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Accelerate agentic planning with trusted data productsAccelerate agentic planning with trusted data productsGoverned data products as the ground for AI planning in SAP Analytics Cloud: using a ready data product or building one in SAP Business Data Cloud, the cataloguing and lineage concern, then agentic AI automating planning tasks and producing insights on top. The abstract names the two products and the data product step and does not say which planning tasks the agents take over. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Jie Deng, Maximilian Paul Gander and Richard Mooney, written here from SAP's abstract; the recording is not yet published.
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Federated Machine Learning with SAP DatasphereFederated Machine Learning with SAP DatasphereSAP's design for training predictive models on an external machine learning platform against SAP Datasphere data that is not replicated to that platform. The open-source FedML Python library runs in the platform's notebook, connects to Datasphere over Python/SQLDBC and reads the analytic models in which Datasphere unifies SAP and non-SAP sources; a trained model can then be deployed to SAP AI Core, or in several sub-pages to SAP BTP, Kyma runtime, which is the predictive models path where training happens outside SAP. Sub-pages cover Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Databricks, NVIDIA RAPIDS on GPUs and IBM watsonx.published 2025-01-23
Transform business data into AI-supported insightsTransform business data into AI-supported insightsBusiness metrics turned into insights, narratives and recommendations by SAP Joule's agents, with People Intelligence, the SAP Snowflake solution extension for SAP Business Data Cloud and SAP Analytics Cloud connected in SAP Business Data Cloud. The abstract names what is connected and what comes out, and does not say what the exercise builds or where the Snowflake extension sits in it; People Intelligence and the extension are not atlas entries. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Babacar Toure, Maximilian Paul Gander, Neetha Pucknat and San Tran, written here from SAP's abstract; the recording is not yet published.
E2E: SAP Cloud Platform Internet of Things to SAP Analytics CloudE2E: SAP Cloud Platform Internet of Things to SAP Analytics CloudDevice data from ingestion to chart, with CAP occupying the middle: a CDS-defined persistence on HANA Cloud, and an OData service published from it for Analytics Cloud to consume live. The interesting choice is that CAP is used for the model rather than for business logic — there is barely any.Gunter, published 2020-08-31
Predictive Asset Insights embedded Live analytics using CAP and SACPredictive Asset Insights embedded Live analytics using CAP and SACCAP as the layer between a line-of-business application's data and a live Analytics Cloud story embedded back into it — master data and operational data both. Structured as ten steps, which keeps it honest about how much of this is configuration rather than modelling.Saif, published 2021-07-18
SAP Data and Analytics Showcase – Use SAP Cloud Application Programming Model to Develop a Machine Learning Application on SAP BTPSAP Data and Analytics Showcase – Use SAP Cloud Application Programming Model to Develop a Machine Learning Application on SAP BTPThe instalment where the showcase becomes code: the CAP application built in Business Application Studio, and the sub-scenario it covers implemented step by step. The overview post is the one that says why this piece exists at all.former_member10846, published 2022-08-12
SAP Incentive Management - Understanding of CSN file & CLI Command to generateSAP Incentive Management - Understanding of CSN file & CLI Command to generateCSN met from the far end: not as CAP's compiled model but as the interchange format a product hands to Analytics Cloud so a story knows the shape of the data. Explains what CSN is, why the format matters here, and the command that produces one.Yogananda, published 2024-11-19
Consume SAP Document Management using @cap-js/sdm pluginConsume SAP Document Management using @cap-js/sdm pluginStoring attachments in a SAP Document Management repository from a CAP application, using the official plugin. The point the post makes about the plugin is that it brings its own UI: a user attaches any number of documents and one Save writes them all to the repository, so the application does not build an upload surface of its own.published 2024-08-26
Media Handling in SAP CAPM – Backend and Frontend ImplementationMedia Handling in SAP CAPM – Backend and Frontend ImplementationFiles against a record with the front end included, which most of the attachments writing here leaves out — the entity that stores the content, the custom logic around it, and then the UI5 side that uploads and retrieves. End to end rather than one half.published 2026-03-02
