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Data Warehousing

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

__________ refers to the process of collecting, storing, and managing large volumes of data from various sources in a centralized repository.

a)

Data Warehousing

b)

Data Mart

c)

Data Modelling

d)

Attributes

2.

Which of these is not a type of data warehouse?

a)

Single Tier

b)

Desktop Based

c)

Multi Tier

d)

Cloud Based

3.

_______________ is a subset of a data warehouse designed to serve a specific group or department's business intelligence (BI) and reporting needs.

a)

Star Schema

b)

Data Warehouse

c)

Data Mart

d)

Snowflake Schema

4.

Which of the following supports day-to-day transactional operations?

a)

OLTP

b)

OLAP

c)

Both

d)

None

5.

Which of the following supports complex and strategic business analysis?

a)

OLTP

b)

OLAP

c)

Both

d)

None

6.

___________ is the blueprint that defines how your data will be stored, accessed and manipulated to support business intelligence.

a)

Data Warehouse

b)

Data Mart

c)

Data Modelling

d)

Data Lake

7.

______________ define the structure and characteristics of dimension table, providing the necessary details for analysis.

a)

Dimension Table

b)

Fact Table

c)

Attributes

d)

Variables

8.

In a ______________, the central feature is a fact table that is directly connected to multiple dimension tables. When visualized, the schema resembles a star, with the fact table at the center and dimensions radiating outward.

a)

Simple Schema

b)

Star Schema

c)

Complex Schema

d)

Snowflake Schema

9.

A _______________ is an extension of the star schema where dimension table are normalized, meaning they are broken into multiple related tables. This results in a structure that resembles a snowflake when visualized, with additional levels of normalization.

a)

Simple Schema

b)

Star Schema

c)

Complex Schema

d)

Snowflake Schema

10.

_____________ is the process of combining data from multiple sources into a single, unified view.

a)

Data Warehouse

b)

Data Integration

c)

Data Mart

d)

Data Modelling