Data collection and analysis are the main part of every management dissertation. Different types of information can be collected or are available in the market. However, every piece of data available in the market cannot be used in a dissertation considering their quality and usability. Due to these constraints, data collection in the management dissertation becomes complex. Students need to understand the art of data collection and analysis to ensure dissertation quality. For more information read the following points.
Understanding the requirements and boundaries
Every dissertation topic differs from the other. Due to this reason, the forest step of data collection is to understand particular types of data that the dissertation needs. There can be two types of data depending on their quality. These data types of as follows:
- Quantitative data or numerical information
- Qualitative data or non-numerical information
Depending on the nature of the source data can be divided into two types. These types are as follows:
- Primary data or unique data collected by the dissertation writer
- Secondary data or data collected from a third-party source
Combining data type and source there can be 4 types of data such as qualitative-primary, qualitative secondary, quantitative primary and quantitative secondary. Understanding the type or types of data that a dissertation needs is difficult without considerable experience. Dissertation help is essential; when it comes to deciding data requirements.
More than that, data collection boundaries also need to be decided. Unauthentic information keeps circulating in the internet and society. Using this type of data can lower the dissertation quality. To understand how to choose suitable data “keep reading”.
Data collection
- For primary quantitative data, students need to conduct data collection processes such as surveys, focus group surveys and so on.
- For collecting primary qualitative data students need to conduct an interview, focus group interview, group discussion and many more similar processes,
- For collecting both secondary qualitative and quantitative data students need to search archives.
Considering the above points, the data collection process may look simple. However, there is more to it than the simple description provided above. For example, a suitable sample size needs to be chosen for collecting data. The dissertation writer also needs to prepare Questionnaires, consent should be taken from participants. This process requires a considerable amount of effort and small mistakes can fail the whole process. To avoid such failure, dissertation help should be taken.
In the case of secondary data collection, the researcher cannot collect data from personal blogs. Information can only be collected from published journals, news articles, books, company websites and other such sources that publish authentic management information. The quality of the published sources also needs to be evaluated to ensure the quality of the dissertation results. The quality of the dissertation of the secondary data sources can only be validated by evaluating their data sources. Doing such a complex procedure requires a considerable amount of effort, time and experience. Students receive limited time for dissertation writing. Due to this reason, it becomes difficult to complete such a lengthy process while maintaining other academic careers. A dissertation can help solve this issue.
Data analysis
A more important part of a dissertation compared to data collection is analysis. In the above discussion, it can be seen that there are different types of data that can be collected. There are a large number of data analysis processes including various statistical analysis and qualitative data analysis techniques. Some of the prominent data analysis methods used in management dissertations are as follows:
- Thematic analysis
- Case study analysis,
- Regression analysis
- T-test
- Correlation analysis
Analysis technique needs to be chosen depending on the dissertation objective and the type of data collected. If the proper data analysis technique is not chosen then it becomes impossible to complete dissertation objectives hence students fail to satisfy instructors. For avoiding such failures it is essential to get dissertation help in dissertation writing. Dissertation help ensures that proper data collecting and analysis methods have been used to fulfil the objectives. After the whole data analysis, it needs to be reviewed to identify and solve errors, which is not uncommon in data analyses. However, without expertise, it becomes difficult to identify and address such issues effectively.
Conclusion
The above discussion highlights different types of data collection and analysis processes can be used under a management dissertation. There are no particular rules when it comes to deciding the required data and analysis process. The researcher needs to choose a suitable method for dissertation writing. However, due to the availability of a large number of options, it often becomes difficult to choose the correct one. For securing a quality dissertation help is essential. The dissertation helps ensure that proper data collection and analysis process is applied which can help to gain a good mark.
