The Future of Software industry: A look into the current trends.
A detailed data analysis of the software industry — its current and future possible trends
Bill Gates, the co-founder of Microsoft, had once said: “Software is a great combination between artistry and engineering.” Today this combination of art and science is ubiquitous, used in a variety of everyday products. The importance of software in the innovation process has been measured by the patents citing software-based technologies in these industries. These have seen a large uptick over the last few decades.
The software industry expanded in the early 1960s, almost immediately after computers were first sold in mass-produced quantities. Universities, government, and business customers created a demand for software. Both national and international companies are playing crucial roles in the rapid growth of the countries to become the leading most destination globally for Software Outsourcing Services.This blog of mine deals with the analysis of a data set of the software industry so that we can get to know about it’s future and it’s current trends.
Here we go…
The following table shows the first six rows of the data set,thereby giving us insight about what sort of data-set it is. And what are the attributes included in the data-set.The entire data set consists of 88883 rows and 85 columns.A quite large data set though!
The first stage of data analysis involves asking the right questions from the data set.The probable questions can be like,
- Which of the rows and columns present in the data set are required for analysis?
- What can the correlation between the different data?
- Which of the data are not required for analysis?
- Is data preprocessing required?
The second stage is known as Data Wrangling or Data Munging.It consists of three steps:
- Acquiring the data
For the dataset used in this blog,we are importing the required libraries for the analysis.
We are now reading the csv file ‘survey_results_public.csv’.The attributes of the data can be seen now.
- Assessing the data
Now,we are finding out the number of rows and columns present in the data-set.The data types of the various columns of the data set are also checked.
The command dataset_name.columns gives the names of the columns present in the data set.From the dataset used in this blog,it is found that the column names are a bit complex for use and data type of the data set is ‘object’.
- Data Cleaning
In this process, we are dropping the columns that are not important for our analysis.For example, I have dropped the columns like ‘Currency Symbol’ , ’Currency Desc’ , ’Comp Total’ , ’Comp Freq’ , ’Converted Comp’ , ’Workweek Hrs’ , ’Work Plan’ , ’Work Challenge’ , ’Work Remote’ , ’Work Loc ’ , ’Imp Syn’ , ’Code Rev’ , ’Code Rev Hrs’ , ’Unit Tests’ ,etc.The memory usage is also reduced after the columns are dropped.
The third stage is known as Exploratory Data Analysis(EDA).It is a statistical method of analysing the data.
For this dataset, we are finding out the top countries that have the most number of developers(taking age of more than 25).The developers working in companies, are responsible for the design, testing and maintenance of software programs for computer operating systems or applications, such as word processing or database management systems.Thus, the developers play an important role in software industry as well as enhancing the growth of the country.
Secondly, we are also finding out the top countries in which the citizens are learning to code(taking age of more than 20).The people learning to code, may be considered that they will be joining the software industry, as coding is an important source in the software industry.Therefore, this learners may be considered as the future pillars of the software industry.
I have also done Exploratory Data Analysis(EDA) on top two countries which have the most developed software industries i.e. United States and India.
The bar graph of ‘Education Level’ versus ‘Age’ shows that how many people have learned courses that are eligible for software industry, so that they can lead to it’s growth.
The correlation between the stack overflow parameters can be shown using heatmap.
The plot of ‘Years of Code’ versus ‘Age’ shows that how many people are experienced in coding so that they can serve the software industry.
The graphs showing parameters like ‘Database worked with’, ‘Database desire next year’ , ‘Programming languages desire next year’ also plays an important role in the analysis.
The fourth stage of data analysis is Drawing Conclusions.From this dataset,it can be concluded that the countries that will attain more development in the software industries are United States,India,Germany as they have a huge ratio of developers and coders.
The percentage of developers who are employed is also high in United Sates therefore contributing in the development of the industry,which can be seen from the bar graph below.
It may be taken into account that the software industry will be working on ‘Microsoft SQL Server’ , ‘SQLlite’ , ‘PostgreSQL’ databases on the upcoming years as the trend for these database management systems is quite high.
The need for programming languages like ‘Python’ , ‘C#’ , ‘Ruby’ , ‘VBL’ , ‘Java’ is more and therefore it can be concluded that the software industry will be recruiting people who have learned this languages and the workflow of the industry will be on the basis of these programming languages.
In India, it is seen that developers who are reaching the age of 40 are mainly retiring from the industry and the percentage of developers reaching this age is more.It can be predicted that there will be a huge vacancy in the seats and therefore there will be an opportunity for the students who are learning to code and to those who are primarily coding as a hobby to join the software industry.
The number of ‘IT persons’ is also more in India, therefore it can be concluded that these persons will help in the growth of IT Industry and thereby contributing to the technological growth of the country.
The last step for Data Analysis is Communicating Results/Data Storytelling. It’s about infusing your data and visuals with narrative and other story motifs, like analogy, so that it resonates with your audience more strongly than it would otherwise.And most importantly,you need good communication skills.
Conclusion
Given data set is quite large to analyse. Countries like United States, United Kingdom, India, Germany are the countries having the most developed software industry and it will continue to grow more as the need for developers, coders is also high. Many of the developers are retiring which means that there will be an opportunity for the upcoming coders and developers to join the industry. The craze for programming languages like ‘Python’ , ‘Java’ , ‘Ruby’ , ‘ C#’ is quite high which means that the software industries will continue working on these languages and this shows that the upcoming coders and developers must have the knowledge of these languages to establish themselves in the software industry. The trends of the database management systems include ‘Microsoft SQL Server’ , ‘SQLlite’ , ‘PostgreSQL’ which also gives an idea that the software industry will be emerging more on the basis of this databases. ‘Android’ , ‘iOS’ , ‘Windows’ , ‘Linux’ , ‘Docker’ , ‘MacOS’ will be the platforms on which the industry will continue to work.It is also seen that the use of social media is more between the age of 15–30. ‘Angular.js’ , ‘ASP.net’ , ‘jQuery’ are the web frame desires in the next years of the software industry.
Thus, it can be taken into account that the software industry will be emerging more and more in the upcoming years. The industry has been supporting more than 10 million jobs, and propelling the economy in more than 50 countries. India’s software development industry has an early start than most countries by capitalizing on her endless pool of young developers and software engineers.So, if you are willing to establish yourself in this industry, it is advised to learn the above mentioned languages and database systems. You must also have must have excellent listening and speaking skills, as well as critical thinking and teamwork. Good luck!
Thanks for reading:)
By,
Chandrima Sarkar.
