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    <description>Practical writing on Databricks, Spark, Delta Lake, and the craft of data engineering.</description>
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    <lastBuildDate>Thu, 20 Aug 2026 13:30:43 GMT</lastBuildDate>
    <item>
      <title>I built a data engineering project in two evenings. Here is exactly what I did</title>
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      <pubDate>Thu, 20 Aug 2026 13:30:43 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A boundary instead of a study plan: two evenings, 100 messy orders, one gold table, and a pipeline that runs twice without breaking. Here is the full walkthrough you can repeat tonight in Databricks Free Edition.</description>
      <category>Databricks</category>
      <category>Data Engineering</category>
      <category>PySpark</category>
      <category>Getting Started</category>
      <category>2026</category>
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    <item>
      <title>The event arrived two days late. How to handle late data in Databricks</title>
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      <pubDate>Thu, 20 Aug 2026 01:50:50 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A phone was offline, a partner file was late, a queue backed up. Here is how to keep event time honest and stop numbers from drifting quietly.</description>
      <category>Databricks</category>
      <category>Streaming</category>
      <category>Delta Lake</category>
      <category>Data Quality</category>
    </item>
    <item>
      <title>The backfill. How to reload history in Databricks without breaking downstream tables</title>
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      <pubDate>Wed, 19 Aug 2026 01:51:14 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Reloading March means touching a table six dashboards already read. Here is the plan that makes a backfill boring instead of frightening.</description>
      <category>Databricks</category>
      <category>Delta Lake</category>
      <category>Backfill</category>
      <category>Pipelines</category>
    </item>
    <item>
      <title>Agent discovers. Agent applies. What that changes for data engineers</title>
      <link>https://bricksnotes.com/blog/agent-discovers-agent-applies</link>
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      <pubDate>Tue, 18 Aug 2026 13:38:17 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>An agent found the table, read the schema, and proposed the merge in forty seconds. Everything it got right came from work a data engineer had already done.</description>
      <category>AI Agents</category>
      <category>Unity Catalog</category>
      <category>Data Quality</category>
      <category>Delta Lake</category>
    </item>
    <item>
      <title>The schema changed overnight. How to survive it in Databricks</title>
      <link>https://bricksnotes.com/blog/schema-evolution-databricks-pipelines</link>
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      <pubDate>Tue, 18 Aug 2026 01:46:27 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>A source team added one column and renamed another, and the nightly job failed. Here is how schema change actually works in Databricks, and how to handle each case calmly.</description>
      <category>Databricks</category>
      <category>Delta Lake</category>
      <category>Schema Evolution</category>
      <category>Auto Loader</category>
    </item>
    <item>
      <title>You are new to data engineering. Here is how to become an AI data engineer with BricksNotes</title>
      <link>https://bricksnotes.com/blog/how-to-become-ai-data-engineer-with-bricksnotes</link>
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      <pubDate>Mon, 17 Aug 2026 00:43:50 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>A complete path for a fresh data engineering aspirant. Free Edition setup, the lessons in order, the habits that matter, and how to grow into AI ready work.</description>
      <category>Career</category>
      <category>Beginners</category>
      <category>Learning Path</category>
      <category>AI Data Engineer</category>
    </item>
    <item>
      <title>Auto Loader or COPY INTO? How to ingest files into Databricks without breaking things</title>
      <link>https://bricksnotes.com/blog/auto-loader-vs-copy-into-databricks</link>
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      <pubDate>Sun, 16 Aug 2026 04:27:00 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>A daily CSV drop grew to seven hundred files and turned a five minute job into forty. Here is how COPY INTO and Auto Loader remember what they already loaded, and how to choose.</description>
      <category>Databricks</category>
      <category>Auto Loader</category>
      <category>Ingestion</category>
      <category>Delta Lake</category>
    </item>
    <item>
      <title>The job ran twice. Why safe reruns decide if a pipeline is production ready</title>
