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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, 03 Sep 2026 02:11:09 GMT</lastBuildDate>
    <item>
      <title>The next phase of data engineering is not faster pipelines. It is faster decisions</title>
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      <pubDate>Thu, 03 Sep 2026 02:11:09 GMT</pubDate>
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      <description>Your pipeline runs in four minutes and the decision still waits for Monday. A practical look at decision latency, designing backwards from the decision, and what changes when the consumer is an agent.</description>
      <category>data engineering</category>
      <category>decisions</category>
      <category>databricks</category>
    </item>
    <item>
      <title>The table had 40,000 tiny files. The small file problem in Databricks, explained</title>
      <link>https://bricksnotes.com/blog/databricks-small-file-problem-optimize-vacuum</link>
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      <pubDate>Wed, 02 Sep 2026 03:10:00 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>A Delta table that was fast in week one became slow by month three. The data had not grown much. The file count had. Here is what the small file problem is, why streaming and frequent merges cause it, and how OPTIMIZE and VACUUM keep a table healthy.</description>
      <category>databricks</category>
      <category>delta lake</category>
      <category>performance</category>
      <category>fundamentals</category>
    </item>
    <item>
      <title>What did this table look like last Tuesday? Delta Lake time travel, explained</title>
      <link>https://bricksnotes.com/blog/delta-lake-time-travel-explained</link>
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      <pubDate>Tue, 01 Sep 2026 03:38:53 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>Delta Lake keeps every version of your table. Learn how to query older versions with VERSION AS OF, read table history, and undo bad writes with RESTORE, with simple examples that run in Databricks Free Edition.</description>
      <category>Databricks</category>
      <category>Delta Lake</category>
      <category>time travel</category>
      <category>data engineering</category>
    </item>
    <item>
      <title>The dashboard was wrong before anyone knew. Observability in a Databricks pipeline</title>
      <link>https://bricksnotes.com/blog/databricks-pipeline-observability-alerts-runbook</link>
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      <pubDate>Mon, 31 Aug 2026 01:51:24 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>A green run is a weak signal. Here are the four questions your pipeline should answer on its own, with freshness checks, run metrics, Delta constraints and alerts you can build in Free Edition.</description>
      <category>Databricks</category>
      <category>monitoring</category>
      <category>data-quality</category>
      <category>pipelines</category>
    </item>
    <item>
      <title>Databricks acquired Electric. Why data next to the agent matters</title>
      <link>https://bricksnotes.com/blog/databricks-electric-acquisition-lakebase-agents</link>
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      <pubDate>Sun, 30 Aug 2026 02:25:52 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>Databricks acquiring Electric is a bet that agents need data close to where they run. Here is what it means for Lakebase, and what it changes for data engineers.</description>
      <category>Databricks</category>
      <category>ai-agents</category>
      <category>lakebase</category>
      <category>architecture</category>
    </item>
    <item>
      <title>Lakebase, explained simply. Where it came from and what to build with it</title>
      <link>https://bricksnotes.com/blog/what-is-lakebase-explained-simply</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/what-is-lakebase-explained-simply</guid>
      <pubDate>Sat, 29 Aug 2026 02:56:00 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>Lakebase is managed Postgres inside Databricks. Here is the idea behind it, where it fits, the use cases worth trying, and why agents make it more than a convenience feature.</description>
      <category>Databricks</category>
      <category>Lakebase</category>
      <category>Data + AI</category>
      <category>Architecture</category>
      <category>Agents</category>
    </item>
    <item>
      <title>Same result, 3 seconds or 30 minutes. Query optimization in Databricks</title>
      <link>https://bricksnotes.com/blog/databricks-query-optimization-execution-plan</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-query-optimization-execution-plan</guid>
      <pubDate>Fri, 28 Aug 2026 01:42:09 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>Two queries, identical results, wildly different cost. Here is what happens between the SQL you write and the answer you get, and the seven techniques that decide how much work the engine does.</description>
      <category>Databricks</category>
      <category>Spark</category>
      <category>Performance</category>
      <category>SQL</category>
      <category>Data Engineering</category>
    </item>
    <item>
      <title>The join that ran for seven hours. Broadcast and shuffle joins in Databricks</title>
      <link>https://bricksnotes.com/blog/databricks-broadcast-vs-shuffle-joins</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-broadcast-vs-shuffle-joins</guid>
      <pubDate>Thu, 27 Aug 2026 02:09:50 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>One line joined orders to customers, and an eleven minute job ran all night. Here is what a join really does on a cluster, and how to choose the right one.</description>
      <category>Databricks</category>
      <category>Spark</category>
      <category>Performance</category>
      <category>Data Engineering</category>
    </item>
    <item>
      <title>The pipeline kept running. Why silent schema changes are the dangerous ones</title>
      <link>https://bricksnotes.com/blog/schema-changes-data-contracts-databricks</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/schema-changes-data-contracts-databricks</guid>
      <pubDate>Wed, 26 Aug 2026 01:34:12 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>Schema evolution is normal. Uncontrolled schema evolution is dangerous. The five change types, why a data contract does what a schema cannot, and six habits that make change visible, testable and safe in Databricks.</description>
      <category>Databricks</category>
      <category>Schema Evolution</category>
      <category>Data Quality</category>
