{"id":6613,"date":"2026-07-15T15:37:18","date_gmt":"2026-07-15T13:37:18","guid":{"rendered":"https:\/\/bluetelligence.de\/from-sap-data-silo-to-data-product-rethinking-transparency-governance-and-self-service-bi\/"},"modified":"2026-07-24T09:40:30","modified_gmt":"2026-07-24T07:40:30","slug":"from-sap-data-silo-to-data-products","status":"publish","type":"post","link":"https:\/\/bluetelligence.de\/en\/from-sap-data-silo-to-data-products\/","title":{"rendered":"From SAP Data Silo to Data Product\u2014Rethinking Transparency, Governance, and Self-Service BI"},"content":{"rendered":"\t\t
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Our guest author hits the nail on the head when he says, \u201cThe critical issue with data products isn\u2019t just whether they work well on a platform. The real question is: Who owns the data and context?\u201d If domain-specific definitions, quality rules, lineage, and data contracts exist only within a single solution\u2019s metamodel, the result is not a data product but a lock-in product. Companies should therefore insist on data sovereignty: Data products must be able to function in SAP, but their significance must not be trapped within SAP.\u201d<\/i><\/p>\n

\u2013 Timm Grosser, Senior Analyst, Data & Analytics at BARC<\/span><\/strong><\/p>\n

That is exactly what this article will explore, drawing on a recent webinar on the topic. Why are data products necessary in the first place? What problems do they solve? And how can they be implemented in practice, particularly in the SAP environment? <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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What does Amazon have to do with Data Products?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Like in the webinar, we’ll start with an unusual comparison: Amazon.<\/p>

In the past, looking for a book meant visiting various libraries or bookstores until you found the copy you wanted. Today, we expect information right away: We open Amazon, search for a product, and within seconds we get all the relevant information\u2014from price and delivery time to reviews and recommendations. <\/p>

We are increasingly applying this very same expectation to corporate data: Data should be easy to find, clearly described, and ready to use\u2014just like a product in an online store.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The reality: Accessing data is often more complicated than it needs to be<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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In many companies, however, the reality is different: Employees often have no idea,<\/p>\n

    \n
  • whether the required data even exists,<\/li>\n
  • where it is stored,<\/li>\n
  • whoever has access to it,<\/li>\n
  • who is responsible for them, or<\/li>\n
  • whether it can be trusted at all.<\/li>\n<\/ul>\n

    On top of that, data often has to be requested through the IT department first. Departments have to wait for access permissions or analyses, thereby losing valuable time. <\/p>\n

    This often leads to data silos or even shadow IT, because departments build up their own data sets. So the real problem isn’t a lack of data\u2014it’s the difficulty in accessing it. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    The Solution: Data Democratization and Data Products<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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    To solve this problem, the concept of data democratization<\/strong> was developed a few years ago.<\/p>\n

    The idea was simple: Companies should move away from the<\/strong> traditional \u201cneed-to-know\u201d principle<\/strong>. Until then, employees had to justify why they needed data. Access was primarily controlled by the IT department. <\/p>\n

    Instead, the “right-to-know” principle <\/strong>became increasingly established : Data <\/strong>should, as a general rule, be accessible to all authorized individuals. The goal was to enable self-service analytics and make business units less dependent on IT. <\/p>\n

    At first, this seemed to solve the original problem\u2014but a new challenge soon emerged: The more data became available, the harder it was to make sense of it all. Suddenly, entirely different questions arose: <\/p>\n

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    • What data can I trust?<\/li>\n
    • Which metric is the right one?<\/li>\n
    • Who is responsible for this data?<\/li>\n
    • Is the information up to date?<\/li>\n
    • Am I even allowed to use this data?<\/li>\n<\/ul>\n

      While this openness led to greater accessibility, it also often resulted in reduced transparency and less trust in the data.<\/p>\n

      This is exactly where data products<\/strong> come in, and in the webinar, Timm Grosser (BARC)<\/b> provided the following definition:<\/p>\n

      \u201cThe purpose of a data product is to democratize access to trustworthy, business-ready data while reducing complexity and shortening the time it takes for data users to gain insights.\u201d<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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      Source: BARC<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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      Data products thus combine the openness of data democratization with the rules of clear data governance. A data product consists of more than just data. <\/p>

      It also combines<\/p>

      • technical context,<\/li>
      • Metadata,<\/li>
      • Responsibilities,<\/li>
      • Quality Information,<\/li>
      • Rules of Use and<\/li>
      • often also so-called “data contracts”.<\/li><\/ul>

        This makes data not only accessible, but also understandable, trustworthy, and reusable.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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        Data Products in the SAP Environment<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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        SAP is also consistently pursuing this approach: With the SAP Business Data Cloud (BDC)<\/strong>, data from various SAP systems can be consolidated and then made available as data products, primarily in the BDC Catalog.<\/p>

        SAP distinguishes between two types of data products:<\/p>

        SAP Managed Data Products<\/strong> are delivered by SAP in a standardized form and can be used with relatively little effort. However, this requires a largely standardized SAP landscape without extensive custom developments. <\/p>

        In practice, however, things often look different: Many companies work with custom Z-tables, their own ABAP code, or specially developed data models. For these scenarios, Customer Data Products<\/strong> must be created using tools provided by SAP, allowing companies to model and maintain their own data themselves. <\/p>

        In addition, many companies today do not rely exclusively on SAP. Power BI, Microsoft Fabric, Snowflake, and Databricks are now just as much a part of the analytics landscape as traditional SAP systems. While data and data products can be integrated into the SAP Business Data Cloud with relative ease, data exchange in the opposite direction often runs into technological\u2014and in some cases, contractual\u2014limitations. This creates the risk of becoming more heavily tied to a single platform than originally planned. <\/p>

        In hybrid environments in particular, this raises the question of how data products can be implemented in a way that is as technology-agnostic as possible. One possible approach is to supplement existing systems with solutions that operate directly at the source system level\u2014such as SAP S\/4HANA, SAP ECC, or SAP BW. Instead of first cataloging data in a central SAP platform, these solutions provide transparency regarding existing data and metadata right where it is generated. This gives companies a complete overview of their SAP data while simultaneously laying the groundwork for data products that can be used independently of any specific target platform. <\/p>

        That’s correct for Data Products that are used externally. Within SAP, Data Products can also be built in Datasphere (+Marketplace). <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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        The Enterprise Glossary by bluetelligence <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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        If your company is amongst those who do not yet use a business data cloud or wish to remain technology-agnostic, implementing data products can be challenging. A logical first step would be to establish transparency regarding existing data assets and make existing data products discoverable and usable by business units. <\/p>

        For this purpose exaclty, we’ve developed a solution: the Enterprise Glossary. As a central web application, the Enterprise Glossary synchronizes metadata from SAP and Power BI systems, catalogs it centrally, and makes it available to business users in an easy-to-understand format. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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        Whenever departments need specific data, they can easily search for and find existing data products in the Enterprise Glossary:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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        Search\/Find Published Data Products<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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        Business users then gain a clear understanding of the technical background\u2014without having to rely on IT support:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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        View the Technical Structure of Data Products (CDS View)<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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        At the same time, you can check the sources of the data product at a glance: either in a list or in a graphical data flow:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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        Visualize cross-system data flow (e.g., from CDS views)<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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        In addition to providing technical transparency, the Enterprise Glossary also enables the enrichment of data objects with domain-specific information. This transforms purely technical metadata into understandable, domain-specific data products that can be published and used in a targeted manner. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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        Enrich data products with subject-matter expertise and publish them as data products<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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        In doing so, organizations create the essential conditions for successful data products:<\/p>