      <link>https://bricksnotes.com/blog/idempotent-pipelines-safe-reruns-databricks</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/idempotent-pipelines-safe-reruns-databricks</guid>
      <pubDate>Sat, 15 Aug 2026 03:02:12 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>A nightly load failed at 2am, got rerun at 7am, and quietly doubled a revenue number for a week. Here is what idempotency really means, and the four write patterns that make a Databricks pipeline safe to run twice.</description>
      <category>Databricks</category>
      <category>Delta Lake</category>
      <category>Pipelines</category>
      <category>Data Quality</category>
    </item>
    <item>
      <title>From a research lab to $190 billion: the Databricks story and what comes next</title>
      <link>https://bricksnotes.com/blog/databricks-190-billion-journey</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-190-billion-journey</guid>
      <pubDate>Fri, 14 Aug 2026 02:37:26 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>Databricks closed a $5 billion round at a $190 billion valuation in August 2026. Here is the full thirteen-year story behind that number, from Spark at Berkeley to Delta Lake, Unity Catalog, Lakeflow and the agent era, and what it means for data engineers.</description>
      <category>Databricks</category>
      <category>Story</category>
      <category>Lakehouse</category>
      <category>Unity Catalog</category>
      <category>2026</category>
    </item>
    <item>
      <title>Streaming table or materialized view? How to choose in a Databricks pipeline</title>
      <link>https://bricksnotes.com/blog/streaming-table-vs-materialized-view-databricks</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/streaming-table-vs-materialized-view-databricks</guid>
      <pubDate>Thu, 13 Aug 2026 03:54:48 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>A nightly silver job that used to finish in twenty minutes started running past breakfast. Nothing was wrong with the code. It was rebuilding the whole table every night. Here is how to decide between a streaming table and a materialized view in Databricks, with examples that run on Free Edition.</description>
      <category>Lakeflow</category>
      <category>Streaming</category>
      <category>Materialized Views</category>
      <category>Databricks</category>
    </item>
    <item>
      <title>Z-ORDER or liquid clustering? How to lay out a Delta table in 2026</title>
      <link>https://bricksnotes.com/blog/delta-lake-zorder-vs-liquid-clustering</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/delta-lake-zorder-vs-liquid-clustering</guid>
      <pubDate>Wed, 12 Aug 2026 03:14:25 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>Your dashboard slowed down and the query never changed. Most Databricks performance problems are layout problems. A practical guide to partitioning, Z-ORDER, and liquid clustering in 2026.</description>
      <category>Delta Lake</category>
      <category>Performance</category>
      <category>Liquid Clustering</category>
      <category>Databricks</category>
    </item>
    <item>
      <title>Context engineering is becoming a real job skill for data engineers</title>
      <link>https://bricksnotes.com/blog/context-engineering-skill-for-data-engineers</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/context-engineering-skill-for-data-engineers</guid>
      <pubDate>Mon, 10 Aug 2026 12:41:12 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>An agent answered a simple question confidently and wrongly. Nobody had decided what it was allowed to know. That decision is now a job, and data engineers are the natural owners of it.</description>
      <category>Context Engineering</category>
      <category>AI Agents</category>
      <category>Databricks</category>
      <category>Governance</category>
      <category>context-advantage</category>
    </item>
    <item>
      <title>The data stack is being redesigned for AI agents</title>
      <link>https://bricksnotes.com/blog/agentic-data-stack-built-for-ai-agents</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/agentic-data-stack-built-for-ai-agents</guid>
      <pubDate>Sat, 08 Aug 2026 15:50:08 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>Data platforms assumed a human was always in the loop. Agents break that assumption. Here is what context, tool access, observability, cost, and approval look like now.</description>
      <category>AI Agents</category>
      <category>Databricks</category>
      <category>Governance</category>
      <category>Context Engineering</category>
    </item>
    <item>
      <title>Databricks Lakemeter: putting a number on a pipeline before you build it</title>
      <link>https://bricksnotes.com/blog/databricks-lakemeter-cost-estimation</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-lakemeter-cost-estimation</guid>
      <pubDate>Fri, 07 Aug 2026 01:39:08 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>Someone asks what your pipeline will cost. Lakemeter, the open source tool from Databricks Labs, turns that shrug into an estimate you can defend.</description>
      <category>Databricks</category>
