
- Needs new technologies such as Hadoop, Spark and NoSQL

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. Which attribute describes how fast data is generated and must be processed?
   A. Volume
   B. Veracity
   C. Variety
   D. Velocity
   Answer: D. Velocity is the speed of data generation and processing, e.g. stock ticks and clickstreams. (Key point: Velocity)

2. JSON, XML and logs belong to which kind of data under Variety?
   A. Semi-structured
   B. Structured
   C. Unstructured
   D. Value
   Answer: A. Variety includes structured tables, semi-structured JSON/XML/logs and unstructured text, images, audio and video. (Key point: Variety)

3. The same word having different sentiment in different contexts illustrates which V?
   A. Veracity
   B. Variability
   C. Volume
   D. Value
   Answer: B. Variability means data meaning and flow change over time or context; veracity is about trustworthiness. (Key point: Variability vs veracity)

## Related in Big Data Technologies

- [Role of data scientist in big data](https://www.bctengineer.com/question.md?key=semester_8%2Fbig_data_technologies%3Arole-of-data-scientist) — Big Data Technologies, chapter 1, asked 2×
- [Why distributed computing for big data](https://www.bctengineer.com/question.md?key=semester_8%2Fbig_data_technologies%3Adistributed-computing-necessary) — Big Data Technologies, chapter 1
- [Distributed system in big data example](https://www.bctengineer.com/question.md?key=semester_8%2Fbig_data_technologies%3Adistributed-system-example) — Big Data Technologies, chapter 1
- [Big data trends, challenges, characteristics](https://www.bctengineer.com/question.md?key=semester_8%2Fbig_data_technologies%3Abig-data-trends-challenges) — Big Data Technologies, chapter 1
- [Hybrid data in big data warehouse](https://www.bctengineer.com/question.md?key=semester_8%2Fbig_data_technologies%3Ahybrid-data-warehouse) — Big Data Technologies, chapter 1
- [Data analytics process and distributed computing](https://www.bctengineer.com/question.md?key=semester_8%2Fbig_data_technologies%3Adata-analytics-distributed-role) — Big Data Technologies, chapter 1

## Related in other subjects

- [Big data and its processing](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Abig-data-processing) — Information System, chapter 8
- [Discrete vs continuous attributes](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adiscrete-vs-continuous) — Data Mining, chapter 2
- [Define Big O, Omega and Theta](https://www.bctengineer.com/question.md?key=semester_4%2Fdata_structure_and_algorithm%3Abig-o-omega-theta-define) — Data Structure and Algorithm, chapter 9, asked 4×
- [Big-O and Big-Omega with curves](https://www.bctengineer.com/question.md?key=semester_4%2Fdata_structure_and_algorithm%3Abig-o-big-omega-curves) — Data Structure and Algorithm, chapter 9, asked 4×