Data Science Methodology 101

Photo by Luca Bravo on Unsplash

Data Science Methodology 101

Business Understanding

Data science methodology begins with spending the time to seek clarification, to attain what can be referred to as a business understanding. Having this understanding is placed at the beginning of the methodology because getting clarity around the problem to be solved, allows you to determine which data will be used to answer the core question.

From the image, we can see business understanding is the first step on the roadmap of deploying the project

Establishing a clearly defined question starts with understanding the GOAL of the person who is asking the question.

Analytic Approach

Once the problem to be addressed is defined, the appropriate analytic approach for the problem is selected in the context of the business requirements. This is the second stage of the data science methodology

Pick Analytic approach depending on the type of question

DIAGNOSTIC

  • What happened?

  • Why is it happening?

PREDICTIVE

  • What will happen next?

  • What if this continues?

DESCRIPTIVE

  • Current state

Tree classification model was used to identify the combination of conditions leading to each patient's outcome. In this approach, examining the variables in each of the nodes along each path to a leaf led to a respective threshold value. This means the decision tree classifier provides both the predicted outcome, as well as the likelihood of that outcome, based on the proportion at the dominant outcome, yes or no, in each group.

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