      <category>Cost</category>
      <category>Open Source</category>
    </item>
    <item>
      <title>Unity AI Gateway is GA. Here is what it changes for data engineers.</title>
      <link>https://bricksnotes.com/blog/databricks-unity-ai-gateway-ga-explained</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-unity-ai-gateway-ga-explained</guid>
      <pubDate>Wed, 05 Aug 2026 19:48:57 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>Databricks made Unity AI Gateway generally available on August 4, 2026. Here is what it actually does, why cost and control matter more than model choice, and what still belongs to you.</description>
      <category>Databricks</category>
      <category>AI</category>
      <category>Governance</category>
      <category>Data Engineering</category>
    </item>
    <item>
      <title>Databricks Variant is now generally available. Here is how to use it.</title>
      <link>https://bricksnotes.com/blog/databricks-variant-data-type-explained</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-variant-data-type-explained</guid>
      <pubDate>Wed, 05 Aug 2026 03:00:00 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>Databricks Variant is now generally available. It is a native SQL type for semi-structured data that solves the old tradeoff between flexibility and query performance. Here is what it does, how Variant Shredding works, and how to start using it with real code.</description>
      <category>Databricks</category>
      <category>Delta Lake</category>
      <category>Data Engineering</category>
    </item>
    <item>
      <title>100,000 data professionals. 25,000 practice exams. Thank you.</title>
      <link>https://bricksnotes.com/blog/100000-data-professionals-bricksnotes-milestone</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/100000-data-professionals-bricksnotes-milestone</guid>
      <pubDate>Fri, 31 Jul 2026 03:43:02 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>More than 100,000 unique data professionals have visited BricksNotes, and over 25,000 practice exams have been completed across Associate, Professional, and Analyst certifications. What these numbers mean, and where we go next.</description>
      <category>Community</category>
      <category>Milestone</category>
    </item>
    <item>
      <title>Genie Code can now convert your legacy SQL. Here is what data engineers should know.</title>
      <link>https://bricksnotes.com/blog/databricks-genie-code-sql-migration-explained</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-genie-code-sql-migration-explained</guid>
      <pubDate>Fri, 31 Jul 2026 03:26:56 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Databricks announced an agentic code converter in Genie Code that translates proprietary SQL dialects to ANSI SQL. Here is what it does, what it does not do, and why open SQL matters for your career.</description>
      <category>databricks</category>
      <category>sql-migration</category>
      <category>genie-code</category>
      <category>ansi-sql</category>
      <category>unity-catalog</category>
    </item>
    <item>
      <title>The new Databricks Context Engineer Associate, explained for data engineers</title>
      <link>https://bricksnotes.com/blog/databricks-context-engineer-associate-explained</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-context-engineer-associate-explained</guid>
      <pubDate>Thu, 30 Jul 2026 02:04:01 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Databricks has a new certification that is not about models. It is about the information you put around them. Here is what the Context Engineer Associate covers, and why data engineers are closer to it than they think.</description>
      <category>databricks</category>
      <category>certification</category>
      <category>context-engineering</category>
      <category>ai</category>
    </item>
    <item>
      <title>The Databricks Free Edition playbook for 2026</title>
      <link>https://bricksnotes.com/blog/databricks-free-edition-playbook-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-free-edition-playbook-2026</guid>
      <pubDate>Tue, 28 Jul 2026 02:35:10 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A calm, practical seven-day path for learning Databricks on Free Edition in 2026. What you get, what you do not, and the exact steps to build real skills.</description>
      <category>Databricks</category>
      <category>Free Edition</category>
      <category>Learning</category>
    </item>
    <item>
      <title>What&apos;s quietly shipping in Databricks: late July 2026</title>
      <link>https://bricksnotes.com/blog/databricks-previews-late-july-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-previews-late-july-2026</guid>
      <pubDate>Mon, 27 Jul 2026 13:40:34 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A calm read of the Databricks previews from mid to late July 2026. Genie Agent API, agents that can read files in Unity Catalog Volumes, Lakebridge, pipeline unit tests, and a few smaller wins.</description>
