Understanding Different Types of Data and Sources
When it comes to working with data, it is important to understand the different types of data that are available, as well as the different sources from which these data points can be retrieved. In this article, we will look at different types of data, as well as define different types of data sources, provide examples of each, and discuss how they can be useful for our purposes.
Types of Data
Data can generally be divided into two primary types: qualitative and quantitative. Qualitative data is usually described as non-numeric, or subjective information that is text-based or has elements of interpretation and opinion. Examples of qualitative data include individual interviews, surveys, and focus groups. On the other hand, quantitative data is normally described as numeric, or objective information that has elements of measurement and statistic. Examples of quantitative data include temperature readings, population studies, and exit polls.
Qualitative Data
Qualitative data is preferred when the primary goal is to gain an understanding of the motivations behind an observed behavior or a phenomenon. Information that falls within this type of data—like individual interviews, surveys and focus groups—are the most helpful when attempting to gather the “why” or “how” of a situation. This data is usually provided in the form of text or images, can be subjective in nature, and is typically analyzed through coding in order to identify patterns of behavior.
Example 1:
A school is interested in understanding the different reasons why some students are not performing well in their studies. They could use a survey or interview-style questionnaire to ask each student why they believe they are not performing as expected.
Example 2:
A consumer goods company would like to identify what motivates their customers to purchase their product. They could use focus groups to better understand the customer’s mindset towards the product.
Quantitative Data
In contrast, quantitative data is best utilized when the primary goal is to measure, record and analyze trends, metrics or behaviors in a systematic and standardized manner. This type of data captures numerical values or measurements, usually through experiments or observational research. Additionally, quantitative data can be depicted on graphs and visualized in order to identify and analyze patterns.
Example 1:
A research study wants to measure and analyze the changes in temperature over the course of a year. They could do a series of temperature readings throughout the year, then compare and analyze the results to assess trends.
Example 2:
A population study wants to identify the number of people in a certain region. They could do an annual census to measure and analyze the population size.
Types of Data Sources
Data can be retrieved from numerous sources. Generally speaking, data sources can be divided into two main categories: primary and secondary. Primary data sources are collected from original sources and generally contain information that is most up-to-date. Secondary data sources, on the other hand, are derived from existing primary or secondary sources, usually from a third party, and thus may not be as up-to-date as primary sources.
Primary Data Sources
Primary data sources can be further divided into two categories: quantitative and qualitative. As mentioned above, quantitative data is numeric and can be easily measured and recorded. Examples of quantitative primary data sources include experiments, surveys and polls. Qualitative sources, on the other hand, are textual or have elements of interpretation and opinion. Examples of qualitative primary data sources include interviews, focus groups, and reviews.
Example 1:
A company wants to assess customer feedback on a newly launched product. They could do a survey to capture feedback directly from existing customers.
Example 2:
A research study wants to better understand the culture and values of the people in a certain region. They could conduct individual interviews or focus groups with members of the community to gain a deeper understanding of their culture and values.
Secondary Data Sources
Secondary data sources are derived from existing primary or secondary data sources, usually from third-party sources. For example, information compiled from newspapers, journal articles and public records are all considered secondary data sources. Additionally, government information, census data, and industry reports are also considered secondary data sources.
Example 1:
A company wants to gain an understanding of market trends and benchmark itself against their competitors. They could look into industry reports to compare their performance with their competitors.
Example 2:
A research study wants to understand the population size and income levels in a certain region. They could look into census data to identify population size and demographics, as well as income levels.
Conclusion
In summary, understanding the different types of data and sources can be crucial when it comes to gathering and analyzing information. Data can be divided into two main categories: qualitative and quantitative. Primary data sources can be further divided into two categories: quantitative and qualitative. Secondary data sources are derived from existing primary or secondary data sources, usually from third-party sources. This helps us understand which type of data is best suited for our needs, and also assists us in locating sources of data to achieve our goals.