Why Data Science needs Subject Matter Experts

In data science, labels and names are important in coding. When describing the task and solution, diagrams, or text need to use a method to make sense. The terms in data science are specific to the sector of the desired solution. Two largest sectors for data science, finance, and healthcare. The popular terms, FinTech and HealthTech, describe the core technology piece of the finance and healthcare sectors

Term: a word or expression that has an exact meaning in some uses or is limited to a subject or field legal

Label: a word or phrase that describes or names something or someone a part-of-speech label

Data: facts and statistics collected together for reference or analysis

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FinTech

The finance sector has many divisions, but the terms, labels, and data use specific words that key into the content. Variable is a value that can change per instance or row in a set of data. The study and analysis of how, why there is change are found through analysis. There are different forms of analysis. Descriptive Analysis transforms the values into a table of present findings. What is the data now? What relationships can be found?

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HealthTech

The healthcare sector is known for having specific terms, or terminology. Terminology is using specific words that key to content and meaning. The feature is a value that can change per instance or row in a set of data. The study and analysis of how, why there is change are found through analysis. There are different forms of analysis. Diagnostic Analysis transforms the values into a table of current findings. This produces a listing of data relationships reflecting “now”.

Finance or Healthcare?

An analytics solution for these sectors can be mathematically and logically identical. However, the coding and description will be different to reflect the specific audience that uses the solution. These differences reflect the knowledge of the scientist to produce quality results that are usable and meaningful. Labels are important. An example is variable and feature, which both define values in a dataset. In analytics, the specific terms relating to data for communication and delivery of results yielding real solutions to achieve and maintain goals.


Originally written by Sarah Mason and Published 11/1/2020 in Codex

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