---

name: sap-hana-cloud-data-intelligence description: SAP HANA Cloud Data Intelligence — data integration pipelines, data quality rules, metadata catalog, data lineage, SAP Data Intelligence Cloud, data governance, ETL orchestration, connection management. Use when building data pipelines with SAP DI Cloud, implementing data quality checks, managing metadata catalogs, or integrating S/4HANA data with HANA Cloud analytics. trigger: keywords: [hana-cloud, data-intelligence, pipelines, data-quality, metadata, lineage, etl, governance, di-cloud, s4hana] intent: >- Build data pipelines, implement data quality checks, and manage metadata catalogs with SAP Data Intelligence Cloud to integrate S/4HANA data with HANA Cloud analytics.

SAP HANA Cloud Data Intelligence

Data integration, quality, and catalog on SAP BTP — formerly SAP Data Intelligence Cloud.

Core Capabilities

Capability	Description	S/4HANA Relevance
Data Integration	ETL/ELT pipelines, 200+ connectors	Extract S/4HANA data for analytics
Data Quality	Rules-based validation, cleansing, dedup	Clean master data before migration
Metadata Catalog	Searchable catalog of all data assets	Discover S/4HANA CDS views, tables
Data Lineage	Track data from source to consumption	Impact analysis for S/4HANA changes
Connection Management	SAP + non-SAP source connectivity	ABAP, HANA, ODP, SLT connections

Data Pipeline

Source (S/4HANA CDS View) → Read → Transform → Quality Check → Write → Target (HANA Cloud)

Pipeline Operators

Operator	Function	Example
CDS Reader	Read SAP CDS views	Extract I_Product view
ODP Extractor	ODP framework extraction	Extract from S/4HANA extractors
SLT Connector	Real-time replication	Replicate MARA table changes
SQL Transform	SQL-based transformation	Join, filter, aggregate
Python Operator	Custom Python logic	ML preprocessing
Data Quality	Validate and cleanse	Check mandatory fields
HANA Client	Write to HANA Cloud	Load into HDI container

Connection Types

// ABAP connection to S/4HANA
{
  "type": "ABAP",
  "host": "s4hana.internal.corp",
  "client": "100",
  "authentication": "BASIC",
  "protocol": "RFC"
}

// HANA connection
{
  "type": "HANA_DB",
  "host": "hana-cloud.cfapps.us10.hana.ondemand.com",
  "port": 443,
  "authentication": "DB_USER",
  "encrypt": true
}

Data Quality Rules

-- Mandatory field check
SELECT COUNT(*) FROM input_data WHERE material IS NULL;

-- Duplicate detection
SELECT material, COUNT(*) FROM input_data GROUP BY material HAVING COUNT(*) > 1;

-- Value range validation
SELECT * FROM input_data WHERE quantity < 0 OR quantity > 1000000;

Data Lineage

Lineage tracks how data flows through pipelines:

S/4HANA table MARA
  → CDS View Z_I_PRODUCT
    → DI Pipeline "Product Enrichment"
      → HANA Cloud table Z_PRODUCT_ENRICHED
        → SAC Story "Product Dashboard"

Impact: changing MARA field length → alerts Z_I_PRODUCT consumers.

S/4HANA CDS Integration

S/4HANA CDS View → ODP Extraction → DI Pipeline → HANA Cloud
  (I_Product)     (delta-enabled)   (transform)    (analytical dataset)

ABAP Trigger

" Trigger DI pipeline from ABAP Cloud
DATA(lo_http) = cl_web_http_client_manager=>create_by_http_destination(
  i_destination = cl_http_destination_provider=>create_by_cloud_destination(
    i_name = 'DI_CLOUD' ) ).
lo_http->get_http_request( )->set_text( '{ "pipeline": "Product_Load" }' ).
DATA(lo_response) = lo_http->execute( i_method = 'POST' ).

Gotchas

• DI Cloud is a separate BTP service subscription (not bundled with HANA Cloud)
• ODP extraction requires S/4HANA ODP framework active (transaction ODQMON)
• Data lineage tracked at column level in S/4HANA CDS views
• Metadata catalog auto-discovers HANA Cloud assets; non-HANA sources need manual registration
• Pipeline scheduling via Job Scheduling service or REST API trigger