What Are Common Data Collection Methods? | Coursera

Explore common methods and the importance of data collection. Below, you can also discover how to distinguish between the different types of data and who ultimately performs data collection.
Whether getting feedback on a product or taking guesswork out of the decision-making process, data collection empowers companies with the information they otherwise wouldn’t have access to. The specific method chosen for data collection typically varies depending on factors such as the information you’re trying to obtain and your field of study. You also need to make additional considerations when collecting data to ensure the process is legal, ethical, and accurate.
Prior to beginning the data collection process, you should have four things already established. These include the question you're answering, who you'll collect data from, when you will collect it, and the method you’ll use.
Keep reading to explore the various data collection methods and how to pursue a career in the field.
Data collection describes activities designed to get information from sources for evaluation, answering questions, and identifying trends. Professionals across many industries use data collection to drive decisions, support goals, and propel businesses forward.
Having as much relevant information as possible allows companies to develop informed plans and strategies based on facts rather than making assumptions about what might work or what people could want. With technological advances, we have access to more data than ever, leading to various collection methods. While data collection can include complex approaches such as analyzing big data accessed through data mining, simpler strategies such as surveys still hold significant value.
For companies to succeed, they look for strategies to develop competitive advantages that drive growth. For example, collecting customer data allows businesses to learn more about their consumers and tailor offerings to better meet their needs. In other applications, including social and physical sciences, data collection helps answer questions, validate studies, and properly allocate resources.
Various positions use data collection as part of their job responsibilities. For example, data collection specialists’ primary responsibilities involve collecting and organizing data. Other data collection roles include:
Sata support specialists
Bioinformatics scientists
Data is either qualitative or quantitative. Both types of data are valuable and are accessible through different methods of collection. Qualitative data is data you can’t assign a numerical value; it is information you can express in descriptive terms. For example, if you observe the color of someone's hair, you classify it with qualitative data since you’re describing a characteristic.
Quantitative data is measurable and results in a numerical value. Therefore, quantitative data is universal since it represents an objective fact, whereas qualitative data is more subjective. Each type of data serves a different purpose and delivers different insights. Qualitative data allows you to develop new hypotheses, and quantitative data directly tests a hypothesis.
Data collection methods are either qualitative or quantitative. Quantitative methods include conducting experiments, observing well-defined situations or events, and gathering data from computer systems like customer relationship management (CRM) or management information systems (MIS). Qualitative methods help you understand the driving forces behind the results. Methods include open-ended questions, interactive interviews, and using multiple collection methods.
In either case, each data collection method has its benefits and use cases. When collecting data, you have two potential sources: primary and secondary. Primary data is data you collect directly from its original source, such as an interview or survey you performed. Secondary data is data sourced from research previously completed, such as published papers and journals.
The following explores six data collection methods researchers use today in greater detail.
Forms and surveys allow you to gather information from a specific group of people. This strategy collects qualitative data about people's opinions, preferences, experiences, knowledge, or behavior. You can distribute surveys through email, phone, and in-person interviews, among other strategies. When creating your surveys, be careful to word your questions in a way that doesn’t elicit any bias to ensure you collect usable, high-quality data.
Using this data collection method, the researcher observes the subject to record and notes how they engage with certain variables or objectives. For example, you could use the observation method to test a new website design and gain insight into how easy or challenging navigating the site is for users.
Interviews fall into three categories depending on how they're conducted:
Structured interviews follow the same set of questions, asked in the same order for each participant.
Unstructured interviews are more open and don’t follow a predetermined list of questions.
Semi-structured interviews have predetermined questions, but the order in which you ask them can differ, and spontaneous questions are also acceptable.
Data from social media is great for gaining insights about your industry, consumers, and the success of a marketing campaign. Data you can collect from social media includes demographic information, likes, follows, and other engagement metrics that allow you to understand people’s interests and the type of content they interact with.
Secondary data from documents and records, such as research journals, is a great way to collect accurate and easily accessible data since they have already fulfilled scientific purposes. Unbiased records from hospitals are another example of quality data sources you can use in health care settings, provided you can obtain legal access to records.
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