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How to understand
your data?
Ahmad Karawash
1
Outline
1-Find the story
in your data
1
2-Search for
patterns or
interesting
insights
2
3-Check data
type
3
4-Check data
relationships
4
1-Find the story in
your data
Information can be visualized in several
ways, each of which can provide a specific
insight. When you start to work with your
data, it’s important to identify and
understand the story you are trying to tell
and the relationship you are looking to
show. Knowing this information will help
you select the proper visualization to best
deliver your message
3
2-Search for patterns or interesting insights
4
3-Check data type
5
Quiz: Matching examples to data types
6
Rainfall in a year
Number of employees in the office
Types of products sold
• CATEGORICAL
1
• QUANTITATIVE
2
• DISCRETE
3
• CONTINUOUS
4
4-Check data relationships
7
4-Check data relationships
8
Quiz: Matching examples to data relationships
9
Number of visitors to various websites.
Salaries according to education level.
Monthly sales.
Historic weather patterns, rank months hot to cold.
Park tickets sold on a rainy day vs. a regular day.
Heights of players on a basketball team.
% of customers purchasing specific products
• TIME-SERIES
1
• NOMINAL COMPARISON
2
• CORRELATION
3
• DISTRIBUTION
4
• RANKING
5
• DEVIATION
6
• PART-TO-WHOLE RELATIONSHIPS
7
Conclusion
Now that you’ve got a handle on the most
common data types and relationships
you’ll most likely have to work with.
10
Questions?
Ahmad.Karawash@gmail.com
11

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How to understand your data

  • 1. How to understand your data? Ahmad Karawash 1
  • 2. Outline 1-Find the story in your data 1 2-Search for patterns or interesting insights 2 3-Check data type 3 4-Check data relationships 4
  • 3. 1-Find the story in your data Information can be visualized in several ways, each of which can provide a specific insight. When you start to work with your data, it’s important to identify and understand the story you are trying to tell and the relationship you are looking to show. Knowing this information will help you select the proper visualization to best deliver your message 3
  • 4. 2-Search for patterns or interesting insights 4
  • 6. Quiz: Matching examples to data types 6 Rainfall in a year Number of employees in the office Types of products sold • CATEGORICAL 1 • QUANTITATIVE 2 • DISCRETE 3 • CONTINUOUS 4
  • 9. Quiz: Matching examples to data relationships 9 Number of visitors to various websites. Salaries according to education level. Monthly sales. Historic weather patterns, rank months hot to cold. Park tickets sold on a rainy day vs. a regular day. Heights of players on a basketball team. % of customers purchasing specific products • TIME-SERIES 1 • NOMINAL COMPARISON 2 • CORRELATION 3 • DISTRIBUTION 4 • RANKING 5 • DEVIATION 6 • PART-TO-WHOLE RELATIONSHIPS 7
  • 10. Conclusion Now that you’ve got a handle on the most common data types and relationships you’ll most likely have to work with. 10