Data Product
Topic
In a nutshell
A data product is a technically defined, reusable data product that provides data in a standardized format for analysis, planning, reporting, or AI applications. It encompasses not only the data itself, but also definitions, responsibilities, quality rules, and a clear technical meaning. In the SAP Business Data Cloud, data products play a central role in the provision and use of data from SAP and non-SAP systems.
Why are data products important?
Many companies today have large amounts of data, but can only utilize it at considerable cost. Often, there are differing definitions of the same metric, redundant data sets, or complex ETL processes. The result is long project timelines, a high level of coordination effort, and a lack of trust in the data.
Data products take a different approach: data is treated as a product. This means that it is described in technical terms, documented, quality-assured, and made available to different user groups. Users do not have to reprocess or reinterpret the data each time; instead, they can access standardized and reusable data products.
This approach is becoming particularly important in the context of modern data platforms. SAP Business Data Cloud, Databricks, Microsoft Fabric, and data mesh architectures are increasingly relying on data products as building blocks of a scalable data landscape. Instead of individual data silos, reusable data products are created that can be shared by analytics, planning, AI applications, and operational processes.
Furthermore, data products form an important foundation for the use of artificial intelligence. AI applications require consistent, domain-expert, and trustworthy data. Without clearly defined data products, the risk of flawed analyses and unreliable AI results increases significantly.
How does celver provide support?
Many companies are currently grappling with the question of what a modern target architecture for data, analytics, planning, and AI should look like. Data products often play a central role in this context, but are frequently interpreted in different ways.
celver helps companies integrate data products into their existing architecture from both a business and technical perspective. We consider both SAP and non-SAP systems, as well as platforms such as SAP Business Data Cloud, SAP Datasphere, Databricks, and Microsoft Fabric. The goal is to design data products so that they can be shared across different business units and technologies.
Typical questions from our customers include:
- What types of data are suitable for a data product?
- Who is responsible for the technical aspects?
- What is the difference between data models and data products?
- How can data products be used for analytics, planning, and AI?
- What role do data products play in SAP Business Data Cloud or Databricks?
- How can SAP and non-SAP data be combined into shared data products?
Our focus is not on individual technologies, but rather on a data architecture that is sustainable in the long term and supports business units, IT, and future AI applications alike.
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Frequently Asked Questions
No. Data products are a general architectural concept and are supported by platforms such as SAP Business Data Cloud, Databricks, and Microsoft Fabric alike.
A report presents information. A data product provides the underlying data, including its business context, quality rules, and responsibilities, for a wide variety of use cases.
AI systems require consistent and domain-specific data. Data products provide the necessary foundation for making data trustworthy and reusable for analytics, planning, and AI.
