Replace your SAP BW by leveraging Simplement and the Microsoft Azure Data Stack

Hi everyone! Let me introduce myself. My name is Alp Kaya. I work for Microsoft as a Data & AI technical presales in Ontario. This is my first post of many to come… enjoy!

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Objective of the Article?

SAP ERP is one of the most widely used business applications in Large Enterprise (LE). It is great piece of software for business processes and so wide spread in the market that 2/3 of the world’s GDP runs through an SAP system. However, one of things it is not known for is its ability to allow users access to the data and enabling analytics on the ERP system. SAP – recognizing this as a short coming, developed an application called SAP BW (Business Warehouse) which is a prebuilt proprietary Data Warehouse application. The licensing for the BW application is free so long as you have users licensed on SAP ECC. SAP BW solution provided SAP customers standard extractors and prepackaged analytics/reports that would read/extract directly from you ECC system (+ other data sources as well) and load SAP BW analytics structures. The prepackaged and out of the box analytics reports would fulfill common reporting requirements such as Sales, A/R, A/P, Financials, etc…However, the SAP BW system is based on the same proprietary SAP ERP platform Netweaver and ABAP. The overall market and customer perception SAP BW application has been luke warm at best – there are customers who absolutely love BW and others who refuse to leverage it and would rather spend the energy and money and build their own.

SAP recognizing the marketplace perception and attempted to modernize SAP BW developed with an in memory DBMS called SAP Hana. SAP Hana allowed SAP BW (+ SAP ECC in subsequent releases) application to run on top of it. In the latest reincarnation, SAP has announced a new transactional product (S/4) but has not been widely adopted yet. The predominate use case for SAP Hana has been to move SAP BW workloads onto SAP Hana. The SAP Hana solution enables the SAP ERP or SAP BW in memory and hence was able to accelerate the data access to business users. In addition, with SAP Hana, a very SQL like interface for the SAP system and this really simplified access so long as you have the Hana Enterprise (i.e. non-runtime). Some customers chose to deploy SAP Hana as a side car and replicated data from SAP ERP straight into it via SLT and other tools. This deployment model constituted a full use (non-runtime license). And although SAP Hana is a great platform, it is a very expensive software license and requires a very expensive hardware appliance. It’s not unusual for customers to spend over 7 figures on licensing and hardware for a couple of TB of Hana.

Overview and the Challenge?

Most recently, I have had the opportunity to work with a customer who has a multi-terabyte ECC and an SAP Hana side car deployment. This customer’s preference was to build their own data warehouse (instead of using SAP BW) via SAP Hana side car. This customer mightily struggled with getting access to Financial Reporting out of their SAP ECC system and by struggled, I mean:

  • It took more than 6 months to build a baseline Financial Income Statement
  • Several years to complete the finalized Financial Income Statement (albeit the final Financial had over 200 measures that included several this period vs prior period vs same period prior year and all of the % increases/decreases of each – which are very computationally taxing)
  • Cost several million dollars to generate and maintain this one single Financial Statement report (for a variety reasons from data integration into SAP Hana via SLT & Data Services, Calculation Views on top of Calculation Views, and the general complexity of the solution)

This customer was wondering if there was a better, easier and more cost effective way to do this both from a licensing, hardware, and resourcing perspective. Working closely with this customer, we engaged in a 6 week project and leveraged an ISV solution called Simplement which produced some incredible results.

What does Simplement Do?

Simplement is a metadata driven solution that comprehends customer's SAP ERP including all custom Z objects and automatically transforms the SAP data and exposes the underlying tables via a common SQL interface. The Simplement solution first takes the underlying SAP tables, de-clusters SAP cluster tables, de-pools SAP pooled tables, and translates German language SAP columns/tables into English and makes them available as regular tables in Microsoft SQL DBMS. The Simplement Data Liberator (core component of the Simplement solution) also automatically manages SAP hierarchies and allows you to automatically inherit your existing SAP security model to the Liberated data. So, for customers who have large user communities where security has already been or for customers who have well defined hierarchies and want to continue leveraging them, these are all cascaded to the SQL world without any re-work.

