<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0" xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" xmlns:psc="http://podlove.org/simple-chapters" xmlns:podcast="https://podcastindex.org/namespace/1.0"><channel><title><![CDATA[Data for AI]]></title><description><![CDATA[<p>Data for AI is the podcast from the Data for AI community: practitioners building the data layer AI runs on, from open lakehouses and catalogs to vectors, graphs, and multimodal data.</p><p>Long-form conversations with the people building this stuff, podcast-only, plus selected meetup talks on semantic layers, metadata and catalogs, Apache Iceberg, knowledge graphs, vector search, RAG, streaming, and agents.</p><p>Produced by Datastrato, the original creator of Apache Gravitino. Sponsored by Neo4j.</p><p>YouTube: youtube.com/@data-for-ai</p><p>Discord: datastrato.ai/discord</p><p>Meetup: lu.ma/dataforai</p>]]></description><link>https://riverside.com</link><generator>Riverside.fm (https://riverside.com)</generator><lastBuildDate>Mon, 26 Oct 2026 22:38:31 GMT</lastBuildDate><atom:link href="https://api.riverside.com/hosting/SYiOPwJk.rss" rel="self" type="application/rss+xml"/><author><![CDATA[Adi Wabisabi]]></author><pubDate>Fri, 25 Sep 2026 18:14:46 GMT</pubDate><copyright><![CDATA[2026 Adi Wabisabi]]></copyright><language><![CDATA[en]]></language><ttl>60</ttl><category><![CDATA[Entrepreneurship]]></category><category><![CDATA[Technology]]></category><itunes:author>Adi Wabisabi</itunes:author><itunes:summary>&lt;p&gt;Data for AI is the podcast from the Data for AI community: practitioners building the data layer AI runs on, from open lakehouses and catalogs to vectors, graphs, and multimodal data.&lt;/p&gt;&lt;p&gt;Long-form conversations with the people building this stuff, podcast-only, plus selected meetup talks on semantic layers, metadata and catalogs, Apache Iceberg, knowledge graphs, vector search, RAG, streaming, and agents.&lt;/p&gt;&lt;p&gt;Produced by Datastrato, the original creator of Apache Gravitino. Sponsored by Neo4j.&lt;/p&gt;&lt;p&gt;YouTube: youtube.com/@data-for-ai&lt;/p&gt;&lt;p&gt;Discord: datastrato.ai/discord&lt;/p&gt;&lt;p&gt;Meetup: lu.ma/dataforai&lt;/p&gt;</itunes:summary><itunes:type>episodic</itunes:type><itunes:owner><itunes:name>Adi Wabisabi</itunes:name><itunes:email>adi@datastrato.com</itunes:email></itunes:owner><itunes:explicit>no</itunes:explicit><itunes:category text="Business"><itunes:category text="Entrepreneurship"/></itunes:category><itunes:category text="Technology"/><itunes:image href="https://hosting-media.riverside.com/media/podcasts/e7b3fbde-3f1c-4e71-8db0-b0f88ed055c2/logos/15709e5a-0bbc-4763-b94e-ef398db21bcc.png"/><item><title><![CDATA[Scott Haines (Part 2): Catalogs, 450 shades of red, and why governance has to be open]]></title><description><![CDATA[<p>Nike had 450 different reds. University Red, Jordan Red, and 448 more. Query for "red shoes" and you either hit a graph database of colors first or you scan every string value in the column. Scott Haines spent years inside that problem, and it is why he cares about catalogs, tags, and semantics more than most people who talk about them.</p><p><br /></p><p>Part 2 picks up where Part 1 left off. Scott is in developer relations at Databricks, working on Delta Lake, Iceberg, and Unity Catalog, and nine months into Rust. He is the author of Modern Data Engineering with Apache Spark and a co-author of Delta Lake: The Definitive Guide.