wayground logo

Free Printable Worksheets

Font size

S
M
L
XL
Worksheets

L3 DT Module 1

Total questions: 16

Worksheet time: 9mins

Name
Class
Date
1.

Which of the options below might we see at the bottom of the DIKW model aka Knowledge Pyramid

a)

Knowledge

b)

Wisdom

c)

Data

d)

Information

2.

What does IoT stand for?

a)

Internet of Things

b)

Interconnection of Things

c)

Interconnected Office Throughput

3.

Which of the below are examples of key data formats we might use?

a)

Spreadsheet / CSV

b)

Binary Files

c)

XML

d)

JSON

e)

Relational Tables

4.

What data format does the image represent?

a)

JSON

b)

XML

c)

Binary file

d)

Plain text

5.

(a)   is data which have been processed in some way to give it meaning.

6.

A spreadsheet would typically hold what type of data?

a)

Structured

b)

Unstructured

7.

JSON is an example of

a)

Structured data

b)

Semi-structured data

c)

Unstructured data

8.

True or false: Quantitative variables will typically contain words.

a)

True

b)

False

9.

Which type of data source described data which is publicly available but has restriction on its use or redistribution?

a)

Open Data

b)

Public Data

c)

Proprietary Data

10.

(a)   data sources are ones which are provided in a machine readable format to the public?

11.

Stock level data for an online shop is an example of

a)

Administrative data

b)

Operational data

12.

Trur or False: Administrative data is often derrived from operational data?

a)

False

b)

True

13.

There are _ stages in the data lifecycle.

(a)  

14.

In relation to working with data, ETL stands for

a)

Extract, transfer, load

b)

Export, transition, live

c)

Export, try, load

d)

Extract, transform, load

15.

In the data analytics lifecycle, which stage is where data is gathered from sources and cleaned?

a)

Business understanding

b)

Data understanding

c)

Data preparation

d)

Validation

16.

Mean, Median and Mode are examples of

a)

Measures of central tendency

b)

Measures of variability or speed

c)

Linear regression

d)

Clustering