# Analytixus - The Analytics-DRUID

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## Sitemaps

- [XML Sitemap](https://analytixus.de/sitemap.xml): Contains all public & indexable URLs for this website.

## Posts

- [Blog](https://analytixus.de/blog/)
- [When AI Doesn't Just Write, but Gets Validated: The Analytixus MCP Server in Practice](https://analytixus.de/2026/07/13/when-ai-doesnt-just-write-but-gets-validated-the-analytixus-mcp-server-in-practice/): Most AI demos I see follow the same pattern: a model writes text or code, a human reads it, and whether it actually holds up only shows later, at compile time, at deployment, in the worst case in production. What has kept me thinking about the Model Context Protocol (MCP) for months is the chance
- [Code Generation in Analytixus with Python and Jinja2: A Practical, Scalable Pattern](https://analytixus.de/2025/11/29/code-generation-in-analytixus-with-python-and-jinja2-a-practical-scalable-pattern/): Audience: Analytixus users and Data Engineers This article demonstrates how to generate SQL code from metadata in Analytixus using Python and Jinja2. We use a simple, understandable example (a CREATE TABLE statement) to show the pattern clearly. In real projects, you will modularize and extend this approach for more artifacts (views, DDL migrations, MERGE statements,
- [DnAML (Data and Analytics Markup Language): A Practical Guide for Analytixus](https://analytixus.de/2025/10/19/dnaml-data-and-analytics-markup-language-a-practical-guide-for-analytixus/): DnAML (Data and Analytics Markup Language) is a compact, JSON-like DSL for modeling data sources, structures, lineage, and relationships across analytics pipelines. It centralizes metadata—defining tables/views, column semantics, origins (UNION/JOIN), and references—while supporting domain organization (e.g., Bronze/Silver/Gold) and automation (DDL, pipelines, validations). By transforming unsupervised metadata into curated models, DnAML enables readable, versionable, and machine-actionable analytics workflows.
- [Lean Data Vault: A Pragmatic Approach to Data Modeling in the Lakehouse](https://analytixus.de/2025/09/18/lean-data-vault-a-pragmatic-approach-to-data-modeling-in-the-lakehouse/): Every data and analytics project (data lakehouse) needs a framework with best practices. This one is definitely worth reading if you're looking for a data modeling approach that doesn't overcomplicate things, focuses on data quality, and supports massive parallel processing. Ping back: https://andyloewen.de/2025/09/17/lean-data-vault-a-pragmatic-approach-to-data-modeling-in-the-lakehouse/
- [Enriching Metadata from Code Comments in Analytixus](https://analytixus.de/2025/09/18/enriching-metadata-from-code-comments-in-analytixus/): In modern Data & Analytics projects, metadata is the backbone of automation and governance. Most of the time, we can derive structural metadata directly from the code — for example, by parsing SQL CREATE TABLE statements into XML-based models. But sometimes, SQL alone isn’t enough. There are attributes we want to capture — like IsBusinessKey, IsTechnical, or History Flags — that cannot be expressed syntactically in the DDL. This is where code comments come into play. In Analytixus, we use comments as metadata carriers. During the build process, they are extracted, transformed, and converted into actionable metadata.

## Pages

- [Home](https://analytixus.de/): Analytixus - The Analytics-DRUID - Metadata - Analytics #separator_saCode Generator - XSLT - XML - Databricks - Microsoft Fabric - Azure - SQL - Python - Metadata driven framework -
- [Get started](https://analytixus.de/getstarted/): Get Started with Analytixus Follow these steps to set up Analytixus on your system and start accelerating your data projects. Install prerequisites Download and install the .NET Core 8 Runtime Framework. Download Analytixus Get the latest release from our Download page as a ZIP file.Extract it into a folder of your choice, for example:C:\Analytixus\App Set
- [Legal Notice](https://analytixus.de/legal-notice/): Impressum Angaben gemäß § 5 TMG Name:Andy LöwenHeesen 6027318 HilgermissenDeutschland Kontakt:E-Mail: info@analytixus.de Haftung für InhalteAls privater Betreiber dieser Website bin ich gemäß § 7 Abs.1 TMG für eigene Inhalte verantwortlich. Für die Richtigkeit, Vollständigkeit und Aktualität der Inhalte kann jedoch keine Gewähr übernommen werden. Haftung für LinksDiese Website enthält Links zu externen Webseiten Dritter, auf

## Templates

- [Lean Data-Vault for Databricks](https://analytixus.de/analytixus-template/lean-data-vault-for-databricks/): Data Vault is a proven methodology for building scalable, auditable data platforms. I consider myself a fundamental advocate of Data Vault – its concepts of hubs, satellites, and links provide a solid foundation for traceability and parallelization. However, in real-world projects, I often experienced that the full methodology was too heavy for organizations to adopt
- [Lean Data-Vault for Databricks complete sample](https://analytixus.de/analytixus-template/lean-data-vault-for-databricks-complete-sample/): Data Vault is a proven methodology for building scalable, auditable data platforms. I consider myself a fundamental advocate of Data Vault – its concepts of hubs, satellites, and links provide a solid foundation for traceability and parallelization. However, in real-world projects, I often experienced that the full methodology was too heavy for organizations to adopt

## Downloads

- [Analytixus-App](https://analytixus.de/download/109/?tmstv=1791142834): Short description
- [Analytixus-App-Dev](https://analytixus.de/download/373/?tmstv=1791142834): Short description
- [Lean-Data-Vault for Databricks complete sample](https://analytixus.de/download/420/?tmstv=1791142834)
- [Lean-Data-Vault for Databricks](https://analytixus.de/download/416/?tmstv=1791142834)

## Categories

- [DnAML](https://analytixus.de/category/dnaml/)
- [supervised / unsupervised Metadata](https://analytixus.de/category/supervised-unsupervised-metadata/)
- [XSLT](https://analytixus.de/category/xslt/)
- [Framework](https://analytixus.de/category/framework/)
- [Python](https://analytixus.de/category/python/)

## Tags

- [Python](https://analytixus.de/tag/python/)
- [Jinja2](https://analytixus.de/tag/jinja2/)
- [Code-Generation](https://analytixus.de/tag/code-generation/)

## Download Categories

- [Analytixus](https://analytixus.de/?dlm_download_category=analytixus)
- [Free-Analytixus](https://analytixus.de/?dlm_download_category=freeanalytixus)
- [Dev-Analytixus](https://analytixus.de/?dlm_download_category=devanalytixus)
- [Templates](https://analytixus.de/?dlm_download_category=templates)