Module 4:

Data Collection

What is data collection?

How do you collect data from numerous sources?

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Let's move into some practical areas of Big Data.

How would you collect data if you were to do data analysis?

Introduction

If you were to do a data analysis yourself, how would you proceed?
The first thing you should do is collect the data because, basically, you are performing an analysis on a dataset.
In this module, you will learn about the first phase of analysis: the data collection step.

Objectives

1. Know how to find appropriate data for different types of projects.
2. Distinguish different data types.
3. Evaluate and evaluate different data sets to know the quality of the data sets.

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What is data collection?

Definition of Data Collection

The procedure of collecting, measuring, and analyzing precise insights for research using standard and validated techniques or tools.

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Let's dive deeper.

Definitions of Primary and Secondary Data, Benefit and Limitation of Secondary Data, Classification of Secondary Data, Different Sources of Secondary Data, and How to Use Secondary Data (25:22)

If you are a reader...

Explore about the concepts of data collection by reading the articles below.

The Difference Between Primary and Secondary
Datasets, Advantages and Disadvantages of
Different Data Types, How to Collect Data (16:45)

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Additionally, learn with infographics.

Infographic On
Data Collection Techniques

Infographic On How To Collect And Process Data Under GDPR

Databases that can start you off

Here are some links to famous databases that are good for beginners.

Assignment

Let's write an article about data collection!

Examine why data collection is so important for big data projects.
Discuss situations where you would use secondary data and under what situation would you use primary data.
Discuss how you would assess data quality or the reliability of data?

Rubric: https://tinyurl.com/cebuv9j4

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