Real learnings from SAP Datasphere customer roadshows, modernizing Data and Analytics
In this conversation with Buntic Georgian, data strategist and analytics advisor from Applexus Technologies, we’d like to shine a light on some of the experiences and customer conversations during the recent SAP Datasphere roadshow events in North America. Have a listen:
SAP: Buntic, you engage with SAP customers all the time, and you advise them on their Data & Analytics transformations and initiatives. Recently, you took part in several customer roadshows in Canada and the US – what was the most surprising thing you’ve learned?
Buntic Georgian: Great question – one surprising thing for me was how most organizations are struggling to transition from reporting to analytics. Lot of these companies have active analytics programs at varying degrees of maturity; however, they are still firmly stuck in the reporting world.
Their analytics programs are still delivering reports and dashboards that deliver information and analysis in hindsight and not necessarily delivering insights that drive action.
The market environment of today requires an agile and flexible approach to data and analytics. It requires delivering insights to decision-makers at the point of decision making. It requires instant access to trusted data. More importantly, it requires integrating data from internal and external data sources, sap and non-sap data sources, structured and unstructured data.
The surprising thing was although most organizations recognize this reality and despite extensively investing in D&A capabilities, they are not able to transform their reporting processes. They deliver reports that provide data in hindsight. They still deal with all the data silos that leads to multiple versions of the truth, and they struggle to transition to analytics that deliver actionable insights.
SAP: How do you start turning the conversation to modernization?
BG: The good thing is that most of these customers realize that they need to transform their D&A capabilities, however they are either constrained by their existing investments or lack of clarity on the roadmap for their analytics platform.
To help customers navigate these questions, we at Applexus have developed a framework, or you can call it a playbook, for Data & Analytics modernization, where we have consolidated all the questions and discussions with the customers into 5 use cases for SAP Datasphere.
SAP: What was one of the concrete examples where you heard about a challenging customer situation, and you could sketch out a transition path to address the challenges? One of the conversations that happened in the corridors between presentations…
BG: One of our first roadshows, a major Oil & Gas Services company approached me with an interesting question. This customer had a large SAP BW installation which was over 50TB in size and their goal was to migrate a cloud data warehousing solution, mainly driven by the high cost of infrastructure and system maintenance for their SAP BW solution. Additionally, their business was asking for more agility and self-service from their D&A solutions and SAP BW with its rigid data models was not able to deliver the agility they were looking for.
So, coming into the roadshow, their preferred approach was to migrate all SAP BW content into their existing Databricks platform and then retire BW. However, as they learned more about the open and flexible architecture of SAP Datasphere, they started reassessing their approach right there at the roadshow.
SAP: So, this was a situation where more information about SAP Datasphere lead to a change of approach – even for such a large deployment?
BG: Right, because their scenario fit very well into a couple of use cases from our playbook. In summary, our conversations centered around three aspects –
1) the risk of downloading data from SAP applications into a data lake without all the business context of SAP business processes
2) the ability to reuse their existing data models by leveraging BW Bridge in their migration from SAP BW to SAP Datasphere
3) a hybrid architecture where SAP Datasphere can be integrated with their existing Databricks solution to provide a unified data platform.
With this approach, the customer would get the best of both worlds i.e leverage BW Bridge, Datasphere native connectivity with S/4 and ECC, and extensive business content available to design a data and analytics solution that is aligned with SAP business processes and then leverage Databricks for non-SAP, unstructured and streaming data. In this scenario, Databricks would be their advanced analytics solutions.
SAP: Recognizing the additional value of SAP Datasphere meant that they keep it running in hybrid mode and transition at their own pace. Impressive – do you have another one like that, maybe a different angle?
BG: Sure – another interesting conversation was around the concept of data products and data mesh: A large Media and Advertising company came up with a unique requirement for their D&A modernization.
This media company is a decentralized organization with a central holding company headquartered in NY and then about 200+ independent agencies spread across the world.
So, their challenge was to deliver a high level of autonomy to the business to drive their own data and analytics, so that insights can be contextualized to their local scenarios. At the same time, they wanted to ensure that the enterprise data is made available to the local agencies in a trusted environment.
In this scenario, we recommended a distributed data process and architecture based on the data mesh concept. SAP Datasphere with its open architecture provides the capabilities to build data products that can be published in a data marketplace for reusability and local contextualization.
SAP: That sounds like a standard requirement of making the LOBs more self-sufficient – what’s different here?
BG: With this approach, central IT can publish a certified data product in the marketplace, then a LOB can consume and enrich the data product, publish it back to the marketplace for the local agencies to consume.
The local agencies can then contextualize the data product to their scenario for end user analytics. An effective distributed governance model is key to making this model successful.
In our view, this is a very innovative approach to delivering LOB autonomy with data and analytics and the key is to manage data as a product and not data as a project.
For this company, we anticipate major benefits from this approach namely, speed to access data, reusability of data (reducing duplication), self-service capabilities and ability to deliver real-world contextualization.
SAP: I get it – data as a product: that’s a bit ahead of the curve, but I trust we’ll see more of that in the future as customers start to consider their data not just from the point of reporting.
BG: Absolutely. One thing I wanted to mention is that for customers who are considering a cloud-based analytics solution like SAP Datasphere, it is a great opportunity to rethink their approach with data and analytics. This is indeed a great opportunity to transition from reporting to analytics. SAP Datasphere with its open and flexible architecture can be a key enabler for this transition.
SAP: Thank you so much for sharing your insights and some of the key experiences. If some of our customers are getting more interested and want to contact you, they’ll find the link to your site just below.
BG: Thank you, Karsten. Enjoyed our conversation!
Applexus is an SAP Gold partner operating out of North America, the United Kingdom, India, and Sri Lanka.