---
title: "Short note: Data marts and metadata"
subject: "Data Mining"
chapter: 1
key: "semester_7/data_mining:datamart-metadata-note"
source: https://www.bctengineer.com/q/semester_7/data_mining/datamart-metadata-note
site: BCT Engineering
---

# Short note: Data marts and metadata

Data Mining · Chapter 1: Introduction

- Asked in: 2063, 3 marks
- Video: [Lec-3_Data Mart and Meta Data| Data Mining | Computer Engineering](https://www.youtube.com/watch?v=VQFBmB6fAsI) — Computer_IT_ICT Engineering Department : LJIET
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_7/data_mining/datamart-metadata-note
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-1

## Question

Write a short note on Data Marts and Metadata in DW.

## Short answer

Data marts are subject-specific subsets of a data warehouse, built for one department; they are cheaper and faster. Metadata is data about the data, including technical (source mappings, schema), business (definitions), and operational (load history) descriptions to help users understand and maintain the warehouse.

## Answer

#### Data mart
A **data mart** is a subset of the data warehouse designed for one department or subject (sales, finance, marketing). It holds less data, is cheaper and quicker to build, and gives faster response. Types: **dependent** (fed from the enterprise warehouse), **independent** (fed directly from sources) and **hybrid**. Example: a Marketing mart holding only customer and campaign data.

#### Metadata
**Metadata** is "data about data". It describes the warehouse contents and how they were created. Types:
- **Technical (back-room) metadata**: source-to-target mappings, schema, transformation rules, load schedule, data lineage.
- **Business (front-room) metadata**: business terms, definitions, ownership, report descriptions, so users can understand the data.
- **Operational metadata**: load history, data currency, usage statistics.

It is used by ETL tools, the warehouse and query managers, and end users; without metadata, the warehouse is hard to use or maintain. Example: metadata for column `amt` says: "sales amount in NPR, from POS table BILL.TOTAL, loaded daily at 11 pm".

## Check yourself

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

1. Which are the data mart types?
   A. Star, snowflake, galaxy
   B. Technical, business, operational
   C. Dependent, independent, hybrid
   D. Hot, warm, cold
   Answer: C. Dependent marts feed from the warehouse, independent directly from sources, hybrid mix both. (Key point: Data mart types)

2. Which describes business (front-room) metadata?
   A. Source-to-target mappings
   B. Business terms, definitions and ownership so users understand the data
   C. Load history
   D. Transformation rules
   Answer: B. Business metadata explains terms and ownership for users; technical metadata covers mappings and rules. (Key point: Metadata types)

3. Metadata for column amt says 'sales amount in NPR, from BILL.TOTAL, loaded daily'. What is this?
   A. Data about data
   B. A backup
   C. A fact table
   D. The actual value data
   Answer: A. It describes the data rather than being data values themselves. (Key point: Metadata example)

## Related in Data Mining

- [Metadata and DW architecture](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Ametadata-dw-architecture) — 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
- [Define metadata](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adefine-metadata) — Data Mining, chapter 1
- [RDBMS vs DW database; DW terms](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Ardbms-vs-dw-terms) — Data Mining, chapter 1
- [Short note: DW process architecture](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adw-process-architecture-note) — Data Mining, chapter 1
- [DW characteristics vs operational database](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adw-characteristics-vs-operational) — Data Mining, chapter 1