Data is becoming easily accessible to researchers all over the world, and the practicality of utilizing secondary data for research is becoming more prevalent, same as its questionable authenticity when compared with primary data.
These two data types can be a double-edged sword when used for research because they can both make or break a project.
Simply put, both primary and secondary data have their pros and cons. So, it’s up to the researcher to decide which one is better when doing research.
Primary data is the kind of data that is collected directly from the data source without going through any existing sources. It is mostly collected specially for a research project and may be shared publicly to be used for other research
Primary data is often reliable, authentic, and objective in as much as it was collected with the purpose of addressing a particular research problem. It is noteworthy that primary data is not commonly collected because of the high cost of implementation.
A common example of primary data is the data collected by organizations during market research, product research, and competitive analysis. This data is collected directly from its original source which in most cases are the existing and potential customers.
Most of the people who collect primary data are government-authorized agencies, investigators, research-based private institutions, etc.
Read More: Primary Data: Definition, Examples & Collection Techniques
Secondary data is data that has been collected in the past by someone else but made available for others to use. They are usually once primary data but become secondary when used by a third party.
Secondary data are usually easily accessible to researchers and individuals because they are mostly shared publicly. This, however, means that the data are usually general and not tailored specifically to meet the researcher’s needs as primary data does.
For example, when conducting a research thesis, researchers need to consult past works done in this field and add findings to the literature review. Some other things like definitions and theorems are secondary data that are added to the thesis to be properly referenced and cited accordingly.
Some common sources of secondary data include trade publications, government statistics, journals, etc. In most cases, these sources cannot be trusted as authentic.
Read More: What is Secondary Data? + [Examples, Sources, & Analysis]
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Primary data comes directly from your research, so it’s more reliable and trustworthy. Your primary data can only be wrong if there is a mix-up in your research. However, primary data is expensive and time-consuming.
Secondary data, on the other hand, is less expensive, time efficient, and helps you extract other researcher’s findings and use their results for your research. But it’s not as reliable as primary; what if the previous researcher manipulated the data?
Primary data is the type of data that is collected by researchers directly from main sources while secondary data is the data that has already been collected through primary sources and made readily available for researchers to use for their own research.
The main difference between these 2 definitions is the fact that primary data is collected from the main source of data, while secondary data is not.
The secondary data made available to researchers from existing sources are formerly primary data that was collected for research in the past. The availability of secondary data is highly dependent on the primary researcher’s decision to share their data publicly or not.
An example of primary data is the national census data collected by the government while an example of secondary data is the data collected from online sources. The secondary data collected from an online source could be the primary data collected by another researcher.
For example, the government, after successfully the national census, shares the results in newspapers, online magazines, press releases, etc. Another government agency that is trying to allocate the state budget for healthcare, education, etc. may need to access the census results.
With access to this information, the number of children who needs education can be analyzed, and hard to determine the amount that should be allocated to the education sector. Similarly, knowing the number of old people will help in allocating funds for them in the health sector.
The type of data provided by primary data is real-time, while the data provided by secondary data is stale. Researchers are able to have access to the most recent data when conducting primary research, which may not be the case for secondary data.
Secondary data have to depend on primary data that has been collected in the past to perform research. In some cases, the researcher may be lucky that the data is collected close to the time that he or she is conducting research.
Therefore, reducing the amount of difference between the secondary data being used and the recent data.
Researchers are usually very involved in the primary data collection process, while secondary data is quick and easy to collect. This is due to the fact that primary research is mostly longitudinal.
Therefore, researchers have to spend a long time performing research, recording information, and analyzing the data. This data can be collected and analyzed within a few hours when conducting secondary research.
For example, an organization may spend a long time analyzing the market size for transport companies looking to talk into the ride-hailing sector. A potential investor will take this data and use it to inform his decision of investing in the sector or not.
Primary data is available in crude form while secondary data is available in a refined form. That is, secondary data is usually made available to the public in a simple form for a layman to understand while primary data are usually raw and will have to be simplified by the researcher.
Secondary data are this way because they have previously been broken down by researchers who collected the primary data afresh. A good example is the Thomson Reuters annual market reports that are made available to the public.
When Thomson Reuters collect this data afresh, they are usually raw and may be difficult to understand. They simplify the results of this data by visualizing it with graphs, charts, and explanations in words.
Primary data can be collected using surveys and questionnaires while secondary data are collected using the library, bots, etc. The differences between these data collection tools are glaring and can it be interchangeably used.
When collecting primary data, researchers lookout for a tool that can be easily used and can collect reliable data. One of the best primary data collection tools that satisfy this condition is Formplus.
Formplus is a web-based primary data collection tool that helps researchers collect reliable data while simultaneously increasing the response rate from respondents.
Primary data sources include; Surveys, observations, experiments, questionnaires, focus groups, interviews, etc., while secondary data sources include; books, journals, articles, web pages, blogs, etc. These sources vary explicitly and there is no intersection between the primary and secondary data sources.
