Primary data is original research data in its raw form, without any analysis or processing. This data provides a wealth of information for researchers. Depending on the nature of a study, the primary data may be provided along with reports and analysis so readers can look at it directly, or it may be kept confidential. Access to this data can be very valuable for people who want to learn more about study methodology, anomalies that occurred during studies, and other topics.
This data can contain results from empirical testing, transcripts of interviews and surveys, and recorded observations. A person conducting a study on mice, for example, would have primary data like test results from blood and urine analysis, along with detailed observations of the mice on a day-to-day basis. The primary data could also include x-rays, brain imaging, and other diagnostic imaging, depending on the nature of the study.
People can distinguish primary data from other kinds of data by the fact that it is directly collected and presented without commentary. Secondary data consists of things like research papers based on the data. The major disadvantage of primary data is the sheer volume of information. People would need to read through pages and pages of information to extract usable data. In data processing, researchers use statistics and other tools to present the data in a more accessible format, turning raw results into meaningful statements like “20% of study participants reported feeling nauseous.”
Primary data records may be digital or hard copy, depending on the nature of the study. Digitization is very common with many studies because it makes it easier to transmit and review the data. A digital copy is easier to work with during analysis and reduces the risk of analytical errors. As long as people enter data correctly the first time, it will be accurate in statistics programs and other tools people use to explore the raw data.
Data analysis can break down the data into useful components for people who may have an interest in the study. It will also discuss outliers and things in the data that did not make sense, such as a single person in a study who failed to respond to an otherwise effective treatment. In analysis, researchers have an opportunity to probe into the information to draw useful conclusions about the research. They can also offer theories and explanations about mysteries found in the data.