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		<title>Data on carlos zansavio</title>
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				<title>My data platform diary - Week 1</title>
				<link>http://carlos.sjdr.cloud/posts/data-platform-diary-week1/</link>
				<pubDate>Sat, 18 Jul 2026 00:00:00 +0000</pubDate>
				<guid>http://carlos.sjdr.cloud/posts/data-platform-diary-week1/</guid>
				<description>&lt;p&gt;Some of you already know I run a bunch of self-hosted services out of a homelab I&amp;rsquo;ve been building for over two years now. It started as a place to store personal files, but it&amp;rsquo;s grown into something a few people in my local community actually rely on.&lt;/p&gt;&#xA;&lt;p&gt;I work in data engineering for a living, but I&amp;rsquo;ve never had my own data platform. At some point that stopped making sense to me — I have the infrastructure, I have the knowledge, so why not build one?&lt;/p&gt;</description>
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				<title>Apache Spark exercises to test and improve your knowledge</title>
				<link>http://carlos.sjdr.cloud/posts/apache-spark-exercises/</link>
				<pubDate>Sat, 11 Jul 2026 00:00:00 +0000</pubDate>
				<guid>http://carlos.sjdr.cloud/posts/apache-spark-exercises/</guid>
				<description>&lt;p&gt;You&amp;rsquo;ve read the docs. You can write queries using SparkSQL or PySpark. You&amp;rsquo;re pretty sure you understand how Spark works under the hood. Then an interviewer asks you to actually reason through a shuffle, and that confidence gets shaky fast.&lt;/p&gt;&#xA;&lt;p&gt;Been there.&lt;/p&gt;&#xA;&lt;p&gt;What actually got these concepts to stick for me was working through math problems tied to Spark&amp;rsquo;s internals. You have to understand the mechanics or the numbers don&amp;rsquo;t add up.&#xA;So I put together a set of exercises built around exactly that.&lt;/p&gt;</description>
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				<title>Building a CDC Streaming Pipeline locally</title>
				<link>http://carlos.sjdr.cloud/posts/creating-a-simple-cdc-streaming-pipeline/</link>
				<pubDate>Sun, 05 Jul 2026 00:00:00 +0000</pubDate>
				<guid>http://carlos.sjdr.cloud/posts/creating-a-simple-cdc-streaming-pipeline/</guid>
				<description>&lt;h1 id=&#34;introduction&#34;&gt;&#xA;  Introduction&#xA;  &lt;a class=&#34;heading-link&#34; href=&#34;#introduction&#34;&gt;&#xA;    &lt;i class=&#34;fa-solid fa-link&#34; aria-hidden=&#34;true&#34; title=&#34;Link to heading&#34;&gt;&lt;/i&gt;&#xA;    &lt;span class=&#34;sr-only&#34;&gt;Link to heading&lt;/span&gt;&#xA;  &lt;/a&gt;&#xA;&lt;/h1&gt;&#xA;&lt;p&gt;Want to understand what a Change Data Capture (CDC) streaming pipeline is and how to build one locally with Docker? Let me help you. This is a POC project to understand how things work in real life.&lt;/p&gt;&#xA;&lt;p&gt;You can find the repository &lt;a href=&#34;https://github.com/carloszan/cdc&#34;  class=&#34;external-link&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;h1 id=&#34;whats-cdc-streaming-pipeline&#34;&gt;&#xA;  What&amp;rsquo;s CDC Streaming pipeline?&#xA;  &lt;a class=&#34;heading-link&#34; href=&#34;#whats-cdc-streaming-pipeline&#34;&gt;&#xA;    &lt;i class=&#34;fa-solid fa-link&#34; aria-hidden=&#34;true&#34; title=&#34;Link to heading&#34;&gt;&lt;/i&gt;&#xA;    &lt;span class=&#34;sr-only&#34;&gt;Link to heading&lt;/span&gt;&#xA;  &lt;/a&gt;&#xA;&lt;/h1&gt;&#xA;&lt;p&gt;CDC stands for Change Data Capture. In simple terms, it streams database update logs to a topic (if using Kafka), so other systems can stay in sync with the source database in near real-time. This approach is especially useful for feeding data into Online Analytical Processing (OLAP) platforms, where analysts need fresh data to work with.&lt;/p&gt;</description>
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