Dependencies (Data Sources)

Business Requirements: The business requirements of an organization play a crucial role in identifying data sources. Understanding the specific data needs, such as the types of data required, the granularity of data, and the specific metrics or KPIs to be tracked, helps determine the relevant data sources. Aligning data sources with business requirements ensures that the data collected is relevant and supports the organization's objectives.

Data Use Cases: Data use cases refer to the specific purposes or applications for which data will be used within the organization. It is important to identify the use cases that require data, such as operational reporting, financial analysis, customer segmentation, or inventory management. Each use case may have specific data requirements, which guide the identification of relevant data sources.

Data Availability: Data availability is a crucial dependency when identifying data sources. It involves assessing the availability and accessibility of data from various systems, databases, or external sources. Consideration should be given to the data sources that can provide the required data in a timely manner. This may include evaluating the availability of data from internal systems, third-party vendors, APIs, or data feeds.

Data Quality: Data quality is an important consideration when identifying data sources. It is essential to assess the quality of data from potential sources to ensure that it meets the organization's standards. Data quality dependencies include factors such as data accuracy, completeness, consistency, and reliability. Data sources with high-quality data should be prioritized to ensure the integrity of the insights derived from the data.

Data Integration Feasibility: Data integration feasibility involves assessing the technical aspects of integrating data from different sources. It considers factors such as data formats, data structures, data governance, and compatibility with existing systems or platforms. Dependencies related to data integration feasibility help determine the feasibility of integrating data from various sources and the effort required for data integration.

Data Security and Privacy: Considerations of data security and privacy are crucial when identifying data sources. Organizations need to ensure that data sources comply with relevant data protection regulations and security standards. Dependencies related to data security and privacy involve assessing the data sources' security measures, data encryption, access controls, and data sharing agreements.