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Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt
- Unified data modeling with dbt allows for end-to-end data lineage analysis with Amazon Athena, Amazon Redshift, and Amazon Neptune.
- Amazon Athena is suitable for one-time queries, Amazon Redshift for complex queries, and Amazon Neptune as a graph database for data lineage analysis.
- A carefully designed architecture and advanced technical solutions are required to merge the data lineage of one-time and complex queries.
- Amazon DataZone offers organization-wide data lineage visualization using AWS services, while dbt provides project-level lineage and supports cross-project integration.
- Integrating Amazon Neptune graph database to store and analyze complex lineage relationships, combined with AWS Step Functions and AWS Lambda functions, results in a fully automated data lineage generation process.
- The solution uses AWS serverless computing and managed services, including Step Functions, Lambda, and EventBridge, providing a highly flexible and scalable design.
- Unified data modeling method simplifies development processes, while end-to-end data lineage graph visualization and analysis helps decision-making and data governance.
- This comprehensive approach balances technical innovation, data governance, operational efficiency, and cost-effectiveness, thus supporting long-term business growth with the adaptability to meet evolving enterprise needs.
- Authors of the article are Nancy Wu, Xu Feng, and Xu Da.
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