      <category>Data Engineering</category>
    </item>
    <item>
      <title>The order was counted twice. Duplicate records in Databricks, explained</title>
      <link>https://bricksnotes.com/blog/databricks-duplicate-records-deduplication</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-duplicate-records-deduplication</guid>
      <pubDate>Tue, 25 Aug 2026 00:34:08 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>A pipeline can finish green and your numbers can still be wrong. Duplicates rarely break pipelines. They break business decisions. Here is how to handle them properly.</description>
      <category>Databricks</category>
      <category>Data Quality</category>
      <category>SQL</category>
      <category>Fundamentals</category>
    </item>
    <item>
      <title>The next database may be built as much for agents as for developers</title>
      <link>https://bricksnotes.com/blog/databases-built-for-agents-not-just-developers</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databases-built-for-agents-not-just-developers</guid>
      <pubDate>Mon, 24 Aug 2026 00:53:14 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>For forty years databases were designed around a human who could ask a teammate. Agents cannot. Here is how a data platform changes when machines are the main readers, and what to do about it in Databricks this week.</description>
      <category>AI Agents</category>
      <category>Unity Catalog</category>
      <category>Data Engineering</category>
      <category>Databricks</category>
    </item>
    <item>
      <title>One task ran for forty minutes. Data skew in Databricks, explained</title>
      <link>https://bricksnotes.com/blog/databricks-data-skew-slow-tasks</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-data-skew-slow-tasks</guid>
      <pubDate>Sun, 23 Aug 2026 03:34:15 GMT</pubDate>
      <dc:creator>BricksNotes</dc:creator>
      <description>The code did not change. The data did. Here is how one heavy key turns a nine minute job into a fifty one minute one, and how to fix it.</description>
      <category>Databricks</category>
      <category>Spark</category>
      <category>Performance</category>
      <category>Joins</category>
    </item>
    <item>
      <title>CSV, JSON, Parquet, and Delta: which one should you use?</title>
      <link>https://bricksnotes.com/blog/csv-json-parquet-delta-which-format-to-use</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/csv-json-parquet-delta-which-format-to-use</guid>
      <pubDate>Sat, 22 Aug 2026 15:16:16 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>CSV, JSON, Parquet, or Delta? A practical comparison with runnable Databricks Free Edition examples, real size and speed differences, and a simple rule for each layer of your pipeline.</description>
      <category>Delta Lake</category>
      <category>Parquet</category>
      <category>File Formats</category>
      <category>Data Engineering</category>
    </item>
    <item>
      <title>How BricksNotes went from 40,000 to 100,000 learners</title>
      <link>https://bricksnotes.com/blog/bricksnotes-40000-to-100000-learners</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/bricksnotes-40000-to-100000-learners</guid>
      <pubDate>Fri, 21 Aug 2026 23:57:32 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A hundred thousand data professionals have now learned with BricksNotes. Here is the honest story of how it happened, what we built along the way, and why we are not stopping.</description>
      <category>Community</category>
      <category>Milestone</category>
      <category>Data Engineering</category>
      <category>2026</category>
    </item>
    <item>
      <title>The pipeline was green. The numbers were wrong.</title>
      <link>https://bricksnotes.com/blog/databricks-data-quality-checks</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-data-quality-checks</guid>
      <pubDate>Fri, 21 Aug 2026 02:21:49 GMT</pubDate>
      <dc:creator>BricksNotes Editorial</dc:creator>
      <description>A successful run tells you the code finished, not that the data is right. How to write quality rules, decide what happens to bad rows, and enforce them with Delta constraints and pipeline expectations.</description>
      <category>Databricks</category>
      <category>Data Quality</category>
      <category>Delta Lake</category>
      <category>Pipelines</category>
    </item>
    <item>
      <title>I built a data engineering project in two evenings. Here is exactly what I did</title>
      <link>https://bricksnotes.com/blog/built-first-data-engineering-project-two-evenings</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/built-first-data-engineering-project-two-evenings</guid>
      <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>
    </item>
    <item>
      <title>The event arrived two days late. How to handle late data in Databricks</title>
      <link>https://bricksnotes.com/blog/databricks-late-arriving-data</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-late-arriving-data</guid>
      <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>
      <link>https://bricksnotes.com/blog/databricks-backfill-without-breaking-downstream</link>
      <guid isPermaLink="true">https://bricksnotes.com/blog/databricks-backfill-without-breaking-downstream</guid>
      <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>
      <guid isPermaLink="true">https://bricksnotes.com/blog/agent-discovers-agent-applies</guid>
      <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>
      <guid isPermaLink="true">https://bricksnotes.com/blog/schema-evolution-databricks-pipelines</guid>
      <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>
      <guid isPermaLink="true">https://bricksnotes.com/blog/how-to-become-ai-data-engineer-with-bricksnotes</guid>
      <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>
      <guid isPermaLink="true">https://bricksnotes.com/blog/auto-loader-vs-copy-into-databricks</guid>
      <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>
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      <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>
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      <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>
      <guid isPermaLink="true">https://bricksnotes.com/blog/innovation-data-ai-people-together</guid>
      <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>
    </item>
    <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>
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      <category>data-and-ai</category>
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