</p><p><br /></p><p>We talk about what a catalog actually is (where data lives and who owns it, which matters more once everybody's agents are querying too), where semantics go when "revenue" means three things in one company, metric views landing in Spark 4.2 and Unity Catalog 0.6, and which layers of the stack have to stay open: catalogs, table formats, and increasingly governance itself. Then the part Scott is most blunt about: the notebook that ends in DROP TABLE, the HDFS cluster at Twilio with no undo, dry-run-by-default as a design rule, the 60-page governance doc nobody read at Nike, and why he reached for the Cedar policy language there and is working with it again now. It ends on the open question: when an agent is a proxy for a lot of processes, whose permissions does it inherit?</p><p><br /></p><p>Chapters</p><p><br /></p><p>00:00 What Scott is working on now: Spark, Iceberg, Delta, DataFusion, Rust</p><p>00:54 Nine months into Rust, and hiring "a good engineer"</p><p>02:21 Software primitives are finally commodities</p><p>03:34 What a catalog is: tribal knowledge before, discovery and ownership after</p><p>05:08 Everybody's agents: certified data and the source of truth</p><p>06:23 From infrastructure abstractions to semantics</p><p>07:00 450 reds at Nike: ontologies, a graph of colors, tags vs scanning columns</p><p>09:00 Metric views in Spark 4.2, and SQL snippets passed around in Slack</p><p>10:37 Unity Catalog 0.6 metric views and governance dictionaries</p><p>12:56 Trust but verify, minus the verify</p><p>13:10 What has to be open: catalogs, Iceberg REST, table formats, compute</p><p>14:32 Apache Gravitino and the lock-in problem</p><p>14:44 Open governance: exchanging policies, tags, and column masks</p><p>16:16 Why governance: the notebook that drops a table in prod</p><p>17:04 HDFS with no undo, and dry run as the default</p><p>19:00 Service principals, Vault, and config-based production at Nike</p><p>20:00 Sixty pages nobody reads, and the Cedar policy language</p><p>21:00 Agents as proxies: whose permissions do they inherit?</p><p><br /></p><p>Part 1: <a href="https://youtu.be/4nWeC_NEYmw" rel="noopener noreferrer nofollow">https://youtu.be/4nWeC_NEYmw</a></p><p><br /></p><p>Scott on LinkedIn: <a href="https://www.linkedin.com/in/scotthaines/" rel="noopener noreferrer nofollow">https://www.linkedin.com/in/scotthaines/</a></p><p>Delta Lake: The Definitive Guide: <a href="https://www.oreilly.com/library/view/delta-lake-the/9781098151935/" rel="noopener noreferrer nofollow">https://www.oreilly.com/library/view/delta-lake-the/9781098151935/</a></p><p>Modern Data Engineering with Apache Spark: <a href="https://link.springer.com/book/10.1007/978-1-4842-7452-1" rel="noopener noreferrer nofollow">https://link.springer.com/book/10.1007/978-1-4842-7452-1</a></p><p><br /></p><p>Data for AI is produced by Datastrato, the original creator of Apache Gravitino. Sponsored by Neo4j.</p><p>Join the community: <a href="https://datastrato.ai/discord" rel="noopener noreferrer nofollow">https://datastrato.ai/discord</a></p><p>Next meetup: <a href="https://lu.ma/dataforai" rel="noopener noreferrer nofollow">https://lu.ma/dataforai</a></p><p>Watch on YouTube: <a href="https://www.youtube.com/@data-for-ai" rel="noopener noreferrer nofollow">https://www.youtube.com/@data-for-ai</a></p>]]></description><guid isPermaLink="false">fa77577a-b33a-4d38-9682-32492b4da2a8</guid><dc:creator><![CDATA[Adi Wabisabi]]></dc:creator><pubDate>Sun, 04 Oct 2026 23:01:52 GMT</pubDate><enclosure