SAP Datasphere: What’s the Steer on the ‘Sphere?

With the recent announcement of SAP Datasphere there are bound to be a lot of questions. Is this just a rebranding exercise for SAP Data Warehouse Cloud (DWC) or is it perhaps something more significant – an evolution of SAP’s strategic direction for Data and Analytics? What does it mean if I already have DWC or will this convince me to move to Public Cloud if I don’t?

The answers might not be evident from the headlines, so let’s have a look at what it is, and what it means for SAP’s customers going forward.

The Strategy

If you log onto Datasphere today, you’ll notice some new items on the left-hand panel and might wonder what the big deal is, but this wouldn’t explain SAP’s longer-term ambitions in this area. Leaving aside the shiny new name there are two key objectives lying behind this change:

1. Moving towards a Data Fabric approach. This is a term that’s been around 2016, but perhaps deserves a little explanation. It describes an architectural approach that provides a set of services to deliver data capabilities across a choice of endpoints – on prem data sources, cloud data sources, databases, APIs, Internet of Things etc – to simplify governing, accessing, integration and working with data, abstracting away where that data may sit. SAP were classified as a Leader in the Forrester Wave for Data Fabric in 2022, and the partnerships that they’ve announced alongside Datasphere (more on these below) are a further step on this journey and a real statement of intent about ongoing collaboration and integration.

Image courtesy of SAP

2. Consolidating SAP’s cloud offerings. Starting with the addition of Replication Flows (more on this below too!) more functionalities will be plucked from SAP Data Intelligence, until eventually Datasphere has parity with it on top of its other core functions. For DWC customers, this means a straight-up value-add: more functionality, same price. But this direction also helps simplify SAP’s data and analytics offering – in the future, rather than having to ask yourself whether you need Data Intelligence and / or Data Warehouse Cloud it should just be a question of choosing Datasphere and then using the functionality you need.

The New Functionality

The Datasphere Roadmap has several interesting items coming over the next year, but let’s focus on what went live the moment the announcement was made:

• Analytic Models. This is a true native OLAP object, allowing optimised querying of multi-dimensional data in a way that wasn’t available in DWC previously, and adding all the functionality you might expect alongside this – richer Measure modelling, time-dependency, etc. We think most existing customers will be tempted away from the DWC Business Builder to take full advantage of these benefits, but SAP also intend it to eventually become the sole consumption object within Datasphere so it’s worth considering your development in this area going forward.
• Replication Flows. Here’s the first of steals from Data Intelligence. Replication Flows are built for speed and ease in bulk replication use-cases, from multiple sources (SAP on-prem, HANA cloud and Azure) to multiple targets (HANA Cloud, HANA Data Lake Files, and of course Datasphere itself). They’re cloud-based, so don’t require a Data Provisioning Agent (DPA) to be in your on-prem landscape, and use Netweaver sources’ inbuilt DMIS functionality, meaning that for S/4HANA, BW/4HANA and fully patched-up ECC and BW systems, you won’t need a separate SAP Landscape Transformation (SLT) Replication Server. They can also use the source systems’ Operational Data Provisioning (ODP) framework so, unlike with DWC previously, these options can now be delta-enabled.
• Data Catalog. Another one from DI, this has come across from its Metadata Explorer and is meant to complement the existing Repository Explorer, but is meant for data consumers rather than developers as you control which data sets are published to the catalog. To help consumers find what they need, you can create Business Glossaries with defined Business Terms to give a clear and consistent understanding for specific business descriptions, KPIs to ensure everyone is measuring consistently, and Tags – labels which you can use to identify and search for certain types of data (for example, ‘Sensitive!’)

The Partnerships

The intention of the Data Fabric-centric approach is about being able to work better with external platforms and data sets – and it goes both ways. With this in mind, SAP have announced four initial principal partners (with more to follow), each bringing something to the table that compliments SAP’s offering with Datasphere:

• Databricks – offering a Data Lakehouse platform based on Apache Spark, this partnership brings bi-directional integration between Datasphere—with SAP data’s complete business context—with its Data Lakehouse platform on any cloud platform
• Confluent – a streaming data platform based on Apache Kafka, it will enable data in motion integration with real-time streaming data from and to Datasphere
• Collibra – a data quality, governance and catalog platform. They will bring bi-directional integration of their data catalogs with Datasphere to future-proof data governance, privacy, and compliance initiatives.
• DataRobot – a machine Learning platform, which will bring the ability to build powerful custom machine learning models on top of SAP Datasphere and bring that data back through into your Data Fabric.

There are many ways you can choose to implement a Data Fabric and hopefully Datasphere illustrates that SAP recognises this and are moving towards better integration of data between SAP and non-SAP systems.  Often it may be driven by the Data Gravity of your enterprise architecture – if the majority of your data is SAP then Datasphere may end up being your main point of entry with partners supporting it and feeding back into it, but if not then Datasphere can still play an important role by being the conduit to external partners’ platforms.

What We’d Like to See

These are all great steps in the right direction, but there’s always room for further improvements. Here are the things we’d most like to see from Datasphere moving forward:

1. Better Data Tiering management. SAP HANA Cloud has multiple data tiering options, but a simpler more user-friendly way of managing temperature would be appreciated. This has been a real success in BW/4HANA, where Data Tiering Optimisation (DTO) has made out-of-the-box temperature management easier than it’s ever been. While adding DTO to Datasphere’s cloud-based BW Bridge extension is in the roadmap for Q4 2023, we’d love to see something similar added for the core Datasphere modelling environment and being able to leverage the HANA Cloud Data Lake or other Hyperscaler offerings more simply.
2. Standard Content Models. Another advantage of the extremely mature BW line, this would be a great accelerator for existing SAP ERP customers, be they on-prem or having moved into the cloud. The Business Content is going someway to doing this but a more comprehensive library of data and business artifacts nearly out-of-the box would drive consistency, simplification and would greatly reduce time-to-value.
3. Improvements to ETL/ELT functionality. The eventual integration of Data Intelligence pipelines into Datasphere will be a welcome addition to help support more sophisticated transformation use cases. Getting the balance between enabling business users to self-serve whilst still allowing developers to create great solutions is key.

That’s a lot of information, so what does this all mean?

If your organisation is an existing Data Warehouse Cloud user, congratulations! You’ve already gained a lot of new functionality and improvements, at the mere expense of having to remember not to say ‘DWC’ anymore. And if you’re thinking of taking the leap? This makes the prospect a lot more tantalising – Datasphere is starting to reach the early-point of a maturity curve, adding in some of what’s missing and providing a clear way forward for the rest. Add to this the push for better integration with all the other quilt-patches in your Data Fabric, and SAP may have put a firm Data Stake (don’t worry, this one’s made up) in the ground of your enterprise architecture.

So where next?

If you think that a Data Fabric approach might be of interest for your organisation or would like to explore options for generating more value from your data then we’d love to speak to you.  Please complete the short form and we’ll contact you directly.  We’re currently working with several clients on Datasphere projects so we’d be happy to discuss some of the options available to you as well as give you some of our insights and real-world experiences into getting the most out of SAP Datasphere.  to allow us to share further details.

You can also meet up with our Data and Analytics experts, experience live software demonstrations, and to get hands on with the very latest SAP Data & Analytics tools at Transformation NOW! 2023, taking place on 27th September in London.  You can Register here.