question archive Sam: Python and other open-source programming languages are better suited to the modern era of big data
Sam: Python and other open-source programming languages are better suited to the modern era of big data
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Sam:
Python and other open-source programming languages are better suited to the modern era of big data. Programming languages are superior to spreadsheet software when statistical analyses are necessary, often performing tests that cannot be accomplished with spreadsheets (Incerti et al., 2019, p. 576). Programming languages are better suited to operating in Bayesian frameworks, due to programming languages' use of attributes and classes. The languages also create programs that are reusable and adaptable (Incerti et al., 2019, p. 578). This allows for flexibility in the fluid world of technology and apps. Despite this short list of advantages, there are some disadvantages. One disadvantage is if an error is programmed into a function, it could be propagated (Incerti et al., 2019, p. 578). Another disadvantage is the difficulty of learning the languages.
Paula:
Healthcare generates a large amount of data within the electronic health care records and in a variety of formats. Open-source programming such as Python are able to analyze large amounts of data in a variety of formats in short period of time when compared to traditional programs such as Excel (Incertii, Thom, Baio, Jansen, 2019). The predictive analytics within Python mesh with healthcare needs for disease detection, treatment plans and possible influx of patients the hospital (Bo Tree Technologies, 2020). Python, like other open-source applications, has a multitude of different programs in the community and developers can collaborate with the users to make improvements on existing programs or build new applications according to user needs (Incerti et al, 2019). Security concerns are addressed by Python and is compliant with HIPPA regulations.
One of the disadvantages is the source of the code which can contain errors or bug within its program. Lack of experience and insufficient training with these types of computer languages in comparison to programs such as Excel, can hamper its implementation in the healthcare arena (Incerti et al, 2019).
Jason:
Open source programming is essentially free code that others can have access to use and modify. These are programs such as R or Python. For example, there are multiple free templates of code that can be utilized so a program does not have to be written from the bottom up (Salter, 2018). Open source programs are incredibly affordable because they are free to use. This makes them quite appealing to utilize when working with healthcare. There are multiple different programs that are open source but some are better than others. Looking at Python specifically, it is a programming language with dynamic building options that span across multiple platforms and applications. Python is a great candidate to work on electronic health records in the health care industry because it facilitates a secure exchange of information. It is also great at analyzing large amounts of information through its machine learning algorithms to obtain usable information (Kalinin, 2020). Open source is not free from any shortcoming though. Since multiple people will be working on the open source code, it can become difficult to locate changes that have been made. It can also become difficult to navigate issues in these languages as usually they do not have full time support as they are free services. Where as incensed languages do provide support for their product (Ratan, 2016). All in all, open source is a neat tool that can be customized to fit the personal needs of an organization with only a few down sides. It should be seriously considered when working with a large EHR to utilize open source.
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Sam
Great post Sam! It is indeed correct that programming languages are better suited to analyzing big data than software packages such as Microsoft excel (British Computer Society, 2014). This is because languages such as python are immensely flexible as noted in the post (Incerti et al., 2019). However, the disadvantages have not been given much discussion, and I would like to point out an additional one. For example, programming languages for analyzing big data may not be compatible, making research sharing between experts difficult. Even those that are compatible tend to be poorly optimized, hence they impose an extra burden on the researchers.
Paula
Hi Paula! Your post is great, and it covers both the advantages and disadvantages of the programming languages in their handling of big data (Incerti et al., 2019). However, one thing that it fails to do is to provide the possible mitigation to the disadvantages, which is an area I would add on. With regard to errors in the source code, programmers can conduct multiple automated, as well as, live user tests in order to help identify such errors before production. With regard to the steep learning curve, organizations should have a dedicated IT department to handle the use and integration of such software.
Jason
Great post Jason! I agree that open-source software is indeed useful in the health care industry (Incerti et al., 2019). The advantages and disadvantages that you present are also well done, providing additional depth to the post. However, one shortcoming that is not clearly spelled out is the deficiency in terms of lack of consistent updates. Open-source projects tend to suffer from delayed patches because they do not have the committed resources their proprietary ones often enjoy. Therefore, since no one is paid handsomely to constantly develop and update these pieces of code, they are often not at their optimum or at their level best compared to their counterparts financed by big corporations such as Microsoft or Oracle.