url="https://api.riverside.com/hosting-analytics/media/cfe5cefd24941b97f56f758c719b34cc91a0325ff33f9c5081b188594f056df9/eyJlcGlzb2RlSWQiOiJmYTc3NTc3YS1iMzNhLTRkMzgtOTY4Mi0zMjQ5MmI0ZGEyYTgiLCJwb2RjYXN0SWQiOiJlN2IzZmJkZS0zZjFjLTRlNzEtOGRiMC1iMGY4OGVkMDU1YzIiLCJhY2NvdW50SWQiOiI2OWUwNGVjYmJjYmExZjdjNDI3MWEwYTQiLCJwYXRoIjoibWVkaWEvY2xpcHMvNmFjMmQ3MzExYjk2MTlhMzNhNWI3Zjg0L2RhdGFzdHJhdG8tMjAyNi0xMC00X18yMy0xLTUzLm1wMyJ9.mp3" length="42617774" type="audio/mpeg"/><podcast:transcript url="https://hosting-media.riverside.com/media/podcasts/e7b3fbde-3f1c-4e71-8db0-b0f88ed055c2/episodes/fa77577a-b33a-4d38-9682-32492b4da2a8/transcripts.txt" type="text/plain"/><itunes:summary>&lt;p&gt;Nike had 450 different reds. University Red, Jordan Red, and 448 more. Query for &quot;red shoes&quot; and you either hit a graph database of colors first or you scan every string value in the column. Scott Haines spent years inside that problem, and it is why he cares about catalogs, tags, and semantics more than most people who talk about them.&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Part 2 picks up where Part 1 left off. Scott is in developer relations at Databricks, working on Delta Lake, Iceberg, and Unity Catalog, and nine months into Rust. He is the author of Modern Data Engineering with Apache Spark and a co-author of Delta Lake: The Definitive Guide.&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;We talk about what a catalog actually is (where data lives and who owns it, which matters more once everybody&apos;s agents are querying too), where semantics go when &quot;revenue&quot; means three things in one company, metric views landing in Spark 4.2 and Unity Catalog 0.6, and which layers of the stack have to stay open: catalogs, table formats, and increasingly governance itself. Then the part Scott is most blunt about: the notebook that ends in DROP TABLE, the HDFS cluster at Twilio with no undo, dry-run-by-default as a design rule, the 60-page governance doc nobody read at Nike, and why he reached for the Cedar policy language there and is working with it again now. It ends on the open question: when an agent is a proxy for a lot of processes, whose permissions does it inherit?&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Chapters&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;00:00 What Scott is working on now: Spark, Iceberg, Delta, DataFusion, Rust&lt;/p&gt;&lt;p&gt;00:54 Nine months into Rust, and hiring &quot;a good engineer&quot;&lt;/p&gt;&lt;p&gt;02:21 Software primitives are finally commodities&lt;/p&gt;&lt;p&gt;03:34 What a catalog is: tribal knowledge before, discovery and ownership after&lt;/p&gt;&lt;p&gt;05:08 Everybody&apos;s agents: certified data and the source of truth&lt;/p&gt;&lt;p&gt;06:23 From infrastructure abstractions to semantics&lt;/p&gt;&lt;p&gt;07:00 450 reds at Nike: ontologies, a graph of colors, tags vs scanning columns&lt;/p&gt;&lt;p&gt;09:00 Metric views in Spark 4.2, and SQL snippets passed around in Slack&lt;/p&gt;&lt;p&gt;10:37 Unity Catalog 0.6 metric views and governance dictionaries&lt;/p&gt;&lt;p&gt;12:56 Trust but verify, minus the verify&lt;/p&gt;&lt;p&gt;13:10 What has to be open: catalogs, Iceberg REST, table formats, compute&lt;/p&gt;&lt;p&gt;14:32 Apache Gravitino and the lock-in problem&lt;/p&gt;&lt;p&gt;14:44 Open governance: exchanging policies, tags, and column masks&lt;/p&gt;&lt;p&gt;16:16 Why governance: the notebook that drops a table in prod&lt;/p&gt;&lt;p&gt;17:04 HDFS with no undo, and dry run as the default&lt;/p&gt;&lt;p&gt;19:00 Service principals, Vault, and config-based production at Nike&lt;/p&gt;&lt;p&gt;20:00 Sixty pages nobody reads, and the Cedar policy language&lt;/p&gt;&lt;p&gt;21:00 Agents as proxies: whose permissions do they inherit?