---
title: "OLAP and its operations"
subject: "Data Mining"
chapter: 2
key: "semester_7/data_mining:olap-operations"
source: https://www.bctengineer.com/q/semester_7/data_mining/olap-operations
site: BCT Engineering
---

# OLAP and its operations

Data Mining · Chapter 2: Data Pre-processing

- Asked in: 2065 Baisakh; year not given
- Video: [OLAP operations with real life example | Data Warehouse](https://www.youtube.com/watch?v=BLqE2EKiAy4) — 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/olap-operations
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-2

## Question

What is Online Analytical Processing (OLAP) in data mining? List and explain the operations associated with OLAP with suitable example.

## Short answer

OLAP enables interactive multidimensional analysis for decision support. Operations: roll-up (city→country), drill-down (quarter→month), slice (time=Q1), dice (location=Kathmandu/Pokhara and time=Q1/Q2), pivot (swap rows/columns), plus drill-across and drill-through.

## Answer

**Online Analytical Processing (OLAP)** is a technology that lets users interactively analyse multidimensional data (data cubes) from different viewpoints. It is built on the data warehouse and supports fast, complex queries such as aggregation, comparison and trend analysis for decision making. Servers are of types ROLAP, MOLAP and HOLAP.

#### OLAP operations
```text
        Roll-up (up the hierarchy)
   city -> country        ^
        |                 |
   Drill-down       Slice / Dice / Pivot
```
Consider a sales cube with dimensions *time* (quarter), *location* (city) and *item* (type).

1. **Roll-up (drill-up)**: aggregates data by climbing a concept hierarchy or by removing a dimension. Example: city → country, so sales of Kathmandu and Pokhara become sales of Nepal.
2. **Drill-down (roll-down)**: the reverse; goes from summary to more detail, by stepping down a hierarchy or adding a dimension. Example: quarter → month.
3. **Slice**: selects one value on one dimension, giving a sub-cube of one lower dimension. Example: time = "Q1" gives a 2-D location-by-item table.
4. **Dice**: selects values on two or more dimensions, giving a smaller sub-cube. Example: (location = Kathmandu or Pokhara) and (time = Q1 or Q2) and (item = mobile or laptop).
5. **Pivot (rotate)**: rotates the axes of the view to show the data from a different perspective. Example: swap rows (item) and columns (location).
6. **Other**: drill-across (query over several fact tables) and drill-through (go to the back-end detail records).

## Check yourself

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

1. OLAP lets users:
   A. Interactively analyse multidimensional data from different viewpoints
   B. Process short transactions
   C. Store backups
   D. Clean data only
   Answer: A. It supports aggregation and trend analysis for decisions. (Key point: OLAP definition)

2. Which is drill-down?
   A. Quarter to month
   B. City to country
   C. Choose time = Q1
   D. Rotate axes
   Answer: A. It goes from summary to detail. (Key point: Drill-down)

3. Dice selects:
   A. One value on one dimension
   B. Values on two or more dimensions giving a smaller sub-cube
   C. Nothing
   D. Rotates
   Answer: B. Slice picks one dimension. (Key point: Dice)

## Related in Data Mining

- [OLAP vs OLTP; data cube, operations](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aolap-oltp-data-cube-fact-dimension) — Data Mining, chapter 2
- [OLAP operations and star schema in DMQL](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aolap-operations-star-dmql) — Data Mining, chapter 2
- [OLAP vs OLTP; OLAP operations, fact, dimension](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aolap-oltp-operations-fact-dimension) — Data Mining, chapter 2
- [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

## Related in other subjects

- [Data structure and basic operations](https://www.bctengineer.com/question.md?key=semester_4%2Fdata_structure_and_algorithm%3Adata-structure-basic-operations) — Data Structure and Algorithm, chapter 1
- [Data structure types and operations](https://www.bctengineer.com/question.md?key=semester_4%2Fdata_structure_and_algorithm%3Adata-structure-types-operations) — Data Structure and Algorithm, chapter 1
- [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