Will I have to learn & do a lot of coding in Supply Chain Mgmt? Answer: No, but…
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I would say very very little coding. Our Business Anaytics minor does require a Python class, but I would not call it a coding class, far from it.
This describes our Python class (CIS 2650): CIS 2650 is not just a “Python” class, but instead a Python class for analytics (big difference). In a traditional Python class, people teach Python straight for the whole semester with tons of syntax, data structure, software development, etc. That type of class is mostly designed for CIS/CS majors. What we do is different. It is Python in a popular analytics platform (more technically speaking, it is Python in Jupyter, which is an analytics platform that data science & business analytics programs do).
Can you imagine what an employer will think if they see Python in Jupyter on your resume? The reason for this design is the following: We studied the top skills in analytics jobs & Python was among the top skills. The visualization libraries in Python can produce the kind of visualizations not available in Tableau & Power BI. Students will be able to differentiate themselves from other schools. Tableau & Power BI recently added Python or Python+Jupyter because certain Python analytics & visualization are not available in Tableau & Power BI. Using them together makes it a powerful analytics solution (e.g., the ability to transform visualization into implementable actions). All data scientists stress the importance of Python in analytics programs.
Note, “data scientist” is one of the fastest growing career paths with escalating salaries because not enough people are good at this stuff. Python are “R” are both number one & two in analytics, but Python is easier to learn compared to R. Past experience in our SCM program shows that non-technical students (SCM, marketing, accounting, etc.) are able to handle the content that we designed. Python + Jupyter (or its variant) are used in Big Data (Hadoop, Microsoft Azure, Amazon AWS, etc.). It can also be used with/on SAP HANA, IoT, AI, Blockchain, & smart contracts to implement supply chain visibility, and other SC related solutions. Meeting the needs of today’s employers is important, but offering a program that does that plus something that can differentiate our students from other schools sounds even better. Compared to the analytics programs from the schools that we benchmarked, our students can do so much more.
Learn to manage large amounts of data rather than pure coding (e.g., big data/predictive analytics, database management, data mining/we use RapidMiner, project management, SQL, Python, PMO, Tableau, Power BI, etc.).
A while back, we made these points about CIS 2650 and the BA minor in general. Do these points still largely apply?…
- We studied the top skills in analytics jobs & Python was among the top skills.
- The visualization libraries in Python can produce the kind of visualizations not available in Tableau & Power BI. Students will be able to differentiate themselves from other schools.
- Tableau & Power BI recently added Python or Python+Jupyter because certain Python analytics & visualization are not available in Tableau and Power BI. Using them together makes it a powerful analytics solution (e.g., the ability to transform visualization into implementable actions).
- All data scientists stress the importance of Python in analytics programs. Note, “data scientist” is one of the fastest growing career paths with escalating salaries because not enough people are good at this stuff.
- Python are “R” are both number one & two in analytics, but Python is easier to learn compared to R.
- Past experience in our SCM program (3+ semesters of experience in CIS 2650) shows that non-technical students (SCM, marketing, accounting, etc.) are able to handle the content that we designed.
- Python + Jupyter (or its variant) are used in Big Data (Hadoop, Microsoft Azure, Amazon AWS, etc.). It can also be used with/on SAP HANA, IoT, AI, Blockchain, and smart contracts to implement supply chain visibility, and other SC related solutions, etc.
We believe the above points are still valid. Here are some evidences:
- We studied the top skills in analytics jobs & Python was among the top skills.
- Python is among the top skills for data analysts (Skill number 4 in the list): https://www.indeed.com/career-advice/resumes-cover-letters/skills-for-data-analyst
- https://www.coursera.org/articles/in-demand-data-analyst-skills-to-get-hired
- The visualization libraries in Python can produce the kind of visualizations not available in Tableau & Power BI. Students will be able to differentiate themselves from other schools.
- Python graphing libraries that help in creating live and highly customized plots. It is possible to use Python or R in Tableau and Power BI to develop advanced plots. To use Python and R in Tableau and Power BI, students should first learn Python syntax and libraries.
- Tableau & Power BI recently added Python or Python+Jupyter because certain Python analytics & visualization are not available in Tableau and Power BI. Using them together makes it a powerful analytics solution (e.g., the ability to transform visualization into implementable actions).
- Here are some examples:
- TabPy makes it possible to use Python scripts in Tableau calculated fields.: https://www.tableau.com/about/blog/2017/1/building-advanced-analytics-applications-tabpy-64916
- PyCaret makes it possible to use machine learning in Tableau: https://towardsdatascience.com/machine-learning-in-tableau-with-pycaret-166ffac9b22e
- Python can create machine learning modules and create the visualization based on the predicated result.
- All data scientists stress the importance of Python in analytics programs. Note, “data scientist” is one of the fastest growing career paths with escalating salaries because not enough people are good at this stuff.
- Python are “R” are both number one & two in analytics, but Python is easier to learn compared to R.
- I believe learning python is easier. Also, because python is a multi-purpose language compared to R, students could benefit more from learning Python.
- Past experience in our SCM program (3+ semesters of experience in CIS 2650) shows that non-technical students (SCM, marketing, accounting, etc.) are able to handle the content that we designed.
- I believe it’s still valid.
- Python + Jupyter (or its variant) are used in Big Data (Hadoop, Microsoft Azure, Amazon AWS, etc.). It can also be used with/on SAP HANA, IoT, AI, Blockchain, and smart contracts to implement supply chain visibility, and other SC related solutions, etc.
- It’s still completely valid. https://towardsdatascience.com/why-is-python-programming-a-perfect-fit-for-big-data-5ac54ee8f95e
To make sure students see Python’s benefits and applications, we added applications of Python in Tableau/Power BI to the course content and offer some examples.
How much Python do I need to know in order to excel in supply chain?
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I have had several people ask me about “Industry 4.0”.
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Do you know how to use Power BI or Tableau? Do not be a victim of technology.
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