Internal sources of data are those that are internal to the organisation in question. For instance, if you are doing a research project for an organisation (or research institution) where you are an intern, and you want to reuse some of their past data, you would be using internal data sources.
The benefit of using these sources is that they are easily accessible and there is no associated financial cost of obtaining them.
External sources of data, on the other hand, are those that are external to an organisation or a research institution. This type of data has been collected by “somebody else”, in the literal sense of the term. The benefit of external sources of data is that they provide comprehensive data – however, you may sometimes need more effort (or money) to obtain it.
Let’s now focus on different types of internal and external secondary data sources.
There are several types of internal sources. For instance, if your research focuses on an organisation’s profitability, you might use their sales data. Each organisation keeps a track of its sales records, and thus your data may provide information on sales by geographical area, types of customer, product prices, types of product packaging, time of the year, and the like.
Alternatively, you may use an organisation’s financial data. The purpose of using this data could be to conduct a cost-benefit analysis and understand the economic opportunities or outcomes of hiring more people, buying more vehicles, investing in new products, and so on.
Another type of internal data is transport data. Here, you may focus on outlining the safest and most effective transportation routes or vehicles used by an organisation.
Alternatively, you may rely on marketing data, where your goal would be to assess the benefits and outcomes of different marketing operations and strategies.
Some other ideas would be to use customer data to ascertain the ideal type of customer, or to use safety data to explore the degree to which employees comply with an organisation’s safety regulations.
The list of the types of internal sources of secondary data can be extensive; the most important thing to remember is that this data comes from a particular organisation itself, in which you do your research in an internal manner.
The list of external secondary data sources can be just as extensive. One example is the data obtained through government sources. These can include social surveys, health data, agricultural statistics, energy expenditure statistics, population censuses, import/export data, production statistics, and the like. Government agencies tend to conduct a lot of research, therefore covering almost any kind of topic you can think of.
Another external source of secondary data are national and international institutions, including banks, trade unions, universities, health organisations, etc. As with government, such institutions dedicate a lot of effort to conducting up-to-date research, so you simply need to find an organisation that has collected the data on your own topic of interest.
Alternatively, you may obtain your secondary data from trade, business, and professional associations. These usually have data sets on business-related topics and are likely to be willing to provide you with secondary data if they understand the importance of your research. If your research is built on past academic studies, you may also rely on scientific journals as an external data source.
Once you have specified what kind of secondary data you need, you can contact the authors of the original study.
As a final example of a secondary data source, you can rely on data from commercial research organisations. These usually focus their research on media statistics and consumer information, which may be relevant if, for example, your research is within media studies or you are investigating consumer behaviour.
TABLE 5 summarises the two sources of secondary data and associated examples:
Dissertation MethodologySearch for PhD COURSES
If you are a taking a taught or research-based masters course, or doing a PhD , then you will likely be asked to present a dissertation that includes research and data from a project of your own design. One of the key factors in writing a dissertation that successfully presents your research is the Dissertation Methodology.
What is the Methodology?
This is the section of your dissertation that explains how you carried out your research, where your data comes from, what sort of data gathering techniques you used, and so forth. Generally, someone reading your methodology should have enough information to be able to create methods very similar to the ones you used to obtain your data, but you do not have to include any questionnaires, reviews, interviews, etc that you used to conduct your research here. This section is primarily for explaining why you chose to use those particular techniques to gather your data. Read more about postgraduate research projects here .
A Scientific Approach
The information included in the dissertation methodology is similar to the process of creating a science project: you need to present the subject that you aim to examine, and explain the way you chose to go about approaching your research. There are several different types of research, and research analysis, including primary and secondary research, and qualitative and quantitative analysis, and in your dissertation methodology, you will explain what types you have employed in assembling and analysing your data.
Explain your methods
This aspect of the methodology section is important, not just for detailing how your research was conducted, but also how the methods you used served your purposes, and were more appropriate to your area of study than other methods. For example, if you create and use a series of ‘yes’ or ‘no’ survey questions, which you then processed into percentages per response, then the quantitative method of data analysis to determine the results of data gathered using a primary research method. You would then want to explain why this combination was more appropriate to your topic than say, a review of a book that included interviews with participants asking open-ended questions: a combination of secondary research and qualitative data analysis.
Writing a Dissertation Methodology
It is important to keep in mind that your dissertation methodology is about description: you need to include details in this section that will help others understand exactly what you aimed to do, how you went about doing it, and why you chose to do it that way. Don’t get too bogged down in listing methods and sources and forget to include why and how they were suitable for your particular research.
Be sure you speak to your course advisor about what specific requirements there may be for your particular course. It is possible that you may need to include more or less information depending on your subject. The type of research you conducted will also determine how much detail you will need to include in the description of your methods. If you have created a series of primary research sources, such as interviews, surveys, and other first hand accounts taken by either yourself or another person active during the time period you are examining, then you will need to include more detail in specifically breaking down the steps you took to both create your sources and use them in conducting your research. If you are using secondary sources when writing your dissertation methodology, or books containing data collected by other researchers, then you won’t necessarily need to include quite as much detail in your description of your methods, although you may want to be more thorough in your description of your analysis.
You may also want to do some research into research techniques – it sounds redundant, but it will help you identify what type of research you are doing, and what types will be best to achieve the most cohesive results from your project. It will also help you write your dissertation methodology section, as you won’t have to guess when it comes to whether documents written in one time period, re-printed in another, and serialised in book form in a third are primary, secondary, or tertiary sources. Read more on dissertation research here .
Whether or not you have conducted your research using primary sources, you will still want to be sure that you include relevant references to existing studies on your topic. It is important to show that you have carefully researched what data already exists, and are seeking to build on the knowledge that has already been collected. As with all of your dissertation, be sure that you’ve fully supported your research with a strong academic basis. Use research that has already been conducted to illustrate that you know your subject well.
Draft as you go
Because your dissertation methodology is basically an explanation of your research, you may want to consider writing it – or at least drafting it – as you gather your data. If you are on a PhD course, or a longer master’s course, then you may be able to finish researching before you begin writing but it doesn’t hurt to start working on it early that way you can keep on top of what you need to do. Analysing your own methods of research may help you spot any errors in data collection, interpretation or sources.
An example of dissertation methodology structure
There are several ways that you can structure your methodology, and the following headings are designed to further give you a better idea of what you may want to include, as well as how you might want to present your findings:
Research Overview: where you reiterate the topic of your research.
Research Design: How you’ve set up your project, and what each piece of it aims to accomplish.
Data Collection: What you used to collect the data (surveys, questionnaires, interviews, trials, etc.). Don’t forget to includes sample size and any attempts to defeat bias.
Data Analysis: Finally, what does your data mean in the context of your research? Were your results conclusive or not? Remember to include what type of data you were working with (qualitative or quantitative? Primary or secondary sources?) and how any variables, spurious or otherwise factor into your results.
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