---
title: "Data warehouse and its characteristics"
subject: "Data Mining"
chapter: 1
key: "semester_7/data_mining:dw-define-characteristics"
source: https://www.bctengineer.com/q/semester_7/data_mining/dw-define-characteristics
site: BCT Engineering
---

# Data warehouse and its characteristics

Data Mining · Chapter 1: Introduction

- Asked in: year not given
- Video: [Lec - 2: Introduction to Data Warehouse🏺 with Examples](https://www.youtube.com/watch?v=NphMcnU8ymU) — Gate Smashers
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_7/data_mining/dw-define-characteristics
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-1

## Question

Describe Data Warehouse and explain its characteristics.

## Answer

A **data warehouse** is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision-making process (W. H. Inmon). It is a central repository of historical data collected from several operational sources and organised for analysis and reporting.

#### Characteristics
- **Subject-oriented**: organised around major subjects such as customer, product, sales, not around day-to-day operations.
- **Integrated**: data from many sources is made consistent in naming, units, formats and encoding.
- **Time-variant**: data is kept as historical snapshots (5-10 years); every record has a time element.
- **Non-volatile**: data is loaded and read, but not updated or deleted in place; only refreshed periodically.

Other features:
- **Large and historical**: stores years of detailed and summarised data.
- **Read-optimised**: designed for complex queries, not for transactions.
- **Multidimensional**: data is modelled as facts and dimensions (star/snowflake) so it can be sliced and diced.
- **Metadata driven**: a metadata repository describes content and lineage.

**Example**: a bank warehouse integrates data from savings, loan and card systems, organised by customer, with 10 years of history, which is never updated after loading.

## Check yourself

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

1. Which is Inmon's definition?
   A. Subject-oriented, integrated, time-variant, non-volatile collection supporting management decisions
   B. A backup of operational DBs
   C. A collection of spreadsheets
   D. A normalised transaction store
   Answer: A. These four properties define a data warehouse. (Key point: Inmon definition)

2. In the bank example, why is data never updated after loading?
   A. Because it is small
   B. It is time-invariant
   C. Warehouse data is non-volatile
   D. Banks forbid computers
   Answer: C. Non-volatility means loaded data is not updated or deleted in place. (Key point: Non-volatile)

3. What does 'metadata driven' mean?
   A. Only users create metadata
   B. A metadata repository describes content and lineage
   C. Metadata replaces data
   D. No metadata is kept
   Answer: B. The repository describes content, sources and lineage. (Key point: Metadata driven)

## 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
- [Short note: Noise in data warehouse](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Anoise-in-dw-note) — Data Mining, chapter 2
- [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
- [Characteristics of a data logger](https://www.bctengineer.com/question.md?key=semester_5%2Finstrumentation_ii%3Adl-characteristics) — Instrumentation II, chapter 5, asked 6×
- [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