wayground logo

Free Printable Worksheets

Font size

S
M
L
XL
Worksheets

Data analytics basics

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

Data analytics is

a)

the art and science of cleaning data.

b)

the process of examining data sets in order to draw

conclusions about the information they contain using specialised software

c)

a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official shared master data assets.

2.

Types of data analysis include

a)

Prescriptive

Diagnostic

Analytic

Descriptive

b)

Descriptive

Prescribed method

Analytic

Diagnostic

c)

Descriptive

Prescriptive

diagnostic

predictive

3.

Artificial intelligence is the best example of which type of data analysis:

(a)  

4.

There are _ steps in the data analysis process.

a)

7

b)

3

c)

5

5.

The 5 Data types analysed in the data analysis process include:

a)

Relational data

Meta data

time-related data

transactional data

hyper-text data

b)

Meta Data

Master Data

Relational data

Time-sensitive data

c)

Relational data

Time-related data

Transactional data

Hyper-text data

Stream data

6.

A data set consists of

a)

entities

b)

raw data

c)

objects

7.

Data found in both relational databases and open databases can be both :

a)

Unstructured and raw

b)

structured and unstructured

c)

meta and raw

8.

The main difference between Management information System (MIS) and Business Intelligence is:

a)

MIS is looking at expenses and revenue reporting of a business while BIS looks at the data to find patterns that could aid the overall operations.

b)

the type of data and how it is handled.

c)

Nothing, they are the same.

9.

Big data is.....

a)

information such as facts and numbers used to analyze something or make decisions.

b)

data or information about data

c)

data that contains greater variety, arriving in increasing volumes and with more velocity.

10.

The Four Vs of big data are:

a)

volume

variety

visual

velocity

b)

Volume

velocity

variety

veracity

c)

There are actually 5 Vs. Volume, variety, veracity and validity.