Primary data sources are sources that require a deep commitment from researchers and require interaction with the subject of study. Secondary data, on the other hand, do not require interaction with the subject of study before it can be collected.
In most cases, secondary researchers do not have any interaction with the subject of research.
Primary data is always specific to the researcher’s needs, while secondary data may or may not be specific to the researcher’s needs. It depends solely on the kind of data the researcher was able to lay hands on.
Secondary researchers may be lucky to have access to data tailored specifically to meet their needs, which mag is not the case in some cases. For example, a market researcher researching the purchasing power of people from a particular community may not have access to the data of the subject community.
Alternatively, there may be another community with a similar standard of living to the subject community whose data is available. The researcher mag uses to settle for this data and use it to inform his conclusion on the subject community.
Some common advantages of primary data are its authenticity, specific nature, and up to date information while secondary data is very cheap and not time-consuming.
Primary data is very reliable because it is usually objective and collected directly from the original source. It also gives up-to-date information about a research topic compared to secondary data.
Secondary day, on the other hand, is not expensive making it easy for people to conduct secondary research. It doesn’t take so much time and most of the secondary data sources can be accessed for free.
The disadvantage of primary data is the cost and time spent on data collection while secondary data may be outdated or irrelevant. Primary data incur so much cost and takes time because of the processes involved in carrying out primary research.
For example, when physically interviewing research subjects, one may need one or more professionals, including the interviewees, videographers who will make a record of the interview in some cases and the people involved in preparing for the interview. Apart from the time required, the cost of doing this may be relatively high.
Secondary data may be outdated and irrelevant. In fact, researchers have to surf through irrelevant data before finally having access to the data relevant to the research purpose.
Primary data is more accurate and reliable while secondary data is relatively less reliable and accurate. This is mainly because the secondary data sources are not regulated and are subject to personal bias.
A good example of this is business owners who lay bloggers to write good reviews about their products just to gain more customers. This is not the case with primary data which is collected by the researcher himself.
One of the researcher’s aims when gathering primary data for research will be gathering accurate data so as to arrive at correct conclusions. Therefore, biases will be avoided at all costs (e.g. same businesses when collecting feedback from customers).
Primary data is very expensive while secondary data is economical. When working on a low budget, it is better for researchers to work with secondary data, then analyze it to uncover new trends.
In fact, a researcher might work with both primary data and secondary data for one research. This is usually very advisable in cases whereby the available secondary data does not fully meet the research needs.
Therefore, a little extension on the available data will be done and cost will also be saved. For example, a researcher may require a market report from 2010 to 2019 while the available reports stop at 2018.
The time required to collect primary data is usually long while that required to collect secondary data is usually short. The primary data collection process is sometimes longitudinal in nature.
Therefore, researchers may need to observe the research subject for some time while taking down important data. For example, when observing the behavior of a group of people or particular species, researchers have to observe them for a while.
Secondary data can, however, be collected in a matter of minutes and analyzed to dead conclusions—taking a shorter time when compared to primary data. In some rare cases, especially when collecting little data, secondary data may take a longer time because of difficulty consulting different data sources to find the right data.
Read Also – What is Secondary Data? + [Examples, Sources & Analysis]
Primary and secondary data have their strengths and weaknesses but they complement each other. The strength of primary data is secondary data’s weakness and vice versa. So, when you combine the two you get a complete picture of your research findings.
The secondary data provides the background for your research and helps you know if you’re on the right path or the previous researchers missed something. However, primary data helps you know the current situation.
Let’s say you want to launch a product and you’re looking for its market fit, secondary data helps you understand past and current trends. Primary data on the other hand collects your customer opinions and perspective, helping you know to meet their needs with the new product.
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Secondary data was once primary data when it was newly collected by the first researcher. The content of the data collected does not change and therefore has the same content as primary data.
It doesn’t matter if it was further visualized in the secondary form, the content does not change. A common example of these are definitions, theorems, and postulates that were made years ago but still remain the same.
Primary data and secondary data are both used in research and statistics. They can be used to carry out the same kind of research in these fields depending on data availability. This is because secondary data and primary data have the same content. The only difference is the method by which they are collected.
Since the method of collection does not directly affect the uses of data, they can be used to perform similar research. For example, whether collected directly or from an existing database, the demography of a particular target market can be used to inform similar business decisions.
When performing research, it is important to consider the available data options so as to ensure that the right type of data is used to arrive at a feasible conclusion. A good understanding of the different data types, similarities, and differences is however required to do this.
Primary data and secondary data both have applications in business and research. They may, however, differ from each other in the way in which they are collected, used, and analyzed.
The most common setback with primary data is that it is very expensive, which is not the case for secondary data. Secondary data, on the other hand, has authenticity issues.
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