Data requirements in the context of business analysis refer to the specific data elements and criteria needed to support various business processes and decision-making activities within an organization. These requirements are essential for understanding, analyzing, and improving business operations.

Key aspects of data requirements

1. Data Identification: Business analysts must identify the types of data required for a particular project or initiative. This involves determining what data is relevant, its source, format, and the frequency of data collection;
2. Data Sources: Analysts need to specify the sources of data, whether it's internal databases, external sources, user inputs, or a combination of these. Knowing the data sources helps ensure data accuracy and reliability;
3. Data Quality: Data quality requirements outline the level of accuracy, completeness, consistency, and reliability expected from the data. Poor data quality can lead to flawed analysis and decisions;
4. Data Volume: Analysts must define the volume of data required, including the size of datasets, the historical data needed, and any growth expectations over time;
5. Data Integration: In cases where data comes from multiple sources, requirements may include data integration specifications to ensure that data can be combined and analyzed effectively;
6. Data Security: Data security requirements address the protection of sensitive or confidential information, ensuring that data is stored, transmitted, and accessed securely;
7. Data Access: Analysts must determine who has access to the data, including user roles and permissions, to ensure that the right people can retrieve and use the required data.

Overall, data requirements play a fundamental role in business analysis, as they ensure that the right data is available in the right format and quality to support informed decision-making and business improvements.