# GeekInData

> Architect notes on Microsoft Fabric, Microsoft Foundry agents, Databricks, and Power Platform.
> Practical trade-offs, failure modes, and decisions that hold up in production - not starter tutorials.

Site: https://www.geekindata.com
Author: Sai Prudhvi Neelakantam - https://www.geekindata.com/authors/sai-prudhvi
LinkedIn: https://www.linkedin.com/in/saiprudhvineelakantam/
RSS: https://www.geekindata.com/blog/rss.xml
Sitemap: https://www.geekindata.com/sitemap.xml

## What this site is
- Short architect-level posts from real Fabric / Azure agent / Databricks work
- Topic hubs for Case Studies, Toolkits, and Experiments
- Series hubs for lakehouse architecture, enterprise agent apps, and analytics readiness

## What this site is not
- A vendor docs mirror or certification dump
- Guaranteed SEO ranking advice or automated LinkedIn posting

## Primary pages
- Home: https://www.geekindata.com/
- Blog: https://www.geekindata.com/blog
- Archive: https://www.geekindata.com/archive
- Authors: https://www.geekindata.com/authors/sai-prudhvi
- Search: https://www.geekindata.com/search?q={query}
- Answers: https://www.geekindata.com/answers
- Post graph: https://www.geekindata.com/graph
- Glossary: https://www.geekindata.com/glossary
- Pattern lab: https://www.geekindata.com/lab
- Decision wizard: https://www.geekindata.com/decide
- Developers / posts API: https://www.geekindata.com/developers
- posts.json: https://www.geekindata.com/api/posts.json

## Topic hubs
- Case Studies: https://www.geekindata.com/topics/case-studies
- Toolkits: https://www.geekindata.com/topics/toolkits
- Experiments: https://www.geekindata.com/topics/experiments

## Series hubs
- Fabric lakehouse architecture: https://www.geekindata.com/series/fabric-lakehouse-architecture
- Enterprise agent apps: https://www.geekindata.com/series/enterprise-agent-apps
- Analytics readiness: https://www.geekindata.com/series/analytics-readiness

## Common topics
Microsoft Fabric, lakehouse topology, Direct Lake, semantic models, Fabric CI/CD, Microsoft Foundry agent apps, entitlements and RBAC, Databricks Genie readiness, Power Platform at platform scale, white-label agent shells.

## Recent posts (high signal)
- https://www.geekindata.com/blog/44-fabric-workspace-naming-hygiene - Workspace naming hygiene and operational tax
- https://www.geekindata.com/blog/42-large-fact-refresh-drift - Large fact refresh drift contracts
- https://www.geekindata.com/blog/41-mlv-nee-fallback-truth - MLV native-execution fallback truth
- https://www.geekindata.com/blog/40-fabric-monitor-runbooks - Fabric monitor runbooks
- https://www.geekindata.com/blog/39-native-ci-linters-language-gates - Native CI linters and language gates
- https://www.geekindata.com/blog/38-secure-proxy-ai-shells - Secure proxies in front of AI shells
- https://www.geekindata.com/blog/12-poc-public-vs-mvp-private-agent-apps - Public PoC vs private MVP agent apps
- https://www.geekindata.com/blog/8-one-lakehouse-schemas-vs-many - One lakehouse with schemas vs many

## Optional full feed
- Full AI answer map: https://www.geekindata.com/llms-full.txt
- Atom: https://www.geekindata.com/blog/atom.xml