Atlan for SAP: Ground Your Agents in the System of Record

● Generally Available

This release turns SAP's notoriously opaque data into a governed, machine-readable context layer for AI. SAP is the system of record for most large enterprises — and the hardest source to ground agents in, thanks to cryptic tables, coded field names, and configuration-driven logic. SAP ECC and SAP S/4HANA are now GA with two new capabilities that give agents (and the people who supervise them) two things they've never had over SAP: provenance — where a number truly comes from — and a map of the human layer, where SAP data is actually created and consumed.

CDS View Column-Level Lineage

Provenance

What's new: Column-level lineage is now generally available for SAP CDS (Core Data Services) views. Trace every column in a CDS view back through its transformations to the exact source table columns that feed it.

What you can do:

• Follow a single field end to end, from the semantic CDS layer down to the underlying SAP table columns.
• Run precise impact analysis — see exactly what breaks downstream if a source field changes.
• Debug and validate at the column, not just the object, level.

Why it matters for agents: This is the provenance backbone of the context layer. When an AI agent surfaces a metric, it can cite the precise origin and transformation path of every value — making the output auditable and trustworthy, and letting governance and quality signals propagate accurately across the SAP estate.

Fiori Apps as a New Asset Type

The Human Layer · First to market for Atlan

What's new: SAP Fiori apps are now a native asset type in Atlan, with asset-level lineage from Fiori apps → CDS views → upstream SAP tables.

The problem this solves: Fiori is the modern SAP UI — where business users actually work, reading, entering, and changing data every day, with near-zero visibility into the data beneath the screen. This release connects the app the user sees to the data it actually touches.

What you can do:

• See, for any Fiori app, the chain of CDS views and source tables it draws from.
• Give business users and stewards a clear map from the interface to the underlying data.
• Trace where sensitive or business-critical data is exposed and modified at the point of use.

Why it matters for agents: Fiori is the human layer of the context graph — where data is created and consumed. Mapping it lets an AI agent understand what an app does in data terms, and lets governance follow data all the way to the screen.

On the roadmap: column-level lineage for Fiori apps · popularity & usage signals for Fiori apps.

What's Next

Next: SAP Business Data Cloud (BDC). Zero-copy data sharing across Snowflake, SAP Databricks, Google BigQuery, and Microsoft Fabric. Context that follows your data across platforms without ever moving or duplicating it — so lineage, meaning, and governance stay intact wherever SAP data is consumed. Connectors for SAP Datasphere and SAP Analytics cloud, complementing our ERP and BW connectors.

More context ingestion from the SAP ecosystem, coming soon:

• Field-level help text as glossaries — SAP's own field documentation, automatically converted into governed business glossary terms and linked to the exact columns they define. The semantic layer that gives agents authoritative meaning for every SAP field.
• Master data as data products — your unique SAP configuration, packaged into governed data products: material types, customer and vendor account groups, and Business Partner groupings, roles, and categories. Context that reflects how your enterprise actually classifies its master data.
• SAP long text as knowledge files — SAP's free-text long texts (notes, descriptions, and documentation) harvested and published as knowledge files, ready to ground agents — for retrieval in agent studios and RAG workflows.

Beyond that — context from across the SAP application landscape (actively working with customers on outcomes and use cases for the below):

• SAP Signavio — business process context (how work actually flows).
• LeanIX — enterprise architecture and application portfolio context.
• SAP IBP — integrated business planning and supply chain context.
• SAP Concur — travel, expense, and spend context.
• SAP SuccessFactors — people and HR context.

The Bigger Picture: SAP + the Leading Non-SAP Context Layer

Pair the deepest context layer for SAP with the leading context layer for everything outside it — cloud warehouses, lakehouses, BI, transformation, and AI tooling — and the whole enterprise becomes legible to AI in ways neither side can deliver alone. An agent can trace a metric from a BI dashboard, through the cloud warehouse, across a zero-copy SAP share, into the CDS view and its source table — with provenance at every hop.

The estate is opening. The connective tissue is here. The result is a single, trustworthy map of how the business really runs — and the foundation for enterprise AI you can actually rely on.

🎉 What's new

Snowflake semantic views are now cataloged directly into Atlan as an open context layer home for the metric definitions that Cortex Analyst, Talk-to-Data and more agents depend on.

Atlan ingests the full hierarchy: the semantic view plus its logical tables, dimensions, facts, and metrics as discoverable, governable assets.

Because these views are the same objects Cortex Analyst runs on, cataloging them closes the gap between your governed metric definitions and the agents querying them.

And Atlan Context Studio lets you build and deploy new agents and semantic views from Atlan with the context they for agents that return accurate, governed answers

✨ Let's dig deeper

Here's what this looks like in practice and how it connects to Context Studio.