Once this is done, all of the data in SAP can now easily be queried via a very common non-proprietary SQL language on the Microsoft SQL DBMS. Simplement then provides out of the box multi-dimensional views (think OLAP) into the data in the form of in memory Microsoft Analysis Services Tabular models. Microsoft Analysis Services Tabular is a multidimensional in memory analytical structures and can be thought of as a competitor to SAP Hana. Furthermore, the Simplement solution provides 9 multi-dimensional Analysis Services Tabular LOB models (known as “Smart Starts” covering areas such as S & D, GL, A/R, A/P, COPA, and others. Finally, to get you going with the Analysis Services Tabular models, the Simplement solution provides a prebaked PowerBI reports for each of the different smart start areas. You can use PowerBI to build management reports, and your company analysts can also connect Excel directly to the Tabular Smart Start model for deep analysis. The Data Liberator can also feed the transformed SAP data to Azure Data Warehouse, Machine Learning, Cognitive Services, etc.

Key Components and Highlights of The Solution


Key Highlights of the Solution

1. Out of the box Microsoft SQL Server that contains the SAP data in a SQL table format. With SQL, SAP documents can be searched from a variety of methods. For instance, PowerBI or Excel can be connected and be used as front end to search for any SAP document or analysis can be done straight on the SAP data in SQL. In addition, with Microsoft SQL 2017, both Python and R can be leveraged to execute statistical and data science packages without having to export to a separate package.

Lastly, the Azure Search as a Service functionality can be used so that “search” can be applied on SAP data in the SQL DBMS.


For instance, imagine navigating your customer data or part masters data in a ‘google’ style search. The image above is an example of Azure Search as a Service with the following features turned on providing a rich UI experience on the SAP data:

§ Full text search is a primary use case for most search-based apps. Queries can be formulated using a supported syntax.

§ Search suggestions can be enabled for type-ahead queries in a search bar. Actual documents in your index are suggested as users enter partial search input.

§ Faceted navigation is enabled through a single query parameter. Azure Search returns a faceted navigation structure you can use as the code behind a categories list, for self-directed filtering (for example, to filter catalog items by price-range or brand).

2. Out of the box, the Simplement solution provides several in memory Microsoft AS Tabular models such as S&D, General Ledger, COPA, A/R, A/P, Inventory, Asset History, etc… These models provide transactional facts, conformed dimensions, and key measures for your SAP data. In addition, using the DAX language in AS Tabular, additional KPI and measures can easily be created. One of the powerful features of the DAX language is the ability to easily create key measures like this period vs prior period or this period vs same period last year. Often, this type of requirement takes long periods of time to develop in other tools, but this is an inherent feature of the AS Tabular solution.


3. Simplement provides out of the box PowerBI reports for modules like S&D, General Ledger, COPA, A/R, A/P, Inventory, Asset History, etc... So, various LOBs can get access to the SAP data and do in depth analysis (drill up/down and across) without having to do any data integration or custom development. Crucial SAP data elements are exposed as prebuilt PowerBI dashboards and reports. Lastly, this content can further be customized with additional calculations and different visualizations.


4. Once the data is in the Microsoft Cloud (i.e. Azure), the possibilities become endless. For instance, IoT Hub can be leveraged to pull in terabytes/petabytes of data and marry that back with Asset/maintenance data from SAP. Or, Azure ML can be leveraged to apply Machine Learning on the data with endless possibilities like predictive maintenance, financial forecasting, and others. The diagram below depicts some of the possibilities once you are on Azure:


Project Results

1. Within a week a fully functional AS Tabular GL Model on commodity hardware on Azure

2. A baseline Financial Income statement within a week after accessing SAP ECC with over a 100 key relevant measures out of the box

3. Leveraging the Azure Data Stack and applying advanced analytics via R and forecasting terabytes worth of Financials within a few minutes

Final Thoughts

Simplement is a great way to provide analytics and easy ad-hoc requests to SAP ERP systems. Simplement works completely transparent of the underlying databases - even if the SAP ERP system is running off Hana. Finally, the Simplement solution provides the out of the box SQL DBMS, Analysis Services Tabular (in-memory) running on commodity hardware, and PowerBI content to get you started. This also unlocks the ability to take a traditional SAP customer and move them to Microsoft Azure – opening with it all that Azure can do. For instance, applying Azure Search as a Service to SAP documents, applying Big Data or IoT, and Machine Learning to SAP ERP data along with elastic scale up/down of the cloud.