There are no second opinions about the fact that data is a crucial element of all systems that surround us today. Whether you are trying to run a business and want to offer products or services that are more relevant to your target audience, or are interested in drawing insights, the fact remains that data remains an extremely important factor.
With that said, however, the majority of people remain confused as to how they must go about data collection and all that one can achieve with it. That’s exactly why we’ll be talking all about the different methods of data and their collection in this article, to ensure that you know how to make the most of the data that you gather and collect.
Why is Data Collection Important?
As mentioned above, data has a variety of purposes and usages in today’s day and age. Regardless of whether you’re taking digitization into account, data is all around us, and needs to be studied to draw insights, make predictions, and manage processes in a way that can add value. By collecting data and information based on metrics, factors, or variables, it does not only become far easier for us to make informed decisions, but doing so is also imperative to ensure that our businesses and systems do not have to take the hit.
Needless to say, there are standards that need to be implemented to ensure that data is collected in an accurate manner. If the right measures are not taken into account, there can be a number of different consequences including not being able to find solutions or draw conclusions for the study or research in question and not being able to validate the results. Moreover, if the right methods are not used for data collection, another possibility is that the decisions might have to be compromised, leading to the integrity of the results being questioned.
What Are the Different Types of Data?
Data can be generalized into two large groups, namely qualitative and quantitative data. As the name suggests, qualitative data is the name given to the group of data that pertains to immeasurable qualities. Quantitative data, on the other hand, is measurable with the help of numbers.
While the groups mentioned above are merely categories, there are three major subtypes of data namely primary, secondary, and mosaic data. Below, we will introduce you to each of these different types of data in detail, and explain how each of these types of data can be collected.
Primary Data
Primary data is data that is collected through firsthand experiences, studies or research. Unlike the other types of data, the person responsible for collecting the data himself conducts studies and researches in order to gather the information and make deductions or reach conclusions as necessary.
Since different kinds of data is required for different scenarios, there are a number of different ways in which primary data can be collected. Some of the most popular techniques for collecting primary data include questionnaires, experiments, and surveys. Once this data is collected, it needs to be structured, organized, and evaluated for best results.
Secondary Data
Unlike primary data, secondary data is data or information that has been collected from other sources. This may include research, studies, or surveys conducted in the past. One thing that is important to note is that since secondary data is essentially secondhand information, the process for collecting secondary data is often less time consuming and relatively easier than the process that one must go through for the collection of primary data.
Mosaic Data
Mosaic data refers to data and information that is collected by putting together bits and pieces of information that is already publicly available. The major difference between mosaic data and secondary data is that while the sources of both of these types of data are already publicly available, collectors of mosaic data need to reach their own conclusions with the data.
Now that you understand the importance of data collection and the different technique that can be used, it will be easier for you to get the results that you need.
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