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Data Science Methodology - From Problem to Approach and From Requirements to Collection (2) 본문

Coursera/IBM Data Science

Data Science Methodology - From Problem to Approach and From Requirements to Collection (2)

떼닝 2023. 12. 27. 07:43

Data Science Methodology

From Requirements to Collection

Data Requirements

From Requirements to Collection

- Data Requirements : What are data requirements?

- Data Collection : What occurs during data collection? 

 

Case Study : Selecting the cohort

Define and select cohort: (cohot : 집단)

- inpatient within health insurance provider's service area

- primary diagnosis of CHF (Congestive Heart Failure) in one year

- Continuous enrollment for at least 6 months prior to primary CHF admission

- Disqualifying conditions

 

Case Study : Defining the data

Contents, formats, representations suitable for decision tree classifier:

- one record per patient with columns representing variables (dependent variable and predictors)

- Content covering all aspects of each patient's clinical history (transactional format, transformations required)

 

Data Collection

Case Study : Gathering available data

Available data sources:

- corporate data warehouse (single source of medical & claims, eligibility, provider, and member information)

- inpatient record system

- claim payment system

- disease management program information

 

Case Study : Deferring inaccessible data

Data wanted but not available:

- pharmaceutical records

- decided to defer (defer : 미루다, 연기하다)

 

Case Study : Merging data

- eliminate redundant data

- can discuss various ways to better manage their data

 

Practice Quiz : From Requirements to Collection

Q. Select the statement that describes what happens during the Data Requirements stage

A. Data Scientists identify the necessary data content, formats, and sources for initial data collection

 

Q. Who determines how to collect and prepare the data?

A. Data Scientists

 

Q. Which of the following statements is correct?

A. Data scientists determine how to collect the data.

    Data scientists identify the data that is required for data modeling.

    Data scientists determine how to prepare the data.

 

 

 

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