---
title: "Main requirements of data mining"
subject: "Data Mining"
chapter: 1
key: "semester_7/data_mining:dm-main-requirements"
source: https://www.bctengineer.com/q/semester_7/data_mining/dm-main-requirements
site: BCT Engineering
---

# Main requirements of data mining

Data Mining · Chapter 1: Introduction

- Asked in: year not given
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_7/data_mining/dm-main-requirements
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-1

## Question

What are the main requirements of data mining?

## Short answer

Main requirements are handling different data types, efficiency and scalability, data quality handling, multiple mining functions, mining at multiple abstraction levels, interactive mining, incorporation of background knowledge, integration with databases, understandable results, a mining query language, and privacy and security.

## Answer

The main requirements (and challenges) a data mining system must meet are:

1. **Handling of different data types**: relational, transactional, text, spatial, multimedia, time-series and web data.
2. **Efficiency and scalability**: algorithms must run in acceptable time on very large data sets, possibly with parallel and distributed processing.
3. **Data quality handling**: noisy, incomplete and inconsistent data must be handled, with outlier detection.
4. **Multiple mining functions**: characterisation, association, classification, clustering, prediction and outlier analysis, usable together.
5. **Mining at multiple levels of abstraction**: drill-down and roll-up on discovered knowledge, using concept hierarchies.
6. **Interactive mining**: the user can refine mining requests and thresholds on the fly.
7. **Incorporation of background (domain) knowledge**.
8. **Integration with databases and warehouses** and with query languages (e.g. DMQL).
9. **Understandable results**: patterns must be interesting, valid and presented clearly through visualisation.
10. **Data mining query language and ad hoc mining.**
11. **Privacy, security and social issues**: protect personal data.

## Check yourself

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

1. Which requirement addresses very large data sets?
   A. Efficiency and scalability, possibly with parallel and distributed processing
   B. Interactive mining
   C. Understandable results
   D. Multiple data types
   Answer: A. Algorithms must run in acceptable time on large data. (Key point: Scalability)

2. What is mining at multiple levels of abstraction?
   A. Drill-down and roll-up on discovered knowledge using concept hierarchies
   B. Mining only raw data
   C. Mining a single table
   D. Ignoring hierarchies
   Answer: A. Users view knowledge at different levels using concept hierarchies. (Key point: Multiple abstraction levels)

3. What does interactive mining allow?
   A. Fixed requests only
   B. Refining mining requests and thresholds on the fly
   C. Running without a user
   D. Deleting the data
   Answer: B. The user can adjust requests and thresholds during mining. (Key point: Interactive mining)

4. Which is a social issue requirement?
   A. Faster hardware
   B. Protecting personal data (privacy and security)
   C. More visualisation
   D. More data types
   Answer: B. Mining systems must protect personal data. (Key point: Privacy)

## Related in Data Mining

- [Data mining and its applications](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adm-banking-biomedical) — Data Mining, chapter 1
- [Data mining vs DW and applications](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adm-vs-dw-applications) — Data Mining, chapter 1
- [CRM; security and privacy of data mining](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Acrm-security-privacy) — Data Mining, chapter 7
- [Where data mining is applicable](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adm-areas-applicable) — Data Mining, chapter 1
- [Descriptive vs predictive data mining](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adm-descriptive-predictive) — Data Mining, chapter 1
- [Architecture of data mining system](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adm-system-architecture) — Data Mining, chapter 1

## Related in other subjects

- [Data warehouse and data mining](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Adata-warehouse-data-mining) — Information System, chapter 4, asked 2×
- [Short note: data mining and warehousing](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Adata-mining-and-warehousing-note) — Information System, chapter 4
- [Data mining and business knowledge](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Adata-mining-business-knowledge) — Information System, chapter 4
- [Design main transmission pipes PQ and QR](https://www.bctengineer.com/question.md?key=semester_5%2Fwater_supply_engineering%3Apd-c70o) — Water Supply Engineering, chapter 7