SAP Data Services


What Is SAP Data Services?

SAP Data Services is an enterprise solution that offers data integration, profiling, quality, and text processing capabilities. It was formerly called SAP BusinessObjects Data Services.

SAP Data Services enables users to integrate, transform, and load data. SAP Data Services is a comprehensive extraction, transformation, and loading (ETL) tool. It supports loading of structured and unstructured data from SAP and non-SAP data sources into any SAP HANA application.

SAP Data Services combines the ability to execute data integration and ensure data quality and data cleansing.

Key Benefits and Capabilities of SAP Data Services

What Is SAP Data Services?

SAP Data Services is an enterprise solution that offers data integration, profiling, quality, and text processing capabilities. It was formerly called SAP BusinessObjects Data Services.

SAP Data Services enables users to integrate, transform, and load data. SAP Data Services is a comprehensive extraction, transformation, and loading (ETL) tool. It supports loading of structured and unstructured data from SAP and non-SAP data sources into any SAP HANA application.

SAP Data Services combines the ability to execute data integration and ensure data quality and data cleansing.

Key Benefits and Capabilities of SAP Data Services

SAP Data Services allows organizations to achieve a complete view of their information, standardize and match data to reduce duplicates and improve decision-making and operational efficiency, and integrate operational, analytical, machine-generated, and geographic data.

Key capabilities of SAP Data Services include:

  • Universal data access
  • Data quality dashboards
  • Native-text data processing
  • Simplified data governance
  • Intuitive business user interfaces
  • High performance scalability

Who Uses SAP Data Services?

According to SAPinsider contributor Michael Vavlitis, several types of users can leverage SAP Data Services, including source system experts, data analysts, developers, and ETL operation managers/data architects.

The core responsibilities of these roles can be summarized as follows:

  • Source system experts – Provide information, metadata about source system and data content, as well as what tables and views to connect through using SAP Data Services
  • Data analysts – Translate business requirements into functional requirements and required source data needs. Validate data test results, transformations, and data-cleansing activities.
  • SAP Data Services developers – Create technical specs based on input from the data analysts. Responsible for developing all objects, schedules, and test procedures.
  • ETL operations managers or data architects – Monitor daily processing of ETL jobs, error logs, manual fixes, connectivity, and security. Upgrade and apply SPs and SAP Notes to maintain the overall application. Track key performance indicators (KPIs) for service level agreements (SLAs), system availability, and overall performance. Responsible for maintaining development standards, standard operating procedures (SOPs), naming conventions, data dictionary, structured walkthroughs, and approvals. Act as the overall data architect for the SAP Data Services and related systems.

In 2019 Nancy Ochs explained during an SAPinsider event how CSL Plasma, a leader in plasma collection, enabled analytics advancements. The company divided its integrated SAP Data Services from the SAP BusinessObjects BI Platform to provide additional features and capabilities in data management and gain the ability to apply updates to the analytics platform and enterprise information management components independently. View the event presentation slides.

922 results

  1. Informatica Strengthens Databricks Partnership with Native GenAI Capabilities for Databricks Data Intelligence Platform

    Reading time: 4 mins

    Informatica has enhanced its partnership with Databricks by integrating its Intelligent Data Management Cloud (IDMC) with Databricks Data Intelligence Platform, enabling no-code data pipelines, AI Functions capabilities, and efficient processing of large datasets, which benefits enterprise customers, including SAP users, by streamlining data management and analytics.

  2. Data Can’t Wait: Start Planning Today

    Reading time: 14 mins

    Since the inception of SAP S/4HANA, one of the main risks that often derails the implementation journey centers around preparing, cleansing, converting, and managing the data. This article presents leading practices that SAP customers can leverage during their SAP S/4HANA implementations to significantly reduce program risks associated with the data conversion process. The advice provided…

  3. How to Migrate to the New DataSource Concept in SAP NetWeaver 2004s

    Reading time: 17 mins

    A new data flow concept has been introduced in SAP NetWeaver 2004s. SAP still supports the existing classic 3.x data flow, which allows customers to migrate as their needs warrant. Although the migration is not required, it presents a host of new capabilities. Key Concept A DataSource can only exist in one of two states:...…

  4. Navigate the Complexities of Big Data with SAP Vora

    Reading time: 13 mins

    In today’s world of distributed and near endless big data, IT faces a wealth of new challenges. Data scientists must find ways to work with multiple data sets pulled from a myriad of sources to derive conclusions and reach actionable business decisions. SAP Vora, an in-memory query engine that plugs into the Apache Spark execution...…

  5. Live from SAPinsider Studio: Anurag Barua on Data Quality for the Digital Enterprise

    Independent consultant and longtime SAP technologist Anurag Barua joins SAPinsider Studio at the BI-HANA 2016 event to discuss data quality for the digital enterprise, including the role of SAP Data Services and SAP Information Steward. Topics of this discussion include the material impact of poor data quality, how a transition to a digital core and...…

  6. Getting Started with SAP BusinessObjects Data Migration to an SAP CRM System

    Reading time: 14 mins

    Data migration is a major task, and crucial for a successful SAP CRM implementation. Learn about using SAP BusinessObjects Data Migration to move your data into SAP CRM, ensuring that it can be trusted by users and is ready for business process execution. Key Concept Enterprise Information Management (EIM) is the discipline of managing, governing,...…

  7. Implementing SAP HANA: Experiences and First Impressions

    Reading time: 17 mins

    /IT/HANAGet a first-person account of an SAP HANA installation, including initial impressions with the software’s features, challenges encountered during the implementation, and lessons on SAP HANA’s integration with SAP BusinessObjects BI tools. Key Concept SAP HANA Studio is the primary client tool used to manage SAP HANA and to create analytic views. It contains database...…

  8. Create a Web Service with SAP BusinessObjects Data Service to Deliver Real-Time Data Quality

    Reading time: 10 mins

    Learn how to create a real-time data quality Web service to deliver accurate and reliable customer data. Explore time-saving tips and tricks for developing a flexible data flow that any application can use to cleanse and standardize data and for configuring an SAP BusinessObjects Data Services server. Key Concept The data quality engine on the...…

  9. Part 2: Data Modeling Strategies to Avoid Data Inaccuracy and Ensure Consistency

    Reading time: 38 mins

    Overcome the challenge of retaining the original master data attribute validity from when transactions occurred. Key Concept Developers only tend to use time-dependent master data attributes when a source system provides them as time dependent. However, SAP NetWeaver BI can also record time-independent master data from a source system as time dependent. This can greatly...…

  10. How to Move SAP BusinessObjects Data Services from One Data Center to Another

    Reading time: 11 mins

    Learn how to migrate an SAP BusinessObjects Data Services’ source data center to a target data center environment by following these step-by-step instructions. In this scenario, both the source and target systems are Windows-based servers.  Membership Required You must be a member to access this content.View Membership LevelsAlready a member? Log in here