Page 155 - AI Ver 1.0 Class 10
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For example, if you have to buy a laptop, you need to explore your requirements of the configuration that you
want, of the RAM, hard disk, processor, operating system, graphic card, touch screen or not, etc. But from this
unstructured data you have to choose the one that suits the best to your needs. Similarly, after the data is acquired,
it needs to be explored to suit the needs of the AI Project.
Visualisation of the data plays a very important role in data analysis. This visualisation process has to be carried in
some user-friendly format so that you can:
• Quickly get a sense of the trends, relationships and patterns contained within the data.
• Define strategy for which model to use at a later stage.
• Communicate the same to others effectively.
Different Ways to Visualise Data
The following are some of the different ways to visualise data:
Data Visualisation Technique 1
Name of the representation Bullet Graphs
It is just like a bar graph with extra visual elements for more explanatory
Description
comparison.
stretch goal
base goal
Business A 50
Business B 20
How to draw?
Business C 55
Business D 110
0 20 40 60 80 100
It is used as data comparison of primary data with respect to other data and
Suitable for which type of data? displays it in the context of qualitative ranges of performance, such as poor,
satisfactory, and good.
Data Visualisation Technique 2
Name of the representation Histogram
It is bar graph-like representation of data where data is on x axis and the number,
Description
count or percentage of occurrences in the data will be on y axis.
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