Google Data Analytics Professional Certification Practice Test

What does 'data capturing' involve in the data life cycle?

1. Analyzing existing datasets

2. Gathering and recording data

3. Sharing insights with stakeholders

4. Archiving old data for future reference

The correct answer is: Gathering and recording data

Data capturing plays a crucial role in the data life cycle as it refers specifically to the process of gathering and recording data from various sources. This step lays the foundation for all subsequent analyses, insights, and decisions based on data. Effective data capturing ensures that the information collected is accurate, relevant, and timely, which is essential for creating high-quality datasets that can be analyzed later. During data capturing, techniques and tools are employed to obtain data, whether it’s through surveys, sensors, web scraping, or other methods. This stage is critical as the quality and reliability of the data collected directly influence the outcomes of any analytical processes that follow. The other options address different stages of the data life cycle. Analyzing existing datasets pertains to examining data that has already been collected, sharing insights with stakeholders relates to the communication of findings post-analysis, and archiving involves storing data for future use. Each of these processes is important but occurs after data capturing has taken place, emphasizing why gathering and recording data is the correct focus in this context.