      <category>databricks</category>
      <category>previews</category>
      <category>genie</category>
      <category>lakeflow</category>
      <category>unity-catalog</category>
    </item>
    <item>
      <title>How to Become an AI Data Engineer in 2026</title>
      <link>https://bricksnotes.com/blog/ai-data-engineer-roadmap-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/ai-data-engineer-roadmap-2026</guid>
      <pubDate>Sun, 26 Jul 2026 21:00:00 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A calm, stage-based roadmap to becoming an AI data engineer in 2026. Databricks foundation, lakehouse pipelines, AI applications, and agent-ready systems.</description>
      <category>ai-data-engineer</category>
      <category>career</category>
      <category>roadmap</category>
      <category>context-advantage</category>
      <category>databricks</category>
    </item>
    <item>
      <title>I Failed the Databricks Associate Exam Twice. Here&apos;s What Fixed It.</title>
      <link>https://bricksnotes.com/blog/failed-databricks-associate-exam-twice-what-fixed-it</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/failed-databricks-associate-exam-twice-what-fixed-it</guid>
      <pubDate>Sun, 26 Jul 2026 03:26:07 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Two failed attempts taught me more than any cheat sheet. Here is the calm, five-part routine and two-week plan that finally worked.</description>
      <category>certification</category>
      <category>associate-exam</category>
      <category>study-guide</category>
    </item>
    <item>
      <title>Apache Spark 4.2: Defining truth in the age of AI</title>
      <link>https://bricksnotes.com/blog/apache-spark-42-defining-truth-age-of-ai</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/apache-spark-42-defining-truth-age-of-ai</guid>
      <pubDate>Sat, 25 Jul 2026 02:52:39 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Apache Spark 4.2 shipped in July 2026. Metric Views, mature Spark Connect, vector search in SQL, and Auto CDC change where truth lives, how agents talk to Spark, and how streaming catches up to reality.</description>
      <category>Spark</category>
      <category>Databricks</category>
      <category>AI</category>
    </item>
    <item>
      <title>Design Beautiful AI/BI Dashboards People Actually Read</title>
      <link>https://bricksnotes.com/blog/design-beautiful-aibi-dashboards</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/design-beautiful-aibi-dashboards</guid>
      <pubDate>Tue, 21 Jul 2026 02:42:59 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Themes, layout, and the small design habits that turn a Databricks AI/BI dashboard from noisy to trustworthy.</description>

    </item>
    <item>
      <title>Agent Bricks is GA. Here&apos;s How to Ship an Agent Without Regret.</title>
      <link>https://bricksnotes.com/blog/agent-bricks-ga-ship-without-regret</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/agent-bricks-ga-ship-without-regret</guid>
      <pubDate>Tue, 21 Jul 2026 02:39:25 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Agent Bricks is now generally available. Here is how to take an agent from demo to production without it going off the rails.</description>

    </item>
    <item>
      <title>Lakebase is GA. Do You Still Need a Separate Postgres?</title>
      <link>https://bricksnotes.com/blog/lakebase-ga-do-you-still-need-postgres</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/lakebase-ga-do-you-still-need-postgres</guid>
      <pubDate>Sun, 19 Jul 2026 02:03:59 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Lakebase is generally available. Do you still need a separate Postgres next to your lakehouse? A calm, honest answer.</description>
      <category>lakebase</category>
      <category>postgres</category>
      <category>unity-catalog</category>
      <category>architecture</category>
      <category>databricks</category>
      <category>2026</category>
    </item>
    <item>
      <title>Your AI is Ready. Is Your Data Foundation?</title>
      <link>https://bricksnotes.com/blog/data-foundation-for-ai-agents-databricks</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/data-foundation-for-ai-agents-databricks</guid>
      <pubDate>Sat, 18 Jul 2026 04:05:07 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Before you plug an agent into your warehouse, ask four quiet questions about the data underneath it.</description>
      <category>ai-agents</category>
      <category>data-quality</category>
      <category>unity-catalog</category>
      <category>medallion</category>
      <category>databricks</category>
    </item>
    <item>
      <title>Context, Control, Cost, Choice: Four Questions Every Data Engineer Should Ask in the Agentic AI Era</title>
      <link>https://bricksnotes.com/blog/context-control-cost-choice-data-engineer-guide</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/context-control-cost-choice-data-engineer-guide</guid>
