Data Collection

Data is very important to solve any problem, the correctness of the data is equally important as the data is there. We at HoldHigh constantly strive to get the best data and provide specific data for projects to organizations and/or individuals. All the data collection process is implemented with integrity and as per the requirement. 

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Every kind of data has a rare quality of describing things after assigning a specific value to it. For analysis, we organize these values, process and present in a given context, to make it useful. Data can be in different forms; here are the primary data types.

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• Qualitative data: When the data presented has words and descriptions, then we call it qualitative data. Although you can observe this data, it is subjective and harder to analyze data in research, especially for comparison. Example: Quality data represents everything describing taste, experience, texture, or an opinion that is considered quality data. This type of data is usually collected through focus groups, personal qualitative interviews, or using open-ended questions in surveys.

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• Quantitative data: Any data expressed in numbers of numerical figures are called quantitative data. This type of data can be distinguished into categories, grouped, measured, calculated, or ranked. Example: questions such as age, rank, cost, length, weight, scores, etc. everything comes under this type of data. You can present such data in graphical format, charts, or apply statistical analysis methods to this data. The (Outcomes Measurement Systems) OMS questionnaires in surveys are a significant source of collecting numeric data. 

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• Categorical data: It is data presented in groups. However, an item included in the categorical data cannot belong to more than one group. Example: A person responding to a survey by telling his living style, marital status, smoking habit, or drinking habit comes under the categorical data. A chi-square test is a standard method used to analyze this data.