SAP Data Governance


Data Governance: An Overview and Key Considerations

What Is Data Governance?

SAP data can deliver innovation, drive user experience, and provide competitive advantage. The process of marrying SAP data with non-SAP data from different systems — from Internet of Things devices to the back office to an organization’s web systems — is defining data culture around the world.

Simply combining data, however, is not enough. Proper management is essential to realizing its value.

Data governance is considered a core component of an effective data management strategy. Data governance can ensure that data is consistent, accurate, and protected.

The Data Governance Institute (DGI) defines data governance as “a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.” (Read the DGI’s 10 rules of engagement.)

Data Governance: An Overview and Key Considerations

What Is Data Governance?

SAP data can deliver innovation, drive user experience, and provide competitive advantage. The process of marrying SAP data with non-SAP data from different systems — from Internet of Things devices to the back office to an organization’s web systems — is defining data culture around the world.

Simply combining data, however, is not enough. Proper management is essential to realizing its value.

Data governance is considered a core component of an effective data management strategy. Data governance can ensure that data is consistent, accurate, and protected.

The Data Governance Institute (DGI) defines data governance as “a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.” (Read the DGI’s 10 rules of engagement.)

Key Considerations for SAPinsiders

The following steps can help you implement effective data governance:

  • Create a strong business case for data governance. According to SAP partner Winshuttle, you need to be able to clearly communicate the value of your data to gain support from leadership. Winshuttle’s Winshuttle Foundation and Winshuttle Studio offer data management capabilities. According to the vendor, your data should be maintained through a data governance program that can ensure data quality and proper management, while complying with regulations to keep the data safe and effective.
  • Increase revenue potential with a strong data governance foundation. Consider the approach of Breakthru Beverage Group. On a mission to become a fully integrated, data-driven business, the company first built a foundation with its data governance program. The initiative to cleanse and conform its material, vendor, and customer data was supported by SAP partner Protiviti, and resulted in a scorecard on data cleanliness as well as a downstream benefit: revenue generation, by enabling the business to more quickly activate products and more accurately report on them. Read the full data story.
  • Set the stage for standardization and automation capabilities. In 2016, we wrote about Keurig Green Mountain’s approach to data governance. In response to meteoric growth and a growing love of the single-cup brew, the company undertook an ambitious data governance project. It transitioned from a data maintenance to a data governance organization. At the time, Keurig’s Director of Master Data Management Business Process Eileen Hanafin said its data governance initiative set the company up for future standardization and automation capabilities with a focus on continuous improvement.

895 results

  1. Pinpoint the Cause of Data Inconsistencies to Ensure Precise Key Figure and Characteristic Values

    Reading time: 16 mins

    Although many people view troubleshooting as a random process, you can apply a systematic technique to verify data quality. Use these helpful suggestions to locate errors. Key Concept During the final phase of BW projects, developers verify data quality. Here, quality refers to consistency and preciseness of the key figure and characteristic values that BEx...…

  2. Use Data Federator for Relational Universes on Top of SAP NetWeaver BW

    Reading time: 17 mins

    Find out how to install and configure SAP BusinessObjects Data Federator with SAP NetWeaver Business Warehouse (SAP NetWeaver BW). Then discover how to create relational universes based on your SAP NetWeaver BW InfoProviders, such as an InfoCube. Key Concept With SAP BusinessObjects Data Federator XI 3.1, you can create a relational universe based on your...…

  3. Role of Data Quality in Supply Chain Digital Transformation

    Reading time: 7 mins

    Quality Data Lays the Foundation As supply chains become increasingly complex, so does the associated data landscape. Millions of data points must be managed in modern supply chains today due to the wide gamut of systems used. From Enterprise resource planning (ERP) systems that manage an organization’s basic processes to customer relationship process (CRM) systems...…

  4. The Informatica Guide to SAP Modernization

    Reading time: 6 mins

    As companies begin to move to SAP S/4HANA, there are a litany of considerations they must make throughout the process. One of the most important considerations is in regard to data. Data management is a vital aspect of the move to SAP S/4HANA. It is important that users take a data-centric approach to this change,…

  5. Leveraging SAP HANA to Enhance SAP Business Planning and Consolidation’s Capabilities

    Reading time: 25 mins

    SAP Business Planning and Consolidation (BPC) 10.1, along with its host environments (SAP Business Warehouse [SAP BW] and SAP HANA) provide abundant design choices to meet today’s business planning needs. See a comparison between the various models available in BPC to facilitate appropriate model selection based on business priorities. The potential to enhance BPC capabilities...…

  6. Data Mining with the Analysis Process Designer in SAP BW 3.5

    Reading time: 9 mins

    The Analysis Process Designer (APD) workbench, introduced in BW 3.1 Content (BW 3.0B SP6), allows users to combine numerous transformations into a single data flow. It offers a less technical approach to enhancing subject-oriented, non-volatile data that has already been integrated, cleansed, and transformed in the data warehouse. The author examines current APD features and...…

  7. Clovity

    Data Management Tools in SAP EIM Portfolio: Part 1

    Reading time: 6 mins

    SAP Enterprise Information Management (EIM) solutions are designed to revolutionize the way organizations manage their data. SAP Enterprise Information Management portfolio is a comprehensive suite of solutions designed to help organizations effectively manage and leverage their data assets. It includes various data management tools and technologies that address the key aspects of information management, including…

  8. Turn Any-Sized Data Volume into Business Value: Discover the Power of SAP Data Warehouse Cloud

    Reading time: 13 mins

    Data volumes today are growing exponentially due to the various ways that data is being produced. SAP customers are being inundated with information as more and more data is arriving into hybrid environments of on-premise and cloud systems from various ERP solutions, data lakes, customer feedback via mobile apps, and social media interactions, to name…

  9. Performance Tuning Strategies to Optimize Your SAP Data Services Environment

    Reading time: 13 mins

    Step beyond traditional database tuning concepts, such as indexing and partitioning, and get expert tips to move toward a parallel approach for code design and job construction. Examine parallel execution within SAP Data Services to see how it distributes operations and uses the strengths across your system. Get expert advice on leveraging the pushdown capabilities...…

  10. Prospecta -- Image

    Data Integrity and Transformation Go Hand in Hand

    Reading time: 6 mins

    Technological innovation enables digital transformation. In his Enterprise Data and Analytics report, SAPinsider’s Kumar Singh explains that the commoditization of technology continuously lowers barriers to entry across industries, enabling smaller, nimble, and agile companies to disrupt larger and more established businesses. The report surveyed 291 members of the SAPinsider community. The purpose of the survey…