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Author's profile photo Wolfgang Albert Epting

Data Mesh with SAP Business Technology Platform Part 1 – SAP Data Warehouse Cloud

Summary: In my first blog with the title: More than just a hype: Data Mesh as a new approach to increase agility in value creation from data I explained the four Data Mesh principles at a high level and mapped some helpful capabilities of the SAP Unified Data & Analytics Portfolio. In the following episodes I will take a closer look at individual SAP products  and explain in more detail which technical capabilities can assist the implementation of a Data Mesh. In this blog, I will start with SAP Data Warehouse Cloud and later follow up with SAP HANA Cloud, SAP Analytics Cloud, SAP Data Intelligence Cloud and SAP Master Data Governance.

 

The reason Data Mesh is all the rage right now that it shall address weaknesses and bottlenecks of traditional, centralized data delivery.

 

Manage Data as a Product:

 

Often there is a mismatch between what the business units request and what they get. When data is viewed and managed as a product, as Data Mesh posits, this discrepancy can be overcome. Then a product manager is responsible for ensuring demand before and consumption after delivery. Like any other slow-moving product in the real economy, slow data products consequently have to be taken off the market.

The place where demand and supply meet is the marketplace, which is no different for data products. The SAP Data Warehouse Cloud Data Marketplace provides an easy and flexible way to offer and consume data products.

The SAP Data Marketplace is fully integrated into SAP Data Warehouse Cloud. Artefacts are provided in form of objects packaged as data products that can be used in one or several SAP Data Warehouse Cloud Spaces.

Activities of the data product producers:

5 steps to offer data products to consumers

Data Providers can manage the entire lifecycle of their data products – including the adoption state which is especially required for potential deletion activities. With the upcoming context management there will be the possibility to differentiate public, private and internal data products, so that the provider will have the possibility to specify his desired visibility upfront to decide with whom you share for what – to run an internal data marketplace or a cross-company data exchange.

Activities of the data product consumers:

3 steps to consume data products

Data products are directly available in the selected SAP Data Warehouse Cloud Spaces to make them accessible:

  • for other decentralized domain teams to build new aggregated consumer-aligned data products:
  • for consumers to get clear and actionable insights that help them to run their business in a better way and build greater products:
    • Interoperable usage in all kind of patterns leveraging the Data Mesh in its best way
    • Visualization, Enterprise Planning and augmented Analytics with SAP Analytics Cloud
    • Usage of any preferred third party tool of choice via open interfaces

By the way, Data Marketplaces and their relevance for Data Mesh, Data Fabric and other approaches are part of Mohamed Abdel Hadi‘s (Chief Technology Officer – Vice President Business Technology Platform – Middle and Eastern Europe at SAP) top 5 focus areas in Data & Analytics.

 

Combine domain knowledge and data engineering skills:

 

Another essential component of Data Mesh are cross functional domain data teams with explicit data product ownership. On the one hand, this shall ensures the availability of domain knowledge and counteract the chronic overload of the central data preparation team, which is the typical situation today in most organizations.

SAP Data Warehouse Cloud Spaces offer a perfect environment to optimally support decentralized domain teams. A space is a secure area created by an Administrator, in which members can acquire, prepare, and model data in virtual work environments with their own databases. Spaces are decoupled, but are open for flexible access, thus allowing domain teams to collaborate without having to worry about sharing their data. Spaces can be prioritized in terms of resources to reflect the importance of the respective underlying project. A space can be created with just a few clicks, which Shoaib Haider describes in this blog post.

SAP Data Warehouse Cloud Spaces

 

Reuse business context:

 

The final weakness of decentralized data delivery I want to address in this blog is the lack of speed with which business departments are served. Decentralized domain teams can only unfold their full potential if all the technical, conceptual and organizational ingredients, such as catalogs, pipelines and particularly metadata, are available. By metadata I don’t mean structural information, but business context. “Business context” is the semantically rich information contained within an SAP application that gives data value and meaning including relationships and metadata.

SAP Data Warehouse Cloud instantly connects to SAP sources out-of-the-box and immediately understands the business context of the data. Its open connectivity and new features like the above mentioned Data Marketplace help to connect to all kinds of external data in a matter of clicks empowering business users to perform self-service analytics. SAP Data Warehouse Cloud provides a business layer that allows everyone to work with data in business terms and to create data products easily without support from the IT infrastructure team. This excellent blog by Hagen Jander gives an example describing how the Human Resources department benefits from SAP Data Warehouse Cloud as it is equipped with intelligent capabilities empowering business users to unlock their full potential.
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I would like to make a general comment at the end. When designing our products, we at SAP attach great importance to customer acceptance and quality. Therefore, we conduct extensive analyzes of our customers’ needs to ensure that we optimally support the generation of real business value from data.

This does not mean that we would ignore trends such as Data Mesh, Data Fabric or others. These are always of great relevance for the design of our products if they are of great importance to our customers. In the case of Data Mesh, we take this very seriously because we believe that, although the success of a socio-technological topic like this depends largely on organizational factors, the right technology is crucial for success.

Further information:

The author would like to thank Hagen Jander, Oliver Huth and Gebhard Roos for the collaboration on this topic and their contributions to this article.

Here the links to my complete blog series aboot Data MEsh with SAP Business Technology Platform:

If you have any further questions about SAP Business Technology Platform or specific elements of our platform, leave a question in SAP Community Q&A or visit our SAP Community topic page.

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