Data basics

Introduction to Data

Maarten Van den Broeck

Senior Content Developer at DataCamp

Data is everywhere

Four avatars of people

Introduction to Data

Data is everywhere

Four avatars of people and threes circles with name, age, hobbies

Introduction to Data

Data is everywhere

Four avatars of people with three bubbles with a tshirt, a coffee cup, and social media icons

Introduction to Data

Data is everywhere

Four avatars of people with three bubbles: a tree, the earth, the moon, and a mini rocket

Introduction to Data

Data is everywhere

Four avatars of people with three bubbles: a tree, the earth, the moon, and a mini rocket

Introduction to Data

Data is everywhere

Four avatars of people with three bubbles: a tree, the earth, the moon, and a mini rocket

Introduction to Data

What is data?

$$

  • Derived from datum: given, fact

Data file illustration

Introduction to Data

What is data?

$$

  • Derived from datum: given, fact
  • Valuable resource in this digital era$^1$

Data file illustration with a fact stamp

1 The Economist, May 6th 2017: The world most valuable resource is no longer oil, but data
Introduction to Data

Data context

$$

  • Who is a great player?
    • Lionel Messi
    • Alexander Ovechkin

$$

Messi_vs_Ovechkin_Goals

Introduction to Data

Data context

$$

  • Who is a great player?
    • Lionel Messi
    • Alexander Ovechkin

$$

Messi_vs_Ovechkin_Goals highlighting messi goals

Introduction to Data

Data context

$$

  • Who is a great player?
    • Lionel Messi
    • Alexander Ovechkin

$$

Messi_vs_Ovechkin_Goals highlighting ovechkin goals

Introduction to Data

Data context

$$

Information that provides meaning to data

  • When the data was collected
  • Where the data was collected
  • ...

These characteristics of the data are called the metadata

$$

Messi_vs_Ovechkin_Goals

Introduction to Data

Types of data

Unstructured:

  • Football match video
  • Without labels or order

$$

Structured:

  • Table listing goals, times, players
  • Organized and easier to analyze

Unstructured or structured data

Quantitative or qualitative data

Introduction to Data

Structured data title

  • Common in spreadsheets
  • Easy to filter and analyze

Examples:

  • Sales records
  • Employee attendance
  • Weather data

$$

$$

Sales records  

ID Product Sales
1 T-shirt 15
2 Jeans 2
3 Shoes 3
4 Jacket 1
5 Hat 5
Introduction to Data

Unstructured

  • Harder to analyze
  • Needs processing

Examples:

  • Videos
  • Interviews
  • Pictures

$$

Video icon

Introduction to Data

Quantitative

  • Also called numerical data
  • Ideal for calculations and visualizations

Examples:

  • Points scored
  • Height
  • Temperature

Qualitative

  • Also called categorical data
  • Useful for spotting patterns

$$

Examples:

  • Favorite sports
  • Customer feedback
Introduction to Data

Let's recap

$$

  • Structured: organized and easy to analyze

  • Unstructured: complex but insightful

  • Quantitative: numerical and ideal for calculations

  • Qualitative: describes categories and reveals trends

Unstructured or structured data

Quantitative or qualitative data

Introduction to Data

Let's practice!

Introduction to Data

Preparing Video For Download...