      <pubDate>Fri, 17 Jul 2026 03:25:14 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>The interesting question is not which model to pick. It is what the model sees, what it is allowed to do, what one answer costs, and how locked in you become.</description>
      <category>context-advantage</category>
      <category>ai-agents</category>
      <category>career</category>
      <category>databricks</category>
    </item>
    <item>
      <title>Genie One goes mobile: what it means for data teams</title>
      <link>https://bricksnotes.com/blog/genie-one-mobile-what-it-means</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/genie-one-mobile-what-it-means</guid>
      <pubDate>Thu, 16 Jul 2026 15:05:29 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Genie One is now a mobile app. A quiet shift in how business users meet their data, and a bigger one than it looks.</description>
      <category>databricks</category>
      <category>genie</category>
      <category>mobile</category>
      <category>ai</category>
      <category>unity-catalog</category>
    </item>
    <item>
      <title>The Data Analyst Associate practice exam is here</title>
      <link>https://bricksnotes.com/blog/databricks-data-analyst-associate-practice-exam-live</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-data-analyst-associate-practice-exam-live</guid>
      <pubDate>Tue, 14 Jul 2026 19:35:35 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A free, full-length practice exam for the Databricks Data Analyst Associate certification is now live. Try it, miss it, review it, and try again.</description>
      <category>databricks</category>
      <category>certification</category>
      <category>data-analyst-associate</category>
      <category>free-edition</category>
    </item>
    <item>
      <title>What Data Engineers Really Do: Moving Data Safely From Source to Value</title>
      <link>https://bricksnotes.com/blog/what-data-engineers-really-do</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/what-data-engineers-really-do</guid>
      <pubDate>Sun, 12 Jul 2026 04:33:18 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Data engineers help data move safely from where it is created to where it becomes useful. A calm, beginner-friendly guide to the real job.</description>
      <category>data-engineering</category>
      <category>data-pipelines</category>
      <category>beginners</category>
      <category>databricks</category>
    </item>
    <item>
      <title>We refreshed the book for the latest Databricks Free Edition</title>
      <link>https://bricksnotes.com/blog/free-edition-refresh-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/free-edition-refresh-2026</guid>
      <pubDate>Fri, 10 Jul 2026 03:13:04 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>We reviewed every chapter for accuracy, tidied the writing, and updated the steps for how Databricks Free Edition works today, including serverless compute and the newer chapters on pipelines, Apps, and Genie.</description>
      <category>databricks</category>
      <category>free-edition</category>
      <category>update</category>
      <category>data-engineering</category>
    </item>
    <item>
      <title>Innovation happens when data, AI, and people come together</title>
      <link>https://bricksnotes.com/blog/innovation-data-ai-people-together</link>
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      <pubDate>Sun, 05 Jul 2026 23:37:13 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>A retail forecast that failed, a hospital model, a fraud check, and a logistics team. Real stories about why innovation lives where data, AI, and people meet.</description>
      <category>data-and-ai</category>
      <category>innovation</category>
      <category>data-engineering</category>
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    <item>
      <title>The builders advantage: why Databricks thinks the way it does</title>
      <link>https://bricksnotes.com/blog/databricks-builders-advantage-data-ai</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-builders-advantage-data-ai</guid>
      <pubDate>Thu, 02 Jul 2026 12:55:18 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>The people who lead Databricks are the same people who built the underlying technology. Here is why that matters, and why data and AI is a direction, not a trend.</description>
      <category>databricks</category>
      <category>data-and-ai</category>
      <category>leadership</category>
    </item>
    <item>
      <title>Databricks Data Engineer Associate sample questions, explained</title>
      <link>https://bricksnotes.com/blog/databricks-data-engineer-associate-sample-questions</link>
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      <pubDate>Wed, 01 Jul 2026 03:43:59 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A set of Databricks Data Engineer Associate sample questions with clear explanations, so you learn how to reason, not just memorize answers.</description>
      <category>databricks</category>
      <category>certification</category>
      <category>data-engineer-associate</category>
      <category>sample-questions</category>
