The definition of data analysis is the process of collecting, modeling, and analyzing data to extract strategies that support decision-making. There are many methods and techniques for data analysis depending on the field and objective of the analysis, All these different methods of data analysis are based largely on two basic areas: quantitative methods and qualitative methods in research.
Before going into detail about the categories of data analysis along with their methods and techniques, you must understand the capabilities that data analysis can bring to your organization.
Let's start with customers, they are arguably the most By using data .important component of any business analysis to gain a comprehensive view of all aspects of your customers, you can understand the channels they use to communicate with you, demographics, interests, habits, buying behaviors, and more.
In the long run, this will lead to the success of your marketing strategies, allow you to identify new leads, and avoid wasting resources targeting the wrong people or sending the wrong message. You can also track customer satisfaction reviews or the performance of your customer service department.
From a managerial perspective, you can also benefit analyzing your data analysis helps you make business decisions based on facts and not simple intuition.
For example, you can understand where to invest your cap perspective covereth opportunities, anticipate income, You or tackle familiar before they become problems. can relevant information from all areas in your organization and present the data to stakeholders.
the process of data analysis is very important for the company because it provided a lot of advantage to campanies , there are 7 types of data analysis.
It is the analysis of a large set of data such as census data, statistics, or elements in the composition of a particular article to help the researcher in interpreting the variables on the phenomenon.
It analyzes some data to find new exploratory results, to answer future studies and questions. Before starting any exploratory analysis, must identify data sources to achieve exploratory goals.
It aims to use small samples of data and infer large results. This type of analysis symbolizes the data of the population and depends on randomness in the selection of samples and the normal distribution.
It contains multiple types of methods that predict future events and depends on linking positions to each other, and most companies use this type of analysis to know the extent of losses and gains that they have obtained.
It is the gold standard for data analysis, as it depends on conducting random studies to extract the multiple aspects of the process of obtaining data, and it is not possible to deduce probabilities of occurrence with the stability of conditions only, but also with the possibility of their occurrence.
Automated analysis helps to understand subtle changes that lead to individual variables, and this kind of inference is only made in very few cases It is through randomized trial dates.
Data analysis is used by Big companies, small businesses, retail companies, in medicine, and even in the world of sports. It's a universal language and more important than ever before.
there are 3 methods of data analysis
through which the researcher can analyze logically and realistically the impact of various variables on a particular phenomenon.
This is an analysis associated with many programs such as (excel, Statistica, SAS) and it is related to statistical processors.
Finally, the science of data analysis is the most important part of the company as it analyzes past data and current data to anticipate the future and make it better.