---
title: "Short note: Noise in data warehouse"
subject: "Data Mining"
chapter: 2
key: "semester_7/data_mining:noise-in-dw-note"
source: https://www.bctengineer.com/q/semester_7/data_mining/noise-in-dw-note
site: BCT Engineering
---

# Short note: Noise in data warehouse

Data Mining · Chapter 2: Data Pre-processing

- Asked in: 2065 Baisakh
- Video: [L30: Techniques to remove Data Noise(Binning, Regression, Clustering) | Data Cleaning Steps | DWDM](https://www.youtube.com/watch?v=EC_IeIBlGto) — Easy Engineering Classes
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_7/data_mining/noise-in-dw-note
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-2

## Question

Write a short note on Noise in Data Warehouse.

## Short answer

Noise in data warehouses is random errors (e.g., age=250) from faulty instruments, human entry, transmission, or inconsistent sources. It causes wrong aggregates and patterns. Handled via binning, regression, clustering, human inspection, and prevention through ETL validation and quality checks.

## Answer

**Noise** in a data warehouse is random error, variance or meaningless/incorrect data in the stored values, for example age = 250, a negative salary, a misspelt city name, or a duplicate record.

**Causes**
- Faulty data collection instruments and sensors.
- Human or data-entry errors.
- Transmission errors and technology limits.
- Inconsistent naming and units across the source systems merged by ETL.

**Effects**: wrong aggregates and reports, wrong patterns, poor decisions, and lower trust in the warehouse.

**Handling noisy data**
- **Binning**: sort values, partition into bins, smooth by bin means, medians or boundaries.
- **Regression**: smooth values using a fitted function.
- **Clustering**: detect and remove outliers that fall outside clusters.
- **Computer and human inspection**: flag suspicious values for manual check.
- Prevention: validation rules at the source and data quality checks in the ETL (cleaning) stage.

Cleaning noise is a main part of the ETL process, done before data are loaded.

## Check yourself

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

1. A cause of noise is:
   A. Faulty instruments, data-entry errors, inconsistent naming and units across sources
   B. Fast networks
   C. Good validation
   D. Small data
   Answer: A. These cause incorrect stored values. (Key point: Causes of noise)

2. Noise leads to:
   A. Wrong aggregates and patterns and poor decisions
   B. Better reports
   C. Faster queries
   D. No effect
   Answer: A. It lowers trust in the warehouse. (Key point: Effects)

3. Noise is best prevented by:
   A. Ignoring it
   B. Validation rules at the source and quality checks in ETL
   C. Deleting the warehouse
   D. Adding duplicates
   Answer: B. Cleaning is a main part of ETL before load. (Key point: Prevention)

## Related in Data Mining

- [Data warehouse, data mart and need](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Awarehouse-datamart-need) — Data Mining, chapter 1
- [Data warehouse architecture and components](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adw-architecture-components) — Data Mining, chapter 1
- [Data warehouse schemas](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adw-schema-types) — Data Mining, chapter 1
- [Data warehouse and its characteristics](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adw-define-characteristics) — Data Mining, chapter 1
- [National data warehouse process architecture](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Anepal-national-data-warehouse) — Data Mining, chapter 1
- [Different data warehouse models](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adw-models) — 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×
- [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
- [Noise, thermal noise, delay distortion](https://www.bctengineer.com/question.md?key=semester_5%2Fdata_communication%3Anoise-types-thermal) — Data Communication, chapter 1
- [Data mining and business knowledge](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Adata-mining-business-knowledge) — Information System, chapter 4