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Midterm Exam Instructions

Description: Applying the CRoss Industry Standard Process for Data Mining (CRISP-DM) framework

CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model that serves as the base for a data science process. It has six sequential phases: Business understanding – What does the business need? Data understanding – What data do we have / need? Is it clean? Data preparation – How do we organize the data for modeling? Modeling – What modeling techniques should we apply? Evaluation – Which model best meets the business objectives? Deployment – How do stakeholders access the results?

Review the following case studies found here:

https://www.knowledgehut.com/blog/data-science/top-data-science-case-studies

Choose one of the industries and create an APA formatted white paper by following these steps:

Step 1. [ BUSINESS UNDERSTANDING] Provide additional research and thoroughly outline the problem faced by the industry chosen. ( 1-page minimum)

Step 2. [ DATA DISCOVERY/UNDERSTANDING] Locate data (e.g., Kaggle.com or similar) relevant to your chosen industry and produce a model (Use one of the tools RStudio, Python, Jupyter, RapidMiner, or Tableau) that you propose will help resolve the issues you discovered in your research and readings. ( Minimum 1 graphic that adequately depicts your model)

Step 3. [ POSTURING STATEMENT] Articulate what your proposed model is postured to accomplish. ( 1-page minimum)

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