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    <item>
      <title>A calm study plan for the Databricks Data Engineer Associate exam</title>
      <link>https://bricksnotes.com/blog/databricks-data-engineer-associate-exam-study-plan</link>
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      <pubDate>Wed, 01 Jul 2026 03:43:59 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A simple, week-by-week study plan for the Databricks Certified Data Engineer Associate exam, built on practice instead of memorization.</description>
      <category>databricks</category>
      <category>certification</category>
      <category>data-engineer-associate</category>
      <category>study-plan</category>
    </item>
    <item>
      <title>Common mistakes to avoid on the Databricks Data Engineer Associate exam</title>
      <link>https://bricksnotes.com/blog/databricks-data-engineer-associate-common-mistakes</link>
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      <pubDate>Wed, 01 Jul 2026 03:43:59 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>The most common mistakes people make on the Databricks Data Engineer Associate exam, and simple habits that prevent them.</description>
      <category>databricks</category>
      <category>certification</category>
      <category>data-engineer-associate</category>
      <category>exam-tips</category>
    </item>
    <item>
      <title>CustomerLake: the CDP moves into the lakehouse</title>
      <link>https://bricksnotes.com/blog/databricks-customerlake-agentic-cdp-2026</link>
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      <pubDate>Sat, 27 Jun 2026 16:20:50 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>Databricks introduced CustomerLake, an agentic CDP built into the lakehouse. Here is what it changes, in plain language, for the people who build data systems.</description>

    </item>
    <item>
      <title>Building Quietly, Helping Globally: The BricksNotes Story</title>
      <link>https://bricksnotes.com/blog/bricksnotes-story-helping-data-professionals-worldwide</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/bricksnotes-story-helping-data-professionals-worldwide</guid>
      <pubDate>Thu, 25 Jun 2026 18:30:24 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>Why BricksNotes exists, what we have built so far, and a genuine thank you to the learners who make this work worth doing.</description>
      <category>BricksNotes</category>
      <category>Data Engineering</category>
      <category>Community</category>
    </item>
    <item>
      <title>Reyden explained clearly: the engine behind Lakehouse//RT</title>
      <link>https://bricksnotes.com/blog/reyden-explained-clearly-lakehouse-rt-engine</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/reyden-explained-clearly-lakehouse-rt-engine</guid>
      <pubDate>Wed, 24 Jun 2026 13:53:33 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>A lot of people saw the word Reyden in the recent Databricks announcements and asked the same thing: what exactly is Reyden? Here is a calm explanation of the engine, the warehouse it powers, and why this matters for data engineers.</description>
      <category>databricks</category>
      <category>lakehouse-rt</category>
      <category>reyden</category>
      <category>real-time analytics</category>
      <category>2026</category>
    </item>
    <item>
      <title>The five fiefdoms of the data realm and why their borders are fading</title>
      <link>https://bricksnotes.com/blog/five-fiefdoms-of-the-data-realm</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/five-fiefdoms-of-the-data-realm</guid>
      <pubDate>Tue, 23 Jun 2026 02:30:14 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>OLTP, data engineering, data science, the data warehouse, and real-time analytics each grew up as its own kingdom. Here is a calm map of the five fiefdoms, why their borders existed, and what changes for you when they begin to merge.</description>
      <category>data platform</category>
      <category>lakehouse</category>
      <category>data engineering</category>
      <category>2026</category>
    </item>
    <item>
      <title>AI everywhere for everyone: what Reliance and Databricks just told data engineers</title>
      <link>https://bricksnotes.com/blog/mukesh-ambani-reliance-databricks-ai-for-everyone-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/mukesh-ambani-reliance-databricks-ai-for-everyone-2026</guid>
      <pubDate>Sun, 21 Jun 2026 15:42:29 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>At the Databricks Data and AI Summit 2026, Mukesh Ambani called the Reliance-Databricks work one of the world&apos;s largest data and AI transformations. Behind the vision sits a quiet lesson every data engineer should hear.</description>
      <category>databricks</category>
      <category>reliance</category>
      <category>ai</category>
      <category>data engineering</category>
      <category>2026</category>
    </item>
    <item>
      <title>One Copy of Data: What LTAP Quietly Changes for Every Data Engineer</title>
