CATEGORIES IN DATA SCIENCE

CATEGORIES IN DATA SCIENCE

1. DATA MANAGEMENT

   • Is the process of persisting and retrieving data.

2. DATA INTEGRATION AND TRANSFORMATION

   • Often referred to as Extract, Transform and Load (ETL). Is the process of retrieving data from remote data management systems.

3. DATA VISUALIZATION

   • Is the part of an initial data exploration process as well as being part of a deliverable.

4. MODEL BUILDING

   • Is the process of creating a ML o DL using an appropriate algorithm with a lot of data.

5. MODEL DEPLOYMENT

   • Makes such a ML or DL model available to third-party applications.

6. MODEL MONITORING AND ASSESSMENT

   • Ensures continues performing quality checks on the deployed. These checks are for accuracy, fairness and adversarial robustness.

7. CODE ASSET MANAGEMENT

   • Uses versioning and other collaborative features to facilitate teamwork.

8. DATA ASSET MANAGEMENT

   • Also supports replication, backups and access rights management.

9. DEVELOPMENT ENVIROMENT

   • IDEs. Are tools that help the data scientist to implement, execute, test and deploy their work.

10. EXECUTION ENVIRONMENTS

    • Are places where data preprocessing, model training and deployment take place.

11. FULLY INTEGRATED VISUAL TOOLS

    • Tools that cover all the previous tooling components either partially or completely.