Data workshop

Ubiquitous - The digital transformation

The digital transformation permeates the economy like no other trend topic and polarises existing business models worldwide. Existing IT architectures are being restructured, processes rethought.

In the data workshop, the basis for sound decision-making and strategic corporate management is created by realizing a complete overview of historical and current corporate data.

The data workshop offers individual approaches to solutions that are oriented to the respective requirements.

Our experts at the data workshop will provide you with competent and efficient support:

Data warehousing as a basis for reporting and planning

Industrialised reporting incl. planning functions for controllers (in Excel and on the web).


The right warehousing strategy makes visualized mobile dashboards for management possible.

Empowerment of your Data Analysts & Scientists

Advanced-analytics options for the work of your data analysts and data Scientists.


Data warehousing as the basis for automating and optimizing business processes using analytical functions.

Big data analytics visualization technology with scientist analyzing information structure on screen with machine learning to extract strategical prediction for business, finance, internet of things

The solutions of the data workshop

The data workshop specialises in the following SAP warehousing topics: (1) SAP Data Warehouse Cloud (DWC), (2) SAP BW ON HANA and (3) SAP BW 4 HANA.

SAP Data Warehouse Cloud (DWC)



Head of the Data Workshop

"We are the specialists for SAP's data warehousing solutions. 

My team was the first consulting firm in the world to license and successfully introduce the Data Warehouse Cloud (DWC) to a customer. Therefore, we have special expertise in the area of DWC.

My team and I look forward to hearing from you."

Paul Vatter, Head of Data Workshop

Paul Vatter Head of the Data Warehousing Competence Centre at s-peers AG
Paul Vatter
Head of Consulting

FAQ Data Workshop

A data warehouse is a company-wide database that integrates data from various heterogeneous data sources and makes it available for analysis and evaluation purposes. A well-designed data warehouse delivers high data throughput, performs queries quickly and offers end users the ability to break the data into smaller pieces to view it from different angles.

  • Topic-oriented = The data structure in a DW is used to support management decisions and is not designed to support operational business processes. Data is stored according to specific objects such as customer or product. Decision makers analyse the data of these objects and make their decisions based on them.
  • Integrated = The data is integrated from various heterogeneous data sources into a common dataset. For the integration, the data must be transferred into a uniform data structure and a common data format
  • Non-volatile = In a DW, the stored data is neither deleted nor modified. Only to correct errors can the data in a DW be changed. In the course of time, a historical data stock is thus created, which is composed of the data of the individual operative application systems
  • Time-related = The data are loaded into a DW at different times. The newly loaded data records do not overwrite the old data stock, but merely supplement it. This creates a snapshot of what is happening in the company each time. Accordingly, the data can be compared over different periods of time and trends can be identified.

Business Intelligence (BI) includes access to information with the help of IT systems. The analysis, evaluation and presentation of business-relevant company data should provide insights into the current state of the company. These insights contribute significantly to strategic and operational decision support. The goal is to provide management with high-quality data and to support them in their decisions in the best possible way. For the technical implementation of a BI solution, a DW is necessary, which forms the foundation of every BI solution.

A database management system - also called a database system for short - has been designed to manage large amounts of information. The primary goal of a database system is to provide the most efficient and convenient way to store and retrieve database information. A database system is an organised collection of electronically structured information or data stored in a computer system. The core task of a database is to store large amounts of data efficiently, permanently and without errors, and to provide the required information as needed.

The name cloud computing is a metaphor for the internet. The internet is typically represented in network diagrams as a cloud. The cloud symbol represents unknown network infrastructures that make the network work.

Probably one of the most currently recognised definitions of cloud computing is that of the National Institute of Standards and Technology (NIST), which is also often referred to in specialist circles. NIST defines cloud computing as a model that enables ubiquitous, convenient and on-demand network access to a shared pool of configurable computing resources (e.g. network, servers, applications, services and storage). These computing resources can be rapidly provisioned and released with minimal management effort or interaction with the service provider. The cloud model is composed of three service models (Infrastructure-as-a-Service, Platform as a Service and Software-as-a-Service) and four deployment models (Private, Public, Hybrid and Community Cloud).

In contrast to cloud computing, solutions are also made available on-premises. "On-Premises" in German means something like "on one's own premises" or "on site". The description of on-premise refers to the use of one's own servers and IT environment. While access in the cloud takes place via the internet, on-premise solutions are operated locally on one's own computer.

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