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og:description: A promotional FAQ-style page from Decube covering data governance topics relevant to regulated financial services, particularly OJK compliance in Indonesia....
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# The 2 AM Spreadsheet: Why OJK Compliance Is Breaking Indonesia's Data Governance Teams, and What Fixes It

**[Decube](https://daily.dev/sources/decuberss)** · 19 min read · 0 upvotes · 0 comments

## Summary

A promotional FAQ-style page from Decube covering data governance topics relevant to regulated financial services, particularly OJK compliance in Indonesia. Topics include data lineage, data catalogs, metadata management, data observability, context engineering for AI agents, and comparisons with competitors like Atlan and Alation. Decube is positioned as a purpose-built alternative for regulated environments in Southeast Asia (MAS, OJK, BNM, APRA), with features like PII auto-classification, approval-gated lineage, and an AI layer that avoids routing metadata to public LLMs.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.decube.io/post/why-ojk-compliance-is-breaking-indonesias-data-governance-teams-and-how-decube-fixes-it>

## Questions this post answers

### What is the difference between a semantic layer and a context layer in data architecture?

A semantic layer standardizes how metrics are defined and calculated so every analyst and BI tool uses the same numbers. A context layer encodes governance rules, data lineage, quality signals, and organizational knowledge so AI agents can make safe, autonomous decisions. The semantic layer serves human-facing analytics; the context layer serves AI-facing autonomy.

_Teams building agentic AI on enterprise data track this distinction on daily.dev._

### How is MCP different from RAG for AI data access?

MCP (Model Context Protocol) enables live, interactive tool execution and bidirectional context exchange between AI agents and external systems, whereas RAG retrieves documents for LLM consumption. MCP is more dynamic and context-aware, allowing agents to call tools and access APIs in real time rather than just retrieving static document chunks.

_Developers choosing between MCP and RAG for AI workflows find the latest comparisons on daily.dev._

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---

Tags: [#big-data](https://daily.dev/tags/big-data), [#data-engineering](https://daily.dev/tags/data-engineering), [#regulatory-compliance](https://daily.dev/tags/regulatory-compliance), [#data-observability](https://daily.dev/tags/data-observability)

[View this post on daily.dev](https://daily.dev/posts/the-2-am-spreadsheet-why-ojk-compliance-is-breaking-indonesia-s-data-governance-teams-and-what-fix-rxsr7kmzi)

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