Business Intelligence

SAP Data Warehouse Cloud, it’s time to talk about it…

I’ll admit I haven’t posted too much about SAP Data Warehouse Cloud (DWC) over the last few years. In part it was due to being heads down working on projects, managing a BI practice, and lacking time to see what makes it work. However, I have had just enough time over the last few months to really dig into the platform and see what it can do, and I am quite excited about what I learned. Frankly, the experience was much like the first time I did the same with SAP HANA some 10 years ago. As a result, I plan to ramp up blogging again and share my thoughts on the platform. To start things off, l will list out a few items I think will really resonate with clients who are seeking a quick overview of what makes DWC unique and exciting. Below are a few of my thoughts on DWC.

Replication of data

I really like how simple DWC makes provisioning and replicating HANA DB tables, S4/HANA CDS Views and ECC ODP extractors into the platform. The architecture and user interfaces are very well put together, simple to setup and use. Replication is a critical component or requirement in my modern agile EDW methodology. While this was achievable with SLT and a HANA database, the architecture was a bit much to setup and manage. With DWC, only two lightweight agents (DP Agent and SAP cloud connector) are required to replicate data securely into DWC. This light architecture makes managing the architecture much simpler. Couple that with DWC being a SaaS platform, organizations will be able to spend more time developing and innovating and less time maintaining and upgrading.

Focus on End Users and IT developers

DWC’s UI is well suited to support advanced IT developers and self-service business users. The data builder, business builder, focus on meta data and space management work well together in producing a shared environment where both IT resources and business users can model and blend data. I can really see how this type of experience can bring about a simpler data governance process for organizations.

Open Connectivity

DWC offers a large array of support for both SAP and non-SAP source systems.  Data can be provisioned from many modern on-premises databases and popular cloud data platforms. With a HANA ODBC client, many data platforms and BI Tools can easily consume data from DWC. Combine this with the fact that you can easily replicate and model data from SAP systems, you will find it an ideal platform to expose SAP data and models to other platforms and tools. 

The BW Bridge

The BW Bridge is a fascinating add-on to DWC. It offers a literal “Bridge” where organizations can leverage their past investments in SAP BW by moving Extractor code, aDSO, transformations, BW master data and composite providers to the cloud. Not only can you move them to DWC but we can continue to load data from SAP systems as if it were a normal BW4/HANA system. Based on SAP’s road map, many BW Queries will soon be supported in the platform. The BW bridge is not a full implementation of BW4/HANA in the cloud. You can think of it as a partial implementation where supported BW models can be used as data sources in DWC. Once exposed to DWC, you will be required to further model them into DWC compliant models. However, if an organization has value in the current BW models and queries, the BW bridge is a quick and easy way to get them started with DWC. The BW Bridge also has standard BW4/HANA content that can be deployed for those seeking a quick way to get a “greenfield” implementation of DWC up and running.

Model with SQL

DWC offers the ability to model data using SQL Statements and Scripts. While the graphical modeling tools are great to have, being able to model in SQL and even port SQL code over from other platforms, make DWC easier to adopt and more flexible for BI and EDW developers well versed in SQL coding. This might seam like an odd feature to call out, but legacy solutions like SAP BW were centered more around ABAP development and GUI wizards for data modeling. SQL is a more universal data modeling language which makes it easier for a general BI developer or advanced power user to work in DWC.

Flexible Storage Tiers

When source tables and CDS Views are initially imported, no data is moved to DWC. While you can query this virtual table entity within DWC, it is initially federated from the source in real-time. You can later choose to batch load the data or replicate the table / CDS View into disk bound storage within DWC to improve query performance. Furthermore, you can choose to have that same data bound to in-memory storage with the toggle of a button. This flexibility allows you to define a simple, per table entity, storage tier for data. Organization can even incorporate the SAP HANA Cloud Data Lake into their cloud landscape giving them even more cost-effective storage options for structured and unstructured data.

HDI Container

DWC supports the deployment of a HANA HDI container. Within this container and using BTP developments tools, organizations can model data using for example SAP HANA XSA Calculation Views. Organizations could even import existing SAP HANA XSA HDI container content into the platform when migrating from an existing HANA DB environment. This is yet another way organizations could migrate existing content into DWC to rapidly get results.

In the upcoming months, I plan to release more blogs and content on DWC. I look forward to hearing about you experience in the comments below.