Skip to Content
Technical Articles
Author's profile photo Fabian Lehmann

Release of SAP Data and Analytics Advisory Methodology

Intro

These days, companies in all industries look for opportunities to use data to improve business operations or provide smart product and services to their customers. Still, the potential to gain value from data remains largely untapped as companies struggle to keep pace with simply accessing, storing and harmonizing the data in complex and unintegrated data landscapes. Many Business and IT leaders are looking for a structured repeatable approach to swiftly design and realise data-driven ideas.

SAP business applications create much of the transactional data our customers require for additional value creation. Also, with the announcement of SAP Datasphere, and its open data ecosystem, as the technology foundation that enables a business data fabric, SAP has underpinned the position as a leading provider of Data Management and Analytics solutions. Looking at the challenges our customers face in this area, SAP has recognized the opportunity to develop a methodology to guide our customers in this process.

Thus, we are pleased to announce the first version of the “SAP Data and Analytics Advisory Methodology” intended for our customers/partners. The purpose is to provide guidance in the design and validation of solution architectures for data-driven business innovations.

SAP%20Data%20and%20Analytics%20Advisory%20Methodology

SAP Data and Analytics Advisory Methodology

The methodology represents an architecture approach based on standard TOGAF Architecture Development Method and is intended for enterprise and data architects to help execute their data strategy.

The structured process is accompanied by a

  • data domain reference model to establish a common understanding of SAP data,
  • a data & analytics capability model to better support the architecture definition and
  • Data-to-value use case patterns and related reference architectures to accelerate solution architecture development.

The methodology also considers the organizational impact new data & analytics capabilities and solutions might have and how governance processes need to be adapted. Finally, it supports an Open Data Ecosystem consisting of related Third-party software products of Hyperscalers or SAP partners.

“SAP Data and Analytics Advisory Methodology” complements the already exiting SAP methodologies for the intelligent, sustainable enterprise:

SAP%20methodologies%20for%20the%20intelligent%2C%20sustainable%20enterprise

SAP methodologies for the intelligent, sustainable enterprise

All three methodologies aim to support our customers and partners and are provided free of charge. They follow a structured and step-wise approach for analyzing requirements and selecting appropriate solutions based on well-established and documented best practice.

 

The „Data Product“ as central architecture building block

The development of data-to-value solutions is based on a common framework of architecture building blocks that guides the definition of a tailored data architectures.

 

Common%20framework%20of%20building%20blocks%20for%20the%20composition%20of%20data%20architecture

Common framework of building blocks for the composition of data architecture

 

In the center of this framework is a “Data Product”, a controlled dataset provided by a data domain that is composed of data, metadata and standard APIs to access it. Any data-to-value business scenario is based on this fundamental concept to provide the right data in the right quality and format, easily accessible for data consumers.

Customer use cases that focus on this data provisioning scenarios are called “Technical Use Cases” while those focusing on creating value out of data are referred to as “Business Use Cases”. The methodology is providing standardized use case patterns that are organized in categories that share architecture patterns or technical capabilities.

Overview%20of%20use%20case%20categories%20and%20patterns%20for%20data%20and%20analytics

Overview of use case categories and patterns for data and analytics

The use case patterns are mapped to reference architectures that help to develop the right solution architecture quicker. The following example represents an SAP BTP-based reference architecture for the use case pattern “Analytical Apps”.

BTP%20reference%20architecture%20for%20analytical%20app

BTP reference architecture for analytical app

You can find the BTP reference architecturese in this GitHub repository

In this repository well publish the BTP reference architecture for our methodologies as well as other BTP based architectures:

 

Overview of architecture development phases

Our new methodology provides a structured process to develop a tailored solution architecture for data-driven business outcomes and is composed of four main phases:

 

Data and Analytics Advisory Methodology

In Phase I the objectives and scope of the investigation is defined and the as-is situation is analysed to identify data-to-value opportunities or improvement potential.

Phase II and III is executed for each business outcome that describes the measurable result. Phase II focusses on analysing the use cases related to the business outcome and define requirements for the data product and the solution architecture.

In Phase III, the consolidated solution requirements are mapped to the technical capabilities provided by the Data & Analytics Capability Model and aligned with potential software solutions. Also, the use case categories & patterns should be reviewed to check if related reference architectures, especially SAP BTP reference architectures fit. The results of these activities could be architecture options that need to be assessed and evaluated. The preferred architecture option could certainly be validated by a proof-of-concept to ensure feasibility.

Finally, Phase IV deals with the impact to organizational skills and data governance processes that might be affected. In a last step a timeline for implementation of the target architecture and organizational changes is created in the form of a roadmap (high level timeline) or a detailed project plan.

