Python Analytics is a great savior for a resistant Developer
In today’s world of Information Technology, even non-Developers need to program or write code at some point. Writing code has become inescapable for non-Developer folks working in IT. The problem with this is that one needs to be well-versed in programming languages like C/ C++. The most basic applications or tasks can be achieved only with long pieces of code. It also required time and proficiency in these programming languages.
However, Python has revolutionized the world of IT. Now it is no longer essential to know any programming language. Python scripts are written in language that is almost similar to English. Now anyone can code, should they need to. This reduces familiarization time with programming languages. Now the non-developers can focus on the task on hand rather than learning programming languages.
Fast and easy programming – As we saw, even non-developers can quickly develop code essential for their tasks
Automates many manual functions – Containerization and VMI have become essential in today’s age of BYOD workspaces. These technologies ensure that there is no theft or loss of Enterprise data. Python can help automate many processes part of Containerization and VMI. Network settings need to be monitored and changed as per evolving requirements. Python can help reduce the human time and effort required for these kinds of high level tasks.
Simplifies complex applications outside code development – Machine learning apps, scientific analysis, statistical analysis etc. are complex fields external to software development. Working with Python has helped simplify the complexity in these areas to some extent. There is potential for further simplification in the future as well.
Python’s slow execution, a big disadvantage
Though Python has overwhelmingly a large number of benefits and is a lifesaver for program development, it has a major disadvantage that hinders its universal adoption. Python, though easy and less time consuming to code in, takes a long time to run. It is much slower in execution than code written in C or C++ or Java. This is held against Python despite its ease and convenience of usage.
However, the evolution of Python has also brought a workaround to this problem. Third party libraries can be developed in faster execution languages similar to C or C++ and then linked to Python. This can speed up the run time of Python applications significantly almost to the level of the library language itself.
This workaround has made Python a convenient to code as well a high performing programming language. Python has a huge potential for deployment software development as well as complex application fields.
About the Author
DataFactZ is a professional services company that provides consulting and implementation expertise to solve the complex data issues facing many organizations in the modern business environment. As a highly specialized system and data integration company, we are uniquely focused on solving complex data issues in the data warehousing and business intelligence markets.