Mastering the Data Science Workflow

The collection stage involves acquiring the necessary data in order to perform a meaningful analysis based upon accurate information.

Techniques

Data Requirements
Define which data is needed to properly approach the project (e.g. format, variables, time range, granularity)

Data Sources
Find reliable and relevant data sources (e.g. databases, APIs, files, sensor readings)

Pengesahan
Secure necessary permissions to access the data (e.g. email/password, OAuth, API key, robots.txt)

Collection
Acquire the data using appropriate methods (e.g. SQL queries, API calls, web scraping, manual data entry)

Data Management
Handle the data in accordance with best practices (e.g. data quality, data governance, data security)