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	<title>Nancy Wu &#8211; Noise</title>
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		<title>Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt</title>
		<link>https://noise.getoto.net/2024/12/12/building-end-to-end-data-lineage-for-one-time-and-complex-queries-using-amazon-athena-amazon-redshift-amazon-neptune-and-dbt/</link>
		
		<dc:creator><![CDATA[Nancy Wu]]></dc:creator>
		<pubDate>Thu, 12 Dec 2024 17:17:33 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon Neptune]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon S3]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. dbt on Athena supports real-time queries, while dbt on Amazon Redshift handles complex queries, unifying the development language and significantly reducing the technical learning curve. Using a single dbt modeling language not only simplifies the development process but also automatically generates consistent data lineage information. This approach offers robust adaptability, easily accommodating changes in data structures.]]></description>
		
		
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