Data analysis, my friend, is a really wonderful field, it generates an intelligent and ambitious person from you and wants to produce more new ideas as well, and as you know that the field of data analysis has become something necessary in the future, and it is a field that has also become in demand in many companies, and it is for the record that data analysis is radically related to the field of machine learning, artificial intelligence and deep education as well, and this field of data analysis aims to give a simplified picture of big data in the form of charts, graphs and graph curves that express, interpret and analyze that data, and this data is often used with intelligent software add-ons for analyzing global market conditions such as trading platforms and Currencies, Price Control and so on, and because I understand in the field of data analysis, I strongly advise you to learn it, because you will lose something wonderful from your software, technical, technological and information path as well…
So: the definition of data analysis in short :
In short, data analysis is the process of studying, analyzing, disassembling, organizing, and arranging certain information and data and representing them in charts and graphs with the aim of concluding and reaching the answer with ease, and there are many uses and methods in the field of data analysis, we mentioned the short and simple side only for beginners, and after deepening and knowing more, you can then discover the sweetness of this field yourself.
The best programming languages on your path to data analysis :
As we know the leading languages in this field are:” Python Python “and” R ” because they are the appropriate and best languages to use and we deal with data analysis intelligently and in many ways, other languages can also be relied on, but not very much innocently, so if you want to enter the field of data analysis, learn Python and the R language, don’t be afraid, they are two completely easy languages and you don’t need effort and time to learn them and they don’t need prior knowledge of programming either, and if you want to contact us to help you with that.
The purpose and purpose of data analysis :
Since the field of data analysis is the most exciting and influential field of technology in our time, its goal is to simplify things far beyond big or huge data and come up with a specific goal and solution, which gives a perception and guess of events and will help to reach answers that can be sufficiently feasible for a particular issue or problem and research them to finally come to an optimal conclusion and a completely convincing solution. These are some goals, but there is a lot you can go deeper into them, some learn the basics, and the nice thing about it is if you learn the basics of data analysis, the field of machine learning and deep learning will be easy to learn for you, just increase some things and certain properties and become a kind of expert in both fields.
Some methods and stages of data analysis :
The methods differ from the stages here and we will mention simple examples of each of them, and start with the methods of data analysis :
Analysis by statistics: statistical analysis is done by some programs and some specific commands, such as the famous Excel program.
Descriptive analysis: it is the one through which it is possible to search with prevention and complete logic to describe a certain phenomenon or information.
Qualitative analysis: it is one of the branches of analytical chemistry, which is usually used in medicine and chemistry.
And these are some stages of data analysis :
Analyzing data and converting it into information:
this stage is in order to collect the largest number of useful information, which ends with an important result and Conclusion, which we need, and also provides us with a solution to some of the questions entered and prefers to be many for the accuracy of the analysis.
Data entry:
it is a basic stage in which information and questions are entered to be analyzed and solved in the best ways and conclusions, and this stage can also be done by entering information into a specific program, but attention and accuracy of the information entered must be paid.
And many, many other stages that you can study when you enter the field.
