---
title: "Different data warehouse models"
subject: "Data Mining"
chapter: 1
key: "semester_7/data_mining:dw-models"
source: https://www.bctengineer.com/q/semester_7/data_mining/dw-models
site: BCT Engineering
---

# Different data warehouse models

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/dw-models
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-1

## Question

Explain Different Data Warehouse Models.

## Short answer

The three data warehouse models are enterprise warehouse, data mart, and virtual warehouse. Enterprise warehouse covers all subjects and is large and costly; data mart is a smaller subject-specific subset, dependent or independent; virtual warehouse is a set of views over operational databases, cheap but without history.

## Answer

From the architecture point of view, there are three data warehouse models:

#### 1. Enterprise warehouse
Collects information about all subjects across the whole organisation. It integrates data from many operational systems and external sources, holds detailed and summarised data, and needs a lot of time, cost and planning (GB to TB). Built on mainframes or large servers.

#### 2. Data mart
A subset of corporate data for one group of users, such as marketing. Limited to selected subjects. Faster and cheaper to build (weeks).
- **Independent**: loaded directly from operational sources.
- **Dependent**: loaded from an enterprise warehouse.

#### 3. Virtual warehouse
A set of **views** over operational databases. Only some summary views are materialised for efficiency. Easy and cheap to build, but needs extra capacity on the operational servers and gives no historical data.

```text
 Enterprise DW  ->  Data marts (dependent)
 Sources        ->  Data marts (independent)
 Sources        ->  Views (virtual warehouse)
```

A recommended approach is incremental: build independent marts with a common design, then integrate them into an enterprise warehouse (a mix of top-down and bottom-up).

## Check yourself

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

1. What does an enterprise warehouse cover?
   A. One department
   B. All subjects across the whole organisation, integrating many sources
   C. Only views
   D. Only external data
   Answer: B. It needs long time, cost and planning. (Key point: Enterprise warehouse)

2. How does a dependent data mart differ from an independent one?
   A. Dependent loads from an enterprise warehouse; independent loads directly from operational sources
   B. Dependent loads from sources; independent from warehouse
   C. No difference
   D. Dependent has no data
   Answer: A. Source of loading distinguishes them. (Key point: Dependent vs independent mart)

3. What is a virtual warehouse?
   A. A set of views over operational databases
   B. A huge separate storage
   C. A data mart
   D. A backup
   Answer: A. It is cheap to build but burdens operational servers and keeps no history. (Key point: Virtual warehouse)

## 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
- [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

## 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
- [Data-centric consistency models](https://www.bctengineer.com/question.md?key=semester_7%2Fdistributed_system%3Adata-centric-consistency) — Distributed System, chapter 7
- [Data mining and business knowledge](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Adata-mining-business-knowledge) — Information System, chapter 4