Python can be a useful tool throughout an organisation, not only for those with a technical background, but also for individuals with an interest in business analysis.
Speaking with Altenar’s Director of Technology Operations, Konrad Pizzuto, he highlighted the benefits of Python for non-technical people within the gaming industry, suggesting that with the availability and accessibility of a powerful array of tools such as Jupyter Notebooks and the Pandas Library the learning curve for people interested in using it to test business ideas or prove concepts was not very large .
With this in mind, it was useful to take time with Konrad to discuss the benefits of the highly accessible Python language to gain greater insights into its use for those with a non-technical background.
Konrad explained, “The first thing to understand is that Python is a high-level, general-purpose programming language. It’s designed to be as understandable by humans as possible and it does a lot to shield you fr om the properties of the underlying machine.”
Noting that, at the core of Python programming was the need to make it accessible; Konrad continued, “this level of abstraction lets you concentrate on your problem instead.”
It’s this accessibility that appears to have grown the language’s user base, wh ere subsequently, ‘libraries and tools have mushroomed; making it easier for people to do mathematical analysis with Python’.
Two of the more well-known tools are Jupyter Notebook and Pandas Library, which are cross-sector must-haves …
In asking what a Jupyter Notebook is capable of, Konrad had the following to say, ‘A notebook integrates code (Python code for example), narrative text and rich media which makes it very easy to explain a business concept you may be trying to model as well as display example analysis and render graphs in response and in real time all in one place.”
Noting that, “with a reasonably small learning curve, people can improve certain gut-feel decisions by basing them on data instead, and this could be particularly useful for product feature decision-making, marketing decisions or customer value estimation.”
Additionally, it seemed prudent to discuss Pandas Library for Python. Konrad explained, “ Pandas allows data to be represented in a DataFrame - which is conceptually the same as looking at row/column data in a spreadsheet.”
Konrad continued, “Once data is loaded into a DataFrame, the barrier to do mathematical analysis or experimentation programmatically is much reduced and once you combine that with Jupyter notebook you have a powerful way to express fairly complex business concepts and make data-driven decisions about them.”
How Python Plays A Role Across Altenar | The Language Built For Variety
At Altenar, there are varying degrees of usage and knowledge around Python, ‘from system administration to mathematical modelling to data analysis prototyping to actual stream processing in parallel computation to adhoc bespoke reporting from manual data exports.’
With a continuously growing interest in Python, especially within Altenar, it’s clear that the language provides a point of access into coding and reference for striving for new resources.
Altenar promotes and helps those within the organisation to gain the knowledge and working understanding of Python.
- Easy to debug
- Can be used in an interpreted version (run command by command)
- Seen its usage in tech/non-tech teams
- Very useful skill to have
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