<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Data Vault on tonshel</title>
    <link>https://blog-5fa.pages.dev/tags/data-vault/</link>
    <description>Recent content in Data Vault on tonshel</description>
    <generator>Hugo -- gohugo.io</generator>
    <language>en-us</language>
    
    
    
    <lastBuildDate>Mon, 04 May 2026 18:00:55 +0000</lastBuildDate>
    <atom:link href="https://blog-5fa.pages.dev/tags/data-vault/index.xml" rel="self" type="application/rss&#43;xml" />
    
    <item>
      <title>Data Vault 2.0 with dbt: Patterns That Scale in Team Settings</title>
      <link>https://blog-5fa.pages.dev/posts/data-vault-dbt-patterns-team-scale/</link>
      <pubDate>Mon, 04 May 2026 18:00:55 +0000</pubDate>
      <guid>https://blog-5fa.pages.dev/posts/data-vault-dbt-patterns-team-scale/</guid>
      <description>In team-based Data Vault 2.0 pipelines, predictability beats cleverness — five concrete patterns around quality gates, standardized transformations, column discipline, explicit CTEs, and debuggable tests will save your team hours of downstream investigation. Covers: why predictability beats cleverness in data vault pipelines, pattern 1: quality gates at ingestion with three-tier expectations, pattern 2: standardized hash-key and staging transformations, pattern 3: column discipline — explicit lists over select *. Tags: data engineering, dbt, data vault, snowflake, data quality, team patterns, automate_dv.</description>
    </item>
    
  </channel>
</rss>