      <link>https://bricksnotes.com/blog/databricks-ltap-one-copy-of-data-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-ltap-one-copy-of-data-2026</guid>
      <pubDate>Thu, 18 Jun 2026 06:16:13 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>For forty years every data stack split operations from analytics. LTAP and Lakebase quietly end that divide, and it reshapes what data engineers do next.</description>
      <category>databricks</category>
      <category>lakebase</category>
      <category>ltap</category>
      <category>ai agents</category>
      <category>lakehouse</category>
      <category>2026</category>
    </item>
    <item>
      <title>What Databricks Summit 2026 told us about the next ten years</title>
      <link>https://bricksnotes.com/blog/databricks-summit-2026-keynote-recap</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-summit-2026-keynote-recap</guid>
      <pubDate>Wed, 17 Jun 2026 02:58:26 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>A calm recap of the Databricks Data and AI Summit keynote: why the real story was context, not models, and what the new agents mean for data engineers.</description>
      <category>databricks</category>
      <category>summit 2026</category>
      <category>ai agents</category>
      <category>lakehouse</category>
      <category>2026</category>
    </item>
    <item>
      <title>Lakebase looks like a platform bet, not a side feature</title>
      <link>https://bricksnotes.com/blog/databricks-lakebase-postgres-lakehouse-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-lakebase-postgres-lakehouse-2026</guid>
      <pubDate>Tue, 16 Jun 2026 13:36:20 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>Databricks took Lakebase to GA, a managed Postgres for real-time apps with branching, autoscaling, and Unity Catalog. A calm look at why it matters for data.</description>
      <category>databricks</category>
      <category>lakebase</category>
      <category>postgres</category>
      <category>lakehouse</category>
      <category>2026</category>
    </item>
    <item>
      <title>The flywheel nobody can stop: why more compute and more data keep making AI better</title>
      <link>https://bricksnotes.com/blog/the-ai-flywheel-compute-data-loop-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/the-ai-flywheel-compute-data-loop-2026</guid>
      <pubDate>Mon, 15 Jun 2026 13:05:18 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>More compute and data make AI better, better AI brings more usage, more usage makes more data. A calm look at the loop driving AI, and where data engineers fit.</description>
      <category>ai</category>
      <category>data engineering</category>
      <category>compute</category>
      <category>vision</category>
      <category>2026</category>
    </item>
    <item>
      <title>Omnigent feels interesting because it is not trying to be just another agent</title>
      <link>https://bricksnotes.com/blog/databricks-omnigent-meta-harness-agents-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-omnigent-meta-harness-agents-2026</guid>
      <pubDate>Sun, 14 Jun 2026 16:11:09 GMT</pubDate>
      <dc:creator>Team BricksNotes</dc:creator>
      <description>Databricks Omnigent is a new open source meta-harness for AI agents. A calm look at why coordinating many agents, not building one more, is the real problem.</description>
      <category>databricks</category>
      <category>omnigent</category>
      <category>ai agents</category>
      <category>open source</category>
      <category>2026</category>
    </item>
    <item>
      <title>OpenSharing: Databricks Turns Delta Sharing Into an Open Standard for Data and AI</title>
      <link>https://bricksnotes.com/blog/databricks-opensharing-delta-sharing-evolution-2026</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-opensharing-delta-sharing-evolution-2026</guid>
      <pubDate>Thu, 11 Jun 2026 02:06:33 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>Databricks open-sourced OpenSharing, the evolution of Delta Sharing. Here is what zero-copy data and AI sharing means for data engineers and enterprises.</description>
      <category>databricks</category>
      <category>opensharing</category>
      <category>delta sharing</category>
      <category>open standard</category>
      <category>ai</category>
      <category>2026</category>
    </item>
    <item>
      <title>Genie Goes Pay-As-You-Go: What the New Pricing and Budgets Mean for Data Engineers</title>
      <link>https://bricksnotes.com/blog/databricks-genie-pay-as-you-go-pricing-budgets-2026</link>
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      <pubDate>Wed, 10 Jun 2026 03:03:14 GMT</pubDate>
      <dc:creator>BrickNotes Editorial</dc:creator>
      <description>On July 6, 2026, Databricks Genie moves to pay-as-you-go pricing. Here is a calm look at the DBU costs, the compute underneath, and why usage budgets matter.</description>
      <category>databricks</category>
      <category>genie</category>
      <category>pricing</category>
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