&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Part 1: &lt;a href=&quot;https://youtu.be/4nWeC_NEYmw&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://youtu.be/4nWeC_NEYmw&lt;/a&gt;&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Scott on LinkedIn: &lt;a href=&quot;https://www.linkedin.com/in/scotthaines/&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://www.linkedin.com/in/scotthaines/&lt;/a&gt;&lt;/p&gt;&lt;p&gt;Delta Lake: The Definitive Guide: &lt;a href=&quot;https://www.oreilly.com/library/view/delta-lake-the/9781098151935/&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://www.oreilly.com/library/view/delta-lake-the/9781098151935/&lt;/a&gt;&lt;/p&gt;&lt;p&gt;Modern Data Engineering with Apache Spark: &lt;a href=&quot;https://link.springer.com/book/10.1007/978-1-4842-7452-1&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://link.springer.com/book/10.1007/978-1-4842-7452-1&lt;/a&gt;&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Data for AI is produced by Datastrato, the original creator of Apache Gravitino. Sponsored by Neo4j.&lt;/p&gt;&lt;p&gt;Join the community: &lt;a href=&quot;https://datastrato.ai/discord&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://datastrato.ai/discord&lt;/a&gt;&lt;/p&gt;&lt;p&gt;Next meetup: &lt;a href=&quot;https://lu.ma/dataforai&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://lu.ma/dataforai&lt;/a&gt;&lt;/p&gt;&lt;p&gt;Watch on YouTube: &lt;a href=&quot;https://www.youtube.com/@data-for-ai&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://www.youtube.com/@data-for-ai&lt;/a&gt;&lt;/p&gt;</itunes:summary><itunes:explicit>no</itunes:explicit><itunes:duration>00:22:12</itunes:duration><itunes:image href="https://hosting-media.riverside.com/media/podcasts/e7b3fbde-3f1c-4e71-8db0-b0f88ed055c2/logos/15709e5a-0bbc-4763-b94e-ef398db21bcc.png"/><itunes:episode>1</itunes:episode><itunes:title>Scott Haines (Part 2): Catalogs, 450 shades of red, and why governance has to be open</itunes:title><itunes:episodeType>full</itunes:episodeType></item><item><title><![CDATA[Scott Haines (Part 1): Storm, Spark, Delta Lake, and why he still writes code by hand]]></title><description><![CDATA[<p>Scott Haines spent 25 years building real-time systems at Yahoo, Twilio, and Nike. Seven months ago he stopped, and started teaching instead. This is a conversation about what that trade costs.</p><p><br /></p><p>Scott is now in developer relations at Databricks, working on Delta Lake, Iceberg, and Unity Catalog. He is the author of Modern Data Engineering with Apache Spark and a co-author of Delta Lake: The Definitive Guide. Before that he was the engineer on the pager: Apache Storm at Yahoo handling 46 million events a second in 2014, then the first streaming team at Twilio on Spark 1.6.</p><p><br /></p><p>We talk about the parts of the transition nobody puts in the job description: measuring your own work when nothing merges, imposter syndrome in a front-facing role, and what it means to build community when the community is increasingly prompting its way through problems. Scott is blunt about the AI part. He spent last winter prompting his way through everything, ended up with what he calls a mountain of dead projects, and found he had to relearn how to start an application from scratch. His answer is to spend deliberate time with no AI at all, and to keep writing books and code by hand, not because he has to, but because the flow state is where the understanding lives.