What is data collection? Plus the top 7 data collection methods

Data collection is a fundamental component of research in any field. It refers to the process of gathering information for analysis on a specific topic in an organized and systematic way.


What is data collection?

Data collection refers to the process of gathering information on a specific topic in an organized and systematic way. Typically this process is initiated to analyze the collected data to answer a question or hypothesis.

Data collection is a fundamental component of research in any field — from business to humanities to cultural analysis to medicine. Different data collection methods may work better in different situations. However, the constant is the need for extensive and accurate data.

Data collection methods and tools can be categorized based on different criteria, such as the source of information, its use, or even whether it requires an internet connection or not. Below, you can find the main distinctions and the most common data collection tools.

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Extracting data from the web for the purpose of further research is legal. You just need to make sure not to violate any regulations connected to copyright or personal data. To learn more about the laws that apply to web scraping, check out our legality article.

Primary vs. secondary data collection

The first distinction among types of data collection is between primary and secondary. Primary data collection refers to data extraction directly from the source. Whether it requires interviews, observation, or internet research, primary data collection gets primary data first-hand, straight from the origin.

In secondary data collection, the user collects the data from a third party who has previously extracted it. In this case, it is crucial that this third party is a trusted source and that the collected data is therefore accurate.

This is not the only way to classify data collection methods. Let’s look at a few more.

Qualitative vs. quantitative data

Another useful distinction is the one between qualitative and quantitative data. Qualitative data is generally non-numerical, making it harder to sort out and structure. It usually answers questions such as “why” or “how.”

Quantitative data, as the name suggests, is numerical and can be easily computed. For example, it may consist of yes/no answers, rating scales, or even multiple-choice answers. It typically answers the question “how much.”

While the definition is intuitive, defining one method as strictly qualitative versus quantitative is not always that obvious. Some methods are a crossover of the two types, and sometimes qualitative data can be “coded” numerically to measure answers.

Qualitative vs. quantitative data, illustrated by Julia Körtge © Apify.
Qualitative vs. quantitative data, illustrated by Julia Körtge © Apify.

Online vs. traditional data collection methods

Once upon a time, there was no World Wide Web. Some of us can still recall and marvel at the days spent gathering information from encyclopedias and seeking out informants and interviewees.

Even though the internet arrived and saved us a lot of labor, some data collection methods still require offline work. Interviews, focus groups, and observations, to name a few, are still a good source of information for many kinds of research. Other times, real-life interaction is not needed, and online research is enough. Often, the online and offline intersect. For example, questionnaires may be sent by email and filled in offline.

But the most efficient online data collection method is probably web scraping. Whether you choose primary or secondary data collection, web scraping allows you to collect a more significant amount of data in a shorter amount of time. If you’ve never heard of web scraping, you should check out our Web Scraping: The Beginner's Guide.

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Top 7 data collection methods

Data collection methods are countless, and you can get really creative when catering to a particular project’s needs. It is possible, however, to identify the most common ones. Here are the top 7 data collection tools:

  1. Questionnaires/surveys: open questions or yes-or-no questions in written or typed form. Easier to compute in the latter case, they can take place online or in person.
  2. Interviews: qualitative data collection method in oral form. They provide qualitative data typically helpful for contextualization purposes.
  3. Focus Groups: a group of people carrying out a specific goal-oriented conversation. They usually take place in person and provide valuable data for market research.
  4. Observation: description of product or situation, online or on the field. This method can follow a more or less structured layout, making it easier to compute.
  5. Diaries: account of a topic specified by the researcher written throughout a period of time. It provides qualitative data.
  6. Case studies: description of an object or process in narrative form. Similar to the diary method, it provides detailed qualitative data.
  7. Web scraping: automated data extraction. It provides structured data, already neatly organized.
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These are the most commonly used data collection tools, but combinations of these exist, as well as many other methods created ad hoc for projects of different kinds.

Why collect data?

There are many reasons why data collection deserves attention. For starters, what would you even analyze without data? Research in every field is based on data gathered to be later analyzed. The results serve to understand a context, prevent unfavorable outcomes, and find solutions to problems.

Here are the three main advantages of choosing the suitable data collection method for the project:

Accuracy: you will have to ensure you have enough relevant data to support your claim. If the data is insufficient, the thesis might not be credible.

Decision-making: collecting the correct data helps you assess the situation better and make an informed decision for yourself or your company.

Saving time and cost: when you are not adequately informed, you might make the wrong decisions. Making bad decisions can cost you time and money while fixing your mistakes. Gathering the correct data beforehand can save you precious time and money.

Find out about the many ways that automated data collection can help in research and education.

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How Apify can help you collect data

As this article shows, data collection is an essential part of any research project: medical, marketing, and academic.

So how can you get all that data? Luckily, Apify Store has an extensive range of free tools that you can use to improve your data collection. Just search for the website you need to gather data from or use our universal Web Scraper to do the job.

Familiar with data collection methods but can’t find the perfect fit for your project? Contact Apify to help you solve your exact use case!

Mariachiara Faraon
Mariachiara Faraon
Writer, cultural analyst, gatherer & teller of stories. Passionate about human rights and equality, and curious about how communication and AI can affect them.

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