What are two components of data discovery according to Dr. Brendeis Marshall?
A data systems and data platforms
B data applications and data tools
C data completeness and data accuracy
D data minimum and data maximum
The correct answer and explanation is:
The correct answer is C) data completeness and data accuracy.
Explanation:
Data discovery is the process of identifying and understanding the data that exists within an organization or system. Dr. Brendeis Marshall emphasizes the importance of two key components in this process: data completeness and data accuracy.
- Data Completeness: This refers to the extent to which all necessary data is present. Incomplete data can lead to inaccurate analysis and decision-making. Ensuring data completeness involves checking that all required fields, records, or datasets are accounted for, and no critical pieces of information are missing. It involves identifying gaps in the data and taking steps to fill them in.
- Data Accuracy: Accuracy refers to how correct the data is. Data accuracy ensures that the values in the dataset reflect reality and are free from errors. Inaccurate data can skew analysis and lead to misleading conclusions. Ensuring data accuracy involves checking for consistency, correcting errors, and verifying the integrity of the data, whether through automated checks or manual validation.
Together, these two components form the foundation for successful data discovery. A complete and accurate dataset is essential for effective analysis, decision-making, and strategy formulation. Without completeness, there is a risk of missing crucial information, while inaccuracies can distort insights derived from the data. Therefore, data completeness and accuracy are fundamental to ensuring that the data being discovered is reliable, actionable, and can be used for meaningful business or research outcomes.