</p><p><br /></p><p>Then the origin story: Hacker Dojo in Mountain View, teaching PHP and Rails as a sole proprietor, pizza at the Hadoop users group at Yahoo, why Storm felt like caffeine, and why Spark at Twilio "was like crack."</p><p><br /></p><p>Chapters</p><p>00:00 Welcome</p><p>00:32 Seven months into DevRel: how do you know if you're doing it well?</p><p>01:30 Graphic design, Hacker Dojo, and teaching before the pager</p><p>03:27 Building a reputation twice</p><p>05:30 Imposter syndrome when you're no longer on call</p><p>06:56 Advice for anyone whose job AI is doing now</p><p>09:01 Time without AI, and the mountain of dead projects</p><p>11:18 Who are you writing for? Books, blogs, and the AI slop sniff test</p><p>15:26 Flow state as the place deep work happens</p><p>17:08 Delta Lake: The Definitive Guide, and making Parquet not suck at Twilio</p><p>19:45 Yahoo Games, the Hadoop users group, and discovering analytics</p><p>21:25 Apache Storm: 46 million events a second</p><p>22:00 Twilio, Spark 1.6, and three months to build a streaming team</p><p>23:37 Why streaming was addictive: Redis, sessionization, and replaying real time</p><p><br /></p><p>Scott on LinkedIn: <a href="https://www.linkedin.com/in/scotthaines/" rel="noopener noreferrer nofollow">https://www.linkedin.com/in/scotthaines/</a></p><p>Delta Lake: The Definitive Guide (O'Reilly)</p><p>Modern Data Engineering with Apache Spark (Apress)</p><p><br /></p><p>Data for AI is produced by Datastrato, the original creator of Apache Gravitino. Sponsored by Neo4j.</p><p>Join the community: <a href="https://datastrato.ai/discord" rel="noopener noreferrer nofollow">https://datastrato.ai/discord</a></p><p>Next meetup: <a href="https://lu.ma/dataforai" rel="noopener noreferrer nofollow">https://lu.ma/dataforai</a></p><p>Watch on YouTube: <a href="https://youtube.com/@data-for-ai" rel="noopener noreferrer nofollow">https://youtube.com/@data-for-ai</a></p>]]></description><guid isPermaLink="false">bbb23095-80af-4d4a-93da-24522cdfea8d</guid><dc:creator><![CDATA[Adi Wabisabi]]></dc:creator><pubDate>Fri, 25 Sep 2026 18:18:48 GMT</pubDate><enclosure url="https://api.riverside.com/hosting-analytics/media/391f5021707f2f02b87829f8570fe024aeb442e31fe12140b4dda4b3c2d69171/eyJlcGlzb2RlSWQiOiJiYmIyMzA5NS04MGFmLTRkNGEtOTNkYS0yNDUyMmNkZmVhOGQiLCJwb2RjYXN0SWQiOiJlN2IzZmJkZS0zZjFjLTRlNzEtOGRiMC1iMGY4OGVkMDU1YzIiLCJhY2NvdW50SWQiOiI2OWUwNGVjYmJjYmExZjdjNDI3MWEwYTQiLCJwYXRoIjoibWVkaWEvY2xpcHMvNmFhODEzZDk0NjQ3NTljMDk1M2Y4YTQ0L2RhdGFzdHJhdG8tMjAyNi05LTI1X18xOC0xOC01Mi5tcDMifQ==.mp3" length="51517797" type="audio/mpeg"/><podcast:transcript url="https://hosting-media.riverside.com/media/podcasts/e7b3fbde-3f1c-4e71-8db0-b0f88ed055c2/episodes/bbb23095-80af-4d4a-93da-24522cdfea8d/transcripts.txt" type="text/plain"/><itunes:summary>&lt;p&gt;Scott Haines spent 25 years building real-time systems at Yahoo, Twilio, and Nike. Seven months ago he stopped, and started teaching instead. This is a conversation about what that trade costs.&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Scott is now in developer relations at Databricks, working on Delta Lake, Iceberg, and Unity Catalog. He is the author of Modern Data Engineering with Apache Spark and a co-author of Delta Lake: The Definitive Guide. Before that he was the engineer on the pager: Apache Storm at Yahoo handling 46 million events a second in 2014, then the first streaming team at Twilio on Spark 1.6.