What is The Field of Data Analysis?

In the business world, data analysis plays an important role in making more effective decisions and has become one of the most important areas of the future and a factor of corporate success and help companies to work more productively and efficiently.
Data analysis has multiple aspects and methods, including various technologies as it is related to artificial intelligence, and aims to give a simplified picture of large data in the form of charts, graphs and curves that cross, interpret and analyze that data and then use this data in the analysis of the conditions of global markets such as trading platforms and currencies.
Its importance lies in the transformation of increasingly large and complex data into clear data that reflects the future of companies, showing the level of progress or decline of companies so that decisions can be made correctly and plans can be developed to increase their success.
So, data analysis is the process of studying, organizing and arranging certain information and data, in order to bring it out and highlight it in the form of information and represent it in charts and graphs so that it becomes easy to understand and explain to the rest of the team members, in order to conclude and reach the answer with ease, and to analyze the data many ways vary according to the field used, where we can use data analysis in the sciences, social sciences and finance as well.
Stages of the data analysis process:
* Define data requirements
* Data collection
* Data organization
* Data checking
* System data modeling
* Relationship analysis
* Database design
As for the programming languages used in data analysis, there are two leading languages in the field of data analysis, namely Python & R, where they are the best to use in analyzing data intelligently and are one of the easiest languages to learn, because they do not require prior knowledge of programming.
Data analysis aims to model data, often using charts and graphs that are somewhat similar to data flow charts, also the field of data analysis aims to simplify things as much as possible, working to come up to reach an optimal solution. data modeling is usually done in three steps, the first is done in the analysis of the system, while the second and third steps are done in the design phase.

Forms of data analysis
• Descriptive analysis of data: is a description of the content of the data summary.
• Exploratory data analysis: attempts to find and identify relationships and correlations of several different variables in order to work out specific ideas and hypotheses.
• Deductive data analysis: the most important and most commonly used data analysis that measures and calculates a number of different relationships between available measurements.
• Predictive data analysis: a number of assigned measurements are expected from existing measurements.
• Causal analysis of data: calculates certain metrics if one of the other metrics changes.
• Mechanical analysis of data: is to find a definite and inevitable relationship between two measurements.