The methodology is rather comprehensive and needs to be tailored to the scope of the investigation. For example, if business outcomes are clear the focus should be on Phases II and III while further analysis described in Phase I is not necessary. On the other hand, if the focus is on the execution of a data strategy that encompasses a large data landscape and several functional areas then Phases I and IV should be managed comprehensively. Also, the adopter of the methodology can adapt the approach to fit the preferred project methodology (agile vs. classic).

What’s next

In case you are interested please reach out to sap-data-analytics-methodology@sap.com to get invited to our SAP Build Work Zone workspace to get access to the presentation and further assets like templates.

Please check also the detailed blog from Alexander Bange about:

Assigned Tags

      16 Comments
      You must be Logged on to comment or reply to a post.
      Author's profile photo Tobias Mache
      Tobias Mache

      Hello Fabian,

       

      these are amazing news and in my opinion the right step in the right direction.

      i want to join the new Workzone workspace but unfortunately the Mail-Adress is not valid.

       

      Could you send me the right one or make an update in blog?

       

      KR Tobias

      Author's profile photo Fabian Lehmann
      Fabian Lehmann
      Blog Post Author

      Hi Tobias,

       

      just fixed it is: sap-data-analytics-methodology@sap.com

       

      Thx for the hint!

       

      br,

      Fabian

      Author's profile photo Tobias Mache
      Tobias Mache

      Thank you for you fast response.

      The Mail is on its way and i am more than ready to join the workspace 😎

      Author's profile photo Fabian Lehmann
      Fabian Lehmann
      Blog Post Author

      Hi Tobias Mache ,

      good to know 😉, we try to sent out the invites later today.

      thx and br,

      Fabian

      Author's profile photo Luc VANROBAYS
      Luc VANROBAYS

      Hi Fabian, good vibes but email address is indeed Invalid email address

       

      cheers

      Author's profile photo Fabian Lehmann
      Fabian Lehmann
      Blog Post Author

      Hi Luc,

       

      yes just found a typo, its: sap-data-analytics-methodology@sap.com

       

      thx and best,

      Fabian

      Author's profile photo Antonio Carlos Murayama
      Antonio Carlos Murayama

      Good explanation and presentation Fabian.

      SAP Customers is looking ahead of S/4HANA.

      Congratulations.

      Author's profile photo Fabian Lehmann
      Fabian Lehmann
      Blog Post Author

      Hi Antonio Carlos Murayama thx for the kind words ... it's teamwork o;) , Kudos goes here especially to my colleague Alexander Bange !

      best,

      Fabian

      Author's profile photo Maria Villar
      Maria Villar

      Hi Fabian and Alexander ,  With my experience as a Chief Data Officer and my current role advising NA customers on their data strategy,  I am glad to see SAP offer this advisory.  It is the trending operating model that CDOs and CDAOs are moving to as the operating model to drive value.

      How can I understand more about the organization and governance capabilities that you recommend in this advisory ?  This is a topic I cover extensively with my  customers and we should align our best practices?

      I also sent an email to join the Work zone

      Author's profile photo Peter Baumann
      Peter Baumann

      Hi Maria Villar !

      I would also be happy to hear how this new approach aligns to your Masterclass.

      Author's profile photo Maria Villar
      Maria Villar

      Sure Peter.  Let's set up a meeting to exchange approaches.   Do you want to do from your side?   I'm on the east coast of US.  I should have time next week

      Author's profile photo Peter Baumann
      Peter Baumann

      Oh, nice! Would be happy to have an exchange. But initially I thought about to hear from you here how both approaches fit together. But if you would give me a little bit time to organize it I would be happy to be in a discussion. I will contact you via LinkedIn.

      Kind regards,

      Peter

       

      Author's profile photo Alexander Bange
      Alexander Bange

      Hi Maria and Peter,

      we are still in the process of developing the content and approach for data & analytics organization and governance part of the methodology. Therefore we would appreciate to exchange with you on your experience on that matter. So please involve us in your discussion.

      Thanks indeed.

       

      Alex

      Author's profile photo Maria Villar
      Maria Villar

      hi Alex,   When Peter and I meet,  we will include you.  The governance of data products is very important

      Author's profile photo Swapnil Tholiya
      Swapnil Tholiya

      Thanks Fabian for informative blog. I see this very relevant as customer needs are shifting towards 'Data Products' and 'Business data fabric' architecture. I have already submitted my interest in joining work zone in the updated email address shared above. Please accept and send me the invitation.

      Author's profile photo Bella De Freitas
      Bella De Freitas

      Hello Fabian,

      This is excellent news - thanks very much for sharing.

      Looking forward to what seems to be very important content to accelerate efforts.

      Have sent an email to the email address.

      Bella De Freitas