Introduction to Secondary Data Analysis
The vast amount of data is getting generated and collected by students, researchers and professionals across the globe. Due to this, the efficient utilization of the current data is important. Secondary Data Analysis is one such technique which does empirical data analysis on the collected data with reference to the current data for some other purpose. This helps the researchers to quickly analyze the data when time and resources are limited. The technique is quite popularly being used by the research community. It was also being used by great social researchers like Max Weber, Karl Max etc. in prior decade.
What is Secondary Data Analysis?
According to Nachmias, Secondary Data Analysis is defined as gathering of data by researchers for some different use case. Punch stated it as re-analyzing of the prior gathered data which was already analyzed. Another definition which adds up to the above definition states that new ideas conceived by research depends on the previously gathered data by the other researchers. In simple terms, it can be stated as second-hand analysis technique. It can be used as an all use-cases market research tool.
However, there are some critics to it arguing that it might lead to a loss in accuracy of data as the researcher will not have control over the data collection process. Another argument states that the data sources being used for performing secondary data analysis might not be related.
Methodologies of Secondary Data Analysis
Secondary data analysis depends on the data source. The data source is dependent on the research areas. For example, to understand the socioeconomic and macroeconomic policies of a country, statistical data provides the most viable option. If a survey is being conducted by the country for let us say voter turnout in the upcoming election. Then census data helps the researchers to understand the same and do secondary analysis on it.
The following steps are being used by the researchers to carry out secondary data analysis.
- Purpose of Research: The researchers must know why they are carrying out research on the gathered data.
- Data tracking: The researchers can use the internet to get access to state of art data collection and gathering techniques for a different purpose.
- Importance of data: The researchers must know the underlying processes being used during data gathering like populating sub-sampling strategies, when and how it was gathered etc.
- Integrity of data: The credentials of the researcher who has done data collection and gathering for some other purpose must be verified. Also, questions like data consistency and problems associated with the same must be addressed.
- Data Analysis: Various statistical processes can be used to get inferences and the corresponding underlying patterns.
Steps Involved in Secondary Data Analysis
- Documentary Data: It is used by the researchers to carry out the projects which use primary data gathering techniques. It uses the following types of documents i.e. Written and Non-Written documents stated below:
- Written documents: It involves minutes of meeting, shareholders report, speech transcripts, correspondence, notices etc.
- Non-Written documents: It uses the digital encoding format like video and tape recordings, television and film programs, CD/DVD etc.
Survey Based Secondary Data
It usually involves data gathered by questionnaires that were already analyzed for some different use-case. It uses the following type of surveys:
- Censuses: It is used by the government like a population survey or voter turnout but the participation is optional. It provides comparative and contextual data for research purposes.
- Continuous and Regular Surveys: It excludes the above method and repeated over a period of time. It involves surveys that gathered data throughout the year and also those which occur repeatedly and at regular intervals. It provides comparative and contextual data for research purposes.
- Ad-hoc Survey: It does not happen regularly and is more of a one-off. It is more specific in a particular research area. The data comes from surveys conducted by the organizations as well as governments as well as those carried out by the independent researchers. To find viable and relevant surveys in this category is deemed difficult.
- Multiple Source Secondary Data: It is either documentary data or survey data or a combination of both. Here the main idea is combining data from different sources to make another data source prior to the use of current data.
Benefits of using Secondary Data Analysis
Below are the benefits of using Secondary Data Analysis:
- Cost-effective: Less investment in money, time, or effort is required as the data is gathered prior by some other researcher. Also, the gathered data is cleaned and stored in some type of electronic format. Thus, the researcher does not have to spend time on data pre-processing instead can focus on how to perform data analysis.
- Reduced volume: Secondary data analysis allows the researcher to collect a specific subset of data instead of collecting large volumes of data. Thus, data can be scaled geographically as large amount of data is already gathered and analyzed by the government and organizations.
- Level of Professionalism: It maintains a certain level of expert know-how and professionalism which may not be the case for individuals carrying out independent research. As it involves people with some skill and level of expertise, a better gathering of secondary data can be expected.
- Unobtrusive: It does not obstruct and hamper the current research being carried out by the researchers.
- Type of Data: It provides researchers with contextual and comparative data.
- Scientific breakthroughs: It can lead to unforeseen discoveries and scientific breakthroughs as previously analyzed data for some other purpose is being used as the benchmark.
- Data Permanence: It provides the permanency of the data analyzed for some research purposes.
Secondary Data Analysis though having some disadvantages and critics have benefitted the researchers using it. However, the researchers using this technique must know about the shortcomings of techniques like loss of data accuracy, data sufficiency and data importance for effectively using this technique and minimizing the threats posed by it.
This is a guide to Secondary Data Analysis. Here we discuss the introduction to Secondary Data Analysis along with methodologies, steps involved and benefits. You can also go through our other related articles to learn more –