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Blog Post
Oct 7, 2026 • 7 min read Databricks Apps

Databricks-Native MDM: Introducing Golden Lake for Entity Resolution

Golden Lake is Entrada’s Databricks-native MDM and entity resolution accelerator, built to resolve your most valuable entities without ever moving data out of Unity Catalog. Master Data Management (MDM) is a constant…

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Blog Post
Sep 9, 2026 • 16 min read AI + ML

Databricks Semantic Layer: 10 Proven AI Agent Practices

Best practices for Databricks semantic layers, ontologies, and Unity Catalog glossaries.

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Blog Post
Aug 27, 2026 • 7 min read AI + ML

The Future of AI Platforms: Where Databricks Fits

AI platforms are converging and fragmenting at the same time. A practitioner's map of the modern AI stack - and where Databricks genuinely fits.

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Blog Post
Aug 27, 2026 • 7 min read AI + ML

The Architecture Tax: Why Your ML Models Cost More Than They Should

Poor ML architecture quietly drains budgets through retraining churn, drift, and shadow infrastructure. Here's how to spot and fix it on Databricks.

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Blog Post
Jul 31, 2026 • 7 min read Databricks Apps

Genie App Builder: Fast, Governed AI Apps on Databricks

Vibe-coding promises a working app in hours, but most of those apps hit the same wall: they're disconnected from real business data, ungoverned, and expensive to run. Databricks' new Genie App Builder,…

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Blog Post
Jul 24, 2026 • 22 min read Data Governance

Beyond Autocomplete: How Databricks Genie Code Turns Data Work into Governed Agentic Workflows

Most AI coding assistants treat code as the end product. In data platforms, code is just the interface, and Genie Code's real advantage is reasoning across the governed tables, lineage, and pipelines…

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Blog Post
Jul 13, 2026 • 8 min read AI + ML

Databricks Genie vs Power BI and Tableau: Should You Add It, Replace, or Ignore?

Every conversation with a CIO this year ends the same way: "Do we still need Power BI if we have Databricks Genie?" The honest answer is more interesting than yes or no.…

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Blog Post
Jul 9, 2026 • 13 min read AI + ML

Why Your Databricks ML Pipelines Are Burning Cash (And How to Fix Them)

Most Databricks ML pipelines do not fail because the math is wrong. They fail because performance decisions made early quietly compound until cost, latency, and trust all start slipping at once.

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Blog Post
Jun 26, 2026 • 5 min read Announcements

Entering the Agent Era: Data + AI Summit 2026 Reflection

Data + AI Summit 2026 brought the Entrada team back to San Francisco alongside more than 31,000 members of the data and AI community. As a pure-play Databricks partner, being there felt…

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