• Search for any semantic view and open its asset profile to see its logical tables, dimensions, facts, and metrics in one place.
• Feed these cataloged views directly into Context Studio, where they act as the primary execution surface. Context Studio either attaches to an existing semantic view or generates and updates its definition, with Atlan staying the source of truth.
• Apply the same governance you use elsewhere, like certification, ownership, README, and tags, to make a view trusted before it powers a production agent.
• Note: if your crawler role lacks the required grants, semantic views are skipped without failing the workflow, so an existing crawl won't break.

👏 Give it a shot

To start using semantic views:

1. Check the Snowflake permissions on your Atlan<>Snowflake connection
2. Run or schedule a metadata sync for your Snowflake connection.
3. Use global search and filter by asset type → Semantic view.
4. Open a semantic view to explore its Entities, Relationships, and Metrics tabs.
5. From there, point a Context Studio context product at the view to power an AI analyst.

📘 Full setup guide here. 

Finally, if you are at Snowflake Summit this week, come say hello and learn more about Snowflake+Atlan together!

🎉 What's new

Introducing Knowledge Folders and Knowledge Files to close the gap between your structured data context and the procedural knowledge that actually governs how your business works.

Before this, your SOPs, policies, and compliance docs lived scattered across SharePoint, Confluence, and Google Drive, invisible to agents at the point of use. 

Now you can upload the definitive versions directly into Atlan as governed, first-class catalog assets. 

A Knowledge Folder is a domain-scoped container (e.g., "Finance SOPs"). 

A Knowledge File is the individual document inside it. 

Context agents process each file automatically, extracting glossary terms, attaching business rules, and generating skill files with full lineage back to the source. 

That output flows into Context Repos via Context Engineering Studio, making your unstructured knowledge available to your MCP-connected agents, Atlan's native conversational search, and anything you deploy downstream.

Consider a customer support agent. It knows the order schema, the churn model, the interaction history. But it guesses when a VIP customer asks about a refund outside standard policy because none of the escalation path, the tier-specific SLA, the product defect window live in a database. They live in a PDF or shared doc.

Upload that PDF as a Knowledge File. Context agents extract the rules and make them available downstream. Now the answer is grounded and cites the source.

✨ Let's dig deeper

• Upload once, governed forever: Drag and drop your PDF or Markdown files into a Knowledge Folder. They become searchable catalog assets with lineage, metadata, and access control.
• Context agents extract automatically: After upload, context agents process knowledge files and synthesize glossary terms, business rules, and skills. Everything traces back to the source document.
• Flows into your Context Repos: Extracted knowledge becomes available via Context Engineering Studio. It feeds your Context Repos, conversational search, and any MCP-connected agent downstream.
• You decide what governs agent behavior: You choose which document is the definitive version. Nothing governs agents without your sign-off.

👏 Give it a shot

If your team has SOPs, policy docs, or compliance guidelines that your AI agents should know about, this is where to start.

Click + New > Knowledge Folder from the top right of Atlan. Create or select a folder, drag and drop your PDF or Markdown files, and upload. Open any file's profile page to preview content, review extracted terms, and trace lineage to downstream skill files and context repos.

Admin access is required to upload; all roles can preview and search

See more at Knowledge Folders | Context Engineering Studio

🎉 What’s New
Atlan now supports SAP HANA User Defined Functions (UDFs) as first-class assets.  There are two different kinds of user-defined functions (UDF) in SAP HANA: Table User-Defined Functions and Scalar User-Defined Functions.

✨ What’s in Store

• UDFs can be searched, discovered, and enriched with business context for stronger governance.

In the future, UDFs will also have lineage support for use in calculation views and other SAP HANA assets.

👏 Give it a Shot
Start exploring SAP HANA in Atlan today — and let us know what you think!

📘 Learn More

• What does Atlan crawl from SAP HANA?

We’re thrilled to announce that Atlan’s SAP ECC and SAP S/4HANA connectors are now live in Public Preview!

This marks a major milestone in our mission to bring deep metadata discovery, lineage, and governance to the SAP ecosystem — helping enterprises unlock visibility into their most complex, business-critical systems.

Why This Matters

End-to-End SAP Metadata Discovery and Governance
Atlan now natively connects to SAP ECC and SAP S/4HANA to extract comprehensive metadata directly from the application layer — including Components, TCODES, Function Modules, ABAP Programs, application components, tables, views, fields, check tables, CDS views and the relationships between them. This allows teams to understand the “what” behind their SAP Components like FI, LO, MM, SD and CO and how the data flows and is consumed within the modern data stack.

New Features from PrPr Release

Column-Level Check Table Relationships
The connector now automatically discovers column-level check table relationships, enabling precise data lineage and semantic context. 

Application Component Hierarchy
We’ve added Application Component Hierarchy relationships — allowing automatic discovery of related SAP tables, fields, and data objects by business domain or component (FI, MM, SD, LO, PP, PM, etc.).
These hierarchies can now be leveraged to build rich business semantic Data Products in Atlan that align directly with SAP’s organizational structure, driving cleaner discovery and business alignment.  If interested in more automation around this please contact your Atlan account representative.  

This helps users discover and connect transactional and master data across key SAP for use as data products such as:

• Business Partners
• Customer & Vendor Master
• Material Master
• Sales & Purchase Orders
• Work Centers
• G/L Accounts
• Profit Centers
• Maintenance Plans
  …and more.

Smarter Metadata Scoping

New flexibility lets users filter the SAP metadata extraction scope by:

• Application Component(s) – focus on only the modules relevant to your use case (e.g., FI, SD, MM).
• Atlan Asset Types – choose which metadata objects (tables, function modules, Programs, TCODEs, views) to include or exclude based on business requirements.

This enables faster, more targeted metadata ingestion and reduces noise across massive SAP landscapes.

 What’s Next

This Public Preview is just the start of Atlan’s journey in the SAP ecosystem.
Coming soon on our roadmap:

• SAP Business Data Cloud
• SAP BW on HANA
• SAP BW/4HANA
• SAP Datasphere
• SAP Analytics Cloud
• SAP Business Objects

Together, these will provide an end-to-end metadata lineage bridge across SAP’s legacy and modern data SAP Business Data Cloud ecosystems — from SAP to cloud analytics and beyond.

Interested in early access or upcoming connectors?
Reach out to your Atlan Account Representative to learn more or join the next preview cohort.

📘 Learn More

• SAP ECC
• SAP S/4HANA

🎉 What’s New
Atlan now supports BigQuery Routines — Stored Procedures, Table Functions, and UDFs — as first-class assets.

✨ What’s in Store

• Routines can be searched, discovered, and enriched with business context for stronger governance.
• In lineage, routines appear as related assets within the lineage tab — keeping views compact and table-centric while still showing where routines are used.

👏 Give it a Shot
Start exploring BigQuery Routines in Atlan today — and let us know what you think!

📘 Learn More

• What does Atlan crawl from Google BigQuery?
• Routines and Process assets

🎉 What’s new
Atlan now supports Databricks Struct datatypes, giving you complete visibility into nested fields for the first time.

✨ What’s in Store

• Explore Struct fields with an interactive tree view—expand & collapse for clear visualization.
• Seamlessly navigate Structs just like simple columns.
• Full metadata context now available for all Struct fields.

👏 Give it a shot

Start exploring Databricks Struct fields in Atlan today — and let us know what you think!

📘 Learn More

• What does Atlan crawl from Databricks?

🎉 What's new

Domains are now discoverable directly from the assets page in Atlan! No matter how a user navigates—whether through assets, products, or search—they’ll now encounter domains as a first-class entity, making domain discovery seamless across the board.

✨ Let's dig deeper

Previously, discovering domains depended on navigating through specific UI paths like the domain browser or the products section. With this update, domains are now fully integrated into the asset search experience.

Here’s what’s new:

• Domains now appear in global asset search results
  You'll find them listed just like tables, views, and products—with a new domain-specific badge.
• Searchable, filterable, and ranked
  Domains come with relevance-based ranking and can be filtered using the asset type selector.
• Complete visibility
  Domain metadata—like name, description, and associated assets and products—can now be previewed from the asset results.

This means that no matter where users begin—searching for a product, asset, or table—they can discover and navigate to the relevant domain effortlessly.

Why this matters: This boosts discoverability, enables better context-switching, and helps users connect data assets to business concepts in just a few clicks.

👏 Give it a shot

Try searching from the global assets page and see how Domains now surface as part of your everyday discovery journey. Whether you’re starting with a table, a product, or just exploring—your domains are now right there with you!

🎉 What’s New

This release brings a powerful set of upgrades to Atlan's Tableau integration, helping you unlock deeper insights, richer lineage, and greater control over metadata workflows:

✨ Let’s Dig Deeper

• Embedded Dashboard Discovery: Discover embedded Tableau dashboards as first-class assets. Understand how they’re connected to upstream data and where they’re being used.
• End-to-End Column Lineage: Column-level lineage now spans from your Tableau DataSources through Worksheets and into Dashboards, offering a complete picture for impact analysis, troubleshooting, and trust.
• Smarter Custom SQL Lineage: We now detect tables even within nested subqueries, providing a deeper understanding of your Tableau logic and ensuring your lineage graphs are accurate and complete.
• Hierarchical Filters for Playbooks: New hierarchical filtering in playbooks means less manual work:
  • Select a full folder to auto-include all assets inside it
  • Or zoom in on specific sub-folders when needed
  • Great for keeping automation organized and scalable
• Secure Agent Support: Need to connect to a Tableau server behind a firewall or in an on-prem environment? Atlan Secure Agent makes it possible, ensuring secure, seamless metadata extraction without exposing internal systems.
• Seamless Metadata Access in Tableau: Stay in flow: now you can access column descriptions, owners, and data classifications directly within Tableau, embedded into your dashboards and sources. Just click, no tab switching required.

👏 Give It a Shot

Learn more and let us know what you think!

• Tableau Lineage
• Custom SQL
• Troubleshooting Tableau connectivity