Streamlining SAP Integration with Informatica's Advanced Extraction and Replication Solutions

Organizations seek seamless and efficient ways to integrate vast SAP datasets for comprehensive analytics and decision-making. Informatica supports this goal by offering sophisticated solutions that enable seamless data extraction from SAP environments. Through diverse methodologies such as application and database layer integration, hybrid approaches, and advanced mechanisms, Informatica empowers organizations to harness their SAP data effectively. This blog offers innovative strategies to showcase how to enhance operational efficiency and transform analytics capabilities.

Informatica provides various options for supporting bulk and incremental data extraction from SAP systems and replication to all supported targets through various connectors and tools designed to facilitate efficient data integration.

Informatica Cloud Data Ingestion and Replication and Cloud Data Integration services provide different approaches for data extraction from SAP to address multiple use cases,

• Application layer:  Data is accessed through SAP application layer
• Database layer: Data is accessed through an underlying database for replicating data leveraging logs or triggers
• Hybrid: An application layer is used for the initial bulk load and database layer is used for incremental data capture.

Please refer following for an overview of these capabilities.

An application layer approach allows users to access data from transparent tables, cluster tables, pool tables, views, ABAP CDS views, Advanced DataStore Objects (ADSOs) etc. via Advanced Business Application Programming (ABAP). When data is read from SAP tables, mapping can be configured to perform delta extraction. With delta extraction, you can choose to read only the changed data. The SAP table and SAP columns for which you want to perform delta extraction must be part of a change document object in SAP.

The approach leverages the Change Document Header (CDHDR) and Change Document Position (CDPOS) tables in SAP to extract the changed data. The CDHDR table stores the change document header information. The CDPOS table stores the new and old values of the changed data.

This option is available via the SAP Table connector in the Cloud Data Integration service.

In this approach, change data is captured from SAP HANA source tables in the schema using AFTER DELETE, AFTER INSERT and AFTER UPDATE triggers. The triggers get before images and after images of DML changes for each source table and write entries for the changes to the PKLOG and shadow _CDC tables.

Hana DB Trigger replication method is available in Cloud Data Ingestion and Replication service.

In this approach, change data is captured from the SAP HANA database logs. Every time there is a change in data, it gets recorded in the transaction log, which is then read by the SAP CDC process to recognize the change. This method ensures minimal impact on the source database.

Hana DB Log-based CDC capability is currently in preview and available in the Cloud Data Ingestion and Replication service.

In this approach, the initial bulk load is done via the application layer. For incremental data updates, the connector uses Oracle Logs or Hana DB Triggers to identify the change data.

The capability is available in the Cloud Data Ingestion and Replication service.

ODP is an SAP NetWeaver-based framework that unifies data transfers between the source and target systems. The ODP installed as a source in the SAP system maintains the Operational Delta Queue (ODQ) that allows delta data extraction from ODP-enabled data sources.

Informatica offers ODP connector which leverages ODP framework for SAP Data extraction. The connector is available in both Cloud Data Ingestion and Replication (CDIR) and Cloud Data Integration services. CDC capability is available in CDIR only.

OData web protocol connectors can be used to invoke SAP OData services for performing various operations such as create, read, update and delete of entities, as well as invoking functions on the service.

Using ODP-based data extraction via OData V2 (based on the OData communication protocol) users can perform consistent, scalable delta extraction of ODP data into external non-ABAP recipients. This is the recently recommended approach by SAP for data extraction.

OData V2 and V4 connectors are available today with the Informatica Data Integration solution. The CDC capability in the Cloud Data Ingestion and Replication service is scheduled to become available in the first half of 2025.

Manufacturing Company

Challenge

A leading manufacturer faced challenges with its analytics capabilities due to siloed data and inefficient reporting processes. Integrating data from multiple sources, including SAP ERP and SAP CRM, into a centralized platform like Snowflake was essential to overcoming these challenges.

Outcomes

• By integrating data from multiple sources into Snowflake, the company transformed its analytics capabilities, enabling a more comprehensive and holistic view of its operations.
• The integration allowed teams to produce more detailed and user-friendly reports in significantly less time, enhancing decision-making processes across the organization.
• With access to integrated data and improved reporting, they can now accurately forecast demand across intricate product groups, leading to better inventory management and resource allocation.
• The organization can meet analytics demands seamlessly, even during crucial month-end and quarter-end periods, ensuring that critical business insights are always available when needed.

Multinational Conglomerate

Challenge

A global organization faced difficulties meeting the growing demand for analytics due to limitations in their on-premises data warehouse, SAP ECC. As a result, they wanted to move to Snowflake but ingesting and replicating large volumes of SAP data posed a significant challenge, adversely affecting business operations. 

Outcomes

•  Reduced the time required for ingesting 90 million records from 2.5 hours to just 30 minutes.
• The significant reduction in data ingestion time resulted in enhanced operational efficiency, allowing the company to process and analyze data more quickly and effectively.
• With improved data ingestion and replication capabilities, the company can now make faster and more informed decisions based on real-time data insights.

Discover how Informatica enhances data integration with SAP through advanced data ingestion and replication capabilities, facilitating seamless data extraction, efficient replication and improved analytics for large-scale, global enterprises. Visit Informatica.com to learn more.