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The Business Analytics Platform ensures a clean data basis and forms a reliable foundation for data-driven business decisions. With IBsolution’s holistic framework, companies can address and overcome their most pressing data challenges.
The holistic approach takes into account not only technological aspects, but also the organization and the people without whom a data-driven company cannot function. Accompanying Organizational Change Management is an indispensable component of the Business Analytics Platform and ensures that employees accept the changes and that a new (data) culture can emerge in the company.
The Business Analytics Platform consists of different layers that build on each other. Companies usually have a variety of data sources. These can be on-premise or cloud systems from SAP or other providers. The data is available there in structured or unstructured form. The Integration Layer brings the data from the source systems to the Data Layer, where it is persisted and stored.
The data layer is usually distributed heterogeneously – across SAP and non-SAP systems. Among SAP systems, SAP BW on HANA or SAP BW/4HANA are the most common in the on-premise area and SAP Datasphere in the cloud area. The non-SAP systems are typically SaaS applications that are part of at least one of the three major hyperscalers Microsoft Azure, Google Cloud Platform and Amazon Web Services (AWS). The Virtualization Layer is necessary to create a unified view of the heterogeneous data in the Data Layer so that the various reporting disciplines can build upon it.
The Business Analytics Platform is flanked by the topics of (master) data governