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Data Analysis: what is it? Benefits
Data analysis is the science that is responsible for examining a set of data with the purpose of extracting
conclusions about the information in order to make decisions, or
Simply expand knowledge on various topics.
Data analysis is the science that is responsible for examining a set of data in order to draw conclusions about the information to make decisions, or simply expand knowledge on various topics.
Data analysis consists of submitting the data to operations, this is done in order to obtain precise conclusions that will help us achieve our objectives, these operations cannot be previously defined since data collection may reveal certain difficulties.
Currently, many industries use data analysis to draw conclusions and decide on actions to implement. It is worth mentioning that science also uses data analysis to prove or rule out existing theories or models.
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Uses of data analysis
Data analysis is used in many industries, regardless of the industry, it gives us the basis for making a decision or not, or ascertaining whether a hypothesis is true or not.
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Marketing: Data analytics has been used primarily to predict consumer behavior, including qualifying it. Learn how to do data analysis for your marketing campaign.
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Human Resources: data analysis is also very useful within companies to maintain a good working environment, and outside of it, qualifying potential employees.
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Academics: Like companies, data analysis is also present in education, it is used to select new students and to measure student performance.
Data analysis techniques
If we want useful data, we must analyze it. For this, we must resort to various techniques that depend on the type of information that is being collected, so it is important to have defined the technique to be used before implementing it.
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Qualitative data analysis: Qualitative data is presented verbally (sometimes in graphs). It is based on interpretation. The most common ways to obtain this information is through open interviews, focus groups, and observation groups, where researchers typically analyze patterns in observations throughout the data collection phase.
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Quantitative data analysis: Quantitative data is presented in numerical form. It is based on tangible results.
Data analysis focuses on reaching a conclusion based solely on what is already known by the researcher. The way you collect your data should relate to how you are planning to analyze and use it, you also need to make sure you collect accurate information that you can trust, there are many data collection techniques for this.