Data lineage is a discipline that traces the origin, transformations, and movement of data as it flows through an organization’s systems and applications. Here are some high-level topics that relate to data lineage:
- Data governance: The management of data as a valuable business asset, including the definition of data policies, standards, and processes.
- Data provenance: The history and context of data, including the source, ownership, and history of changes.
- Data quality: The accuracy, completeness, and consistency of data, and the measures taken to maintain and improve data quality over time.
- Data security: The protection of sensitive data from unauthorized access, theft, or misuse, and the measures taken to maintain the confidentiality, integrity, and availability of data.
- Data privacy: The protection of personal data and the adherence to data privacy regulations, such as GDPR and CCPA.
- Data lineage visualization: The visual representation of the flow and transformations of data, including the relationships between data elements, the source of data, and the history of changes.
- Data management: The processes and technologies for acquiring, storing, and utilizing data, including data warehousing, data integration, and master data management.
- Data analytics: The use of data and statistical methods to extract insights and make informed decisions, including data mining, predictive analytics, and big data analytics.