Data Market Services (DMS) provides SMEs with training for the development of data management, analysis and visualisation skills. This service is an online course called Fundamentals of Data Science. The course is highly practical, where participants will handle data with a popular programming language. The chosen language is Python, for several reasons. It is versatile, flexible, powerful, easy to use, and open source.
Created in the early nineties, Python is a widely used object-oriented and general-purpose language that has experienced a steep growth in popularity since its inception, becoming one of the most popular languages worldwide.
Python is versatile
The ability to adapt to a wide range of formats and frameworks is a crucial factor for the success of data driven SMEs. Python can be the answer to many of the challenges faced by small teams of developers who need to perform a wide range of tasks. Python can be used to develop websites, to work against SQL databases, to scrape data from websites, to perform complex statistical analyses, to design and train Machine Learning models, to visualise data, to build dashboards, to develop Artificial Intelligence applications, only to name a few of its functions. The main advantage Python performs very well in all these tasks, compared to other specialised languages.
Python is concise
Python requires less lines of code (LOCs) than other languages to perform the same tasks. That does not mean that Python is the most concise language for everything. For example, a study comparing code length for different data analysis tasks found that R (another popular language for statistics and data analysis) requires about half of the LOCs used in Python for equivalent large tasks. However, programs in Python are generally thought to be relatively short, requiring fewer resources to produce and debug, and therefore more cost-effective for small companies.
Python is easy to use
In commercial settings, a balanced combination of domain expertise and coding skills are essential for data-driven projects. More and more subject experts who aim to handle data find that they need to code to keep up with the demands of technological progress and innovation. Not all these subject experts are expert coders. Python is one of the best choices in that respect. Its syntax is simple, and its code is fairly human readable. This is the reason why many scientists decide to learn python to analyse their data, and so do domain experts in the industry. If you have never coded before, or you haven’t been coding for a while, perhaps Python is your best option to get started.
Python is Open Source
Python and its most commonly used libraries are free to use. This is a particularly interesting feature for companies in their early stages, where fundings have to be wisely spent. Python’s open source nature allows for experimentation with its libraries at no cost, which can be helpful for exploration and experimentation.
Python is popular
Another advantage is that Python, being open source, has a very large user community. IEEE Ranking situates Python as the top programming language in 2018. This popularity is advantageous for many reasons. Its number of libraries grows very quickly, offering ready made functions for all sorts of tasks. The forums about Python are lively and abundant, offering quick and precise answers to virtually every question you may have.
It should be clear that Python is not the perfect language for everything. For example, Python is not thought to be a good language for mobile apps development. It neither has the fastest runtime. However, the combination of features named above (versatility, conciseness, ease of use, open source, popularity) make it a very appropriate choice of a language to be used in SMEs.