&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;We talk about the parts of the transition nobody puts in the job description: measuring your own work when nothing merges, imposter syndrome in a front-facing role, and what it means to build community when the community is increasingly prompting its way through problems. Scott is blunt about the AI part. He spent last winter prompting his way through everything, ended up with what he calls a mountain of dead projects, and found he had to relearn how to start an application from scratch. His answer is to spend deliberate time with no AI at all, and to keep writing books and code by hand, not because he has to, but because the flow state is where the understanding lives.&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Then the origin story: Hacker Dojo in Mountain View, teaching PHP and Rails as a sole proprietor, pizza at the Hadoop users group at Yahoo, why Storm felt like caffeine, and why Spark at Twilio &quot;was like crack.&quot;&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Chapters&lt;/p&gt;&lt;p&gt;00:00 Welcome&lt;/p&gt;&lt;p&gt;00:32 Seven months into DevRel: how do you know if you&apos;re doing it well?&lt;/p&gt;&lt;p&gt;01:30 Graphic design, Hacker Dojo, and teaching before the pager&lt;/p&gt;&lt;p&gt;03:27 Building a reputation twice&lt;/p&gt;&lt;p&gt;05:30 Imposter syndrome when you&apos;re no longer on call&lt;/p&gt;&lt;p&gt;06:56 Advice for anyone whose job AI is doing now&lt;/p&gt;&lt;p&gt;09:01 Time without AI, and the mountain of dead projects&lt;/p&gt;&lt;p&gt;11:18 Who are you writing for? Books, blogs, and the AI slop sniff test&lt;/p&gt;&lt;p&gt;15:26 Flow state as the place deep work happens&lt;/p&gt;&lt;p&gt;17:08 Delta Lake: The Definitive Guide, and making Parquet not suck at Twilio&lt;/p&gt;&lt;p&gt;19:45 Yahoo Games, the Hadoop users group, and discovering analytics&lt;/p&gt;&lt;p&gt;21:25 Apache Storm: 46 million events a second&lt;/p&gt;&lt;p&gt;22:00 Twilio, Spark 1.6, and three months to build a streaming team&lt;/p&gt;&lt;p&gt;23:37 Why streaming was addictive: Redis, sessionization, and replaying real time&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Scott on LinkedIn: &lt;a href=&quot;https://www.linkedin.com/in/scotthaines/&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://www.linkedin.com/in/scotthaines/&lt;/a&gt;&lt;/p&gt;&lt;p&gt;Delta Lake: The Definitive Guide (O&apos;Reilly)&lt;/p&gt;&lt;p&gt;Modern Data Engineering with Apache Spark (Apress)&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt;Data for AI is produced by Datastrato, the original creator of Apache Gravitino. Sponsored by Neo4j.&lt;/p&gt;&lt;p&gt;Join the community: &lt;a href=&quot;https://datastrato.ai/discord&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://datastrato.ai/discord&lt;/a&gt;&lt;/p&gt;&lt;p&gt;Next meetup: &lt;a href=&quot;https://lu.ma/dataforai&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://lu.ma/dataforai&lt;/a&gt;&lt;/p&gt;&lt;p&gt;Watch on YouTube: &lt;a href=&quot;https://youtube.com/@data-for-ai&quot; rel=&quot;noopener noreferrer nofollow&quot;&gt;https://youtube.com/@data-for-ai&lt;/a&gt;&lt;/p&gt;</itunes:summary><itunes:explicit>no</itunes:explicit><itunes:duration>00:26:50</itunes:duration><itunes:image href="https://hosting-media.riverside.com/media/podcasts/e7b3fbde-3f1c-4e71-8db0-b0f88ed055c2/logos/15709e5a-0bbc-4763-b94e-ef398db21bcc.png"/><itunes:title>Scott Haines (Part 1): Storm, Spark, Delta Lake, and why he still writes code by hand</itunes:title><itunes:episodeType>full</itunes:episodeType></item></channel></rss>