After reviewing the dataset and its accompanying DataCard documentation, several potential issues have been identified:

### Issue 1:
- **Issue**: Inconsistent naming convention between DataCard and dataset
- **Evidence**: "salaryinusd: The salary in USD" in the DataCard vs "salary_in_usd" in the dataset.
- **Description**: The naming convention for column headers as outlined in the DataCard does not match with the actual dataset's column name. Particularly, 'salaryinusd' as described in the DataCard does not include an underscore, unlike in the dataset ('salary_in_usd'). This inconsistency could lead to confusion or errors when using automated scripts or tools that rely on column names to process the dataset.

### Issue 2:
- **Issue**: Misleading column description for “company_size”
- **Evidence**: "company_size: The median number of people that worked for the company during the year"
- **Description**: The description in the DataCard suggests that the company_size column should contain numerical values indicating the median number of employees. However, the dataset seems to classify companies into categories (e.g., 'L', 'S', 'M') rather than providing a numerical median value. This discrepancy between expectation and actual data format could affect the analysis, especially if numerical operations were planned based on this column.

To resolve these issues, it is recommended that:
- The dataset's column names be reviewed and corrected to match the descriptions provided in the DataCard accurately.
- The description of the "company_size" column in the DataCard should either be revised to accurately reflect the categorical nature of the data it contains or consider adjusting the dataset to align with the initial description, depending on the intended use and analysis requirements.