Unlocking Efficiency: Leveraging SAP BTP Document Management Service in Fiori Applications # 2Unlocking Efficiency: Leveraging SAP BTP Document Management Service in Fiori Applications # 2Document Management's own Attachment Reuse UI dropped into a Fiori elements List Report, in two variants — OData V2, and OData V4 in a CAP application. The CAP half is one of the two scenarios rather than the subject; the rest of the series is about custom Fiori apps and a process task UI, with no CAP in them.published 2024-12-10
Use SAP Document Management Service Plugin In CAP NODEJS Step by Step GuidanceUse SAP Document Management Service Plugin In CAP NODEJS Step by Step GuidanceThe official plugin is documented in capire; this is somebody who set it up anyway and wrote down where it went wrong. The author says as much — the point is to spare customers the troubles, so the value is in the order of the steps and the prerequisites, not in the API.Jacky_Liu1, published 2025-03-06
Accelerate agentic planning with trusted data productsAccelerate agentic planning with trusted data productsGoverned data products as the ground for AI planning in SAP Analytics Cloud: using a ready data product or building one in SAP Business Data Cloud, the cataloguing and lineage concern, then agentic AI automating planning tasks and producing insights on top. The abstract names the two products and the data product step and does not say which planning tasks the agents take over. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Jie Deng, Maximilian Paul Gander and Richard Mooney, written here from SAP's abstract; the recording is not yet published.
Building custom Joule Agents with SAP Knowledge GraphBuilding custom Joule Agents with SAP Knowledge GraphCustom Joule Agents built in a hands-on with SAP Knowledge Graph and Joule Studio: discovering APIs from a user's intent, grounding an agent's answers in business context, and integrating data products for SAP Business Data Cloud. The agents are SAP Joule's; the Knowledge Graph is not an atlas entry, and the abstract does not say which Joule Studio edition the exercises use. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Jan Portisch, Lucas Kiesow, Pavithra G K and Rafael Martin, written here from SAP's abstract; no recording is announced.
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Transform business data into AI-supported insightsTransform business data into AI-supported insightsBusiness metrics turned into insights, narratives and recommendations by SAP Joule's agents, with People Intelligence, the SAP Snowflake solution extension for SAP Business Data Cloud and SAP Analytics Cloud connected in SAP Business Data Cloud. The abstract names what is connected and what comes out, and does not say what the exercise builds or where the Snowflake extension sits in it; People Intelligence and the extension are not atlas entries. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Babacar Toure, Maximilian Paul Gander, Neetha Pucknat and San Tran, written here from SAP's abstract; the recording is not yet published.
Transforming Enterprise Data Strategy with SAP Business Data CloudTransforming Enterprise Data Strategy with SAP Business Data CloudSAP's layered picture of SAP Business Data Cloud, from lake storage and compute up to a knowledge core and agents, with eight sub-pages that each work one part through. The data products page is the cataloguing and lineage part: datasets described by Open Resource Discovery metadata, listed in the BDC catalog and shared over Delta Sharing to SAP Databricks and SAP HANA Cloud, with SAP Datasphere as a consumer on the intelligent content page; other pages install intelligent content, bring SAP BW data in through the Data Product Generator, provision groups by SCIM from Cloud Identity Services into SAP Databricks, which is identity provisioning, and train predictive models in SAP Databricks that SAP AI Core then serves for batch and real-time scoring. The main page states direction more than mechanism, and the BW page marks SQL Share for derived and OData for analytical data products as to be available.published 2026-05-12
Federating, Replicating, and Caching Remote Data in CAP — Part 2Federating, Replicating, and Caching Remote Data in CAP — Part 2The practical half of the pair. Where Part 1 sets out the terminology, what CAP does out of the box and where the gaps are, this one builds a small application that federates, replicates and caches remote data, one step at a time, with the finished project published as sales-cockpit so a reader can either follow along or start from the end. It began as a twenty-minute reCAP talk, which the author says was only room for the intro.published 2026-07-17
Deep Insert in SAP CAPM Using Composition and Fiori ElementsDeep Insert in SAP CAPM Using Composition and Fiori ElementsParent and children created in one transaction, which composition already gives you in the model — the post is about what Fiori elements does with it, and what the payload looks like when the UI sends both at once.published 2026-05-22
Explore the declarative power of status-transition flowsExplore the declarative power of status-transition flowsModelling which state a record may move to next, declaratively, rather than scattering the rule across the handlers that move it.SAP
Learn how to define constraints declaratively in your CDS modelLearn how to define constraints declaratively in your CDS modelConstraints expressed in the model rather than checked in a handler — the distinction the atlas draws between input validation the framework enforces and validation somebody writes.SAP
SAP Incentive Management - Understanding of CSN file & CLI Command to generateSAP Incentive Management - Understanding of CSN file & CLI Command to generateCSN met from the far end: not as CAP's compiled model but as the interchange format a product hands to Analytics Cloud so a story knows the shape of the data. Explains what CSN is, why the format matters here, and the command that produces one.Yogananda, published 2024-11-19
[BTP HANA Cloud Database] : How to access HANA Cloud Database & HDI Container in BTP[BTP HANA Cloud Database] : How to access HANA Cloud Database & HDI Container in BTPGetting at the database your application already deployed to, which sounds trivial until the HDI container is the only thing that has credentials for it. Guidance for the case where the account is already configured and the question is only how to look inside.showkath_naseem, published 2023-01-18
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Exposing Calculation View with Dynamic Client via OData APIExposing Calculation View with Dynamic Client via OData APIGetting a HANA Cloud calculation view — built in Business Application Studio and deployed to an HDI container, which is the recommended way to build native HANA artifacts — out through an OData API. The gap it fills is the one between HANA-native development and a service a client can call, which CAP does not cover for artifacts it did not generate.published 2023-10-04
Get hands on with tabular AI and forecasting models in SAP HANA CloudGet hands on with tabular AI and forecasting models in SAP HANA CloudPrediction and forecasting as predictive models inside SAP HANA Cloud, worked through hands-on: tabular AI models such as SAP-RPT-1 for on-the-fly predictions, time series foundation models for ad hoc forecasts, and the AutoML in the predictive analysis library. The abstract names the model kinds and the library and does not say how a model is called from SQL or from an application. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Markus Fath, Ritty Joseph and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
How to share tables across different CAP projectsHow to share tables across different CAP projectsFour scenarios for reading one CAP project's table from another, worked out as a matrix of what each one needs: the same HDI container and namespace, the same container under a different namespace, a different container, and a different Cloud Foundry space. The mechanics change with each step — @cds.persistence.exists on the reused entity throughout, an .hdbsynonym once namespaces diverge, .hdbrole and .hdbgrants once containers do, and a user-provided service built from the grantor's credentials once spaces do. The author flags the caveat themselves: these are learning scenarios, and consuming the OData service is often the better answer than reaching into another project's database. Dated corrections from twelve days after publication sit inline — synonyms need only the name because the configuration comes from .hdbsynonymconfig, SERVICE_REPLACEMENTS in mta.yaml removes the hard-coded service name, and the reused container need not be bound to the srv module.published 2021-10-03
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Medallion Reference Architecture for Big Data Processing in SAP HANA CloudMedallion Reference Architecture for Big Data Processing in SAP HANA CloudSAP's medallion layout for SAP HANA Cloud: structured, semi-structured and unstructured data lands raw in HANA Cloud, data lake files as the bronze layer, is cleansed into a common structure in silver, held in data lake files or the HANA database, and is curated and read-optimised in gold, from where it can also be exposed as a Delta Share. The staged path from raw to consumable is the ground loading a warehouse covers, with Spark jobs and SAP Datasphere data flows named as ways to move data between layers and SAP Analytics Cloud among the consumers of gold. It leaves the ingestion method open, to be chosen by source, freshness and performance, and names no pipeline or schedule beyond that.published 2025-04-03
SAP HANA Cloud as an Esri GeodatabaseSAP HANA Cloud as an Esri GeodatabaseSAP's design for running an Esri ArcGIS Enterprise geodatabase inside SAP HANA Cloud, so that geometries and SAP business data sit in one database and are joined in a HANA calculation view, which is the spatial part of graph, spatial and document data. It traces three personas: an analyst in ArcGIS Pro building query layers over that view, a developer whose CAP application models spatial types such as ST_Point in CDS, and an analyst using a Fiori app on top of such an application. The deployment advice stops at placement: ArcGIS Server and HANA Cloud go in the same region and availability zone, because Esri's certified architectures allow under 5 milliseconds of network latency between them.published 2025-03-25
Setting Up PostgreSQL for SAP BTP Development: A Practical GuideSetting Up PostgreSQL for SAP BTP Development: A Practical GuideOpens with the premise the rest of this bucket mostly assumes away — not every BTP application needs HANA Cloud — and then sets up PostgreSQL on the hyperscaler option. Part one of a series that continues into XSUAA.michal_majer, published 2026-01-20
Use SAP HANA as the Database for a CAP Java ApplicationUse SAP HANA as the Database for a CAP Java ApplicationMoving a CAP Java application off the development database onto HANA, which is the step where the persistence choice stops being invisible.SAP
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as an Esri GeodatabaseSAP HANA Cloud as an Esri GeodatabaseSAP's design for running an Esri ArcGIS Enterprise geodatabase inside SAP HANA Cloud, so that geometries and SAP business data sit in one database and are joined in a HANA calculation view, which is the spatial part of graph, spatial and document data. It traces three personas: an analyst in ArcGIS Pro building query layers over that view, a developer whose CAP application models spatial types such as ST_Point in CDS, and an analyst using a Fiori app on top of such an application. The deployment advice stops at placement: ArcGIS Server and HANA Cloud go in the same region and availability zone, because Esri's certified architectures allow under 5 milliseconds of network latency between them.published 2025-03-25
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Medallion Reference Architecture for Big Data Processing in SAP HANA CloudMedallion Reference Architecture for Big Data Processing in SAP HANA CloudSAP's medallion layout for SAP HANA Cloud: structured, semi-structured and unstructured data lands raw in HANA Cloud, data lake files as the bronze layer, is cleansed into a common structure in silver, held in data lake files or the HANA database, and is curated and read-optimised in gold, from where it can also be exposed as a Delta Share. The staged path from raw to consumable is the ground loading a warehouse covers, with Spark jobs and SAP Datasphere data flows named as ways to move data between layers and SAP Analytics Cloud among the consumers of gold. It leaves the ingestion method open, to be chosen by source, freshness and performance, and names no pipeline or schedule beyond that.published 2025-04-03
How to share tables across different CAP projectsHow to share tables across different CAP projectsFour scenarios for reading one CAP project's table from another, worked out as a matrix of what each one needs: the same HDI container and namespace, the same container under a different namespace, a different container, and a different Cloud Foundry space. The mechanics change with each step — @cds.persistence.exists on the reused entity throughout, an .hdbsynonym once namespaces diverge, .hdbrole and .hdbgrants once containers do, and a user-provided service built from the grantor's credentials once spaces do. The author flags the caveat themselves: these are learning scenarios, and consuming the OData service is often the better answer than reaching into another project's database. Dated corrections from twelve days after publication sit inline — synonyms need only the name because the configuration comes from .hdbsynonymconfig, SERVICE_REPLACEMENTS in mta.yaml removes the hard-coded service name, and the reused container need not be bound to the srv module.published 2021-10-03
HANA Database Migration: Handling Incompatible Changes to Existing TablesHANA Database Migration: Handling Incompatible Changes to Existing TablesThe question schema evolution exists for, asked plainly: how do you restructure a table in a production system that already holds live data. Incompatible changes are the ones CAP's own alter path will not make, which is where this starts.Sekar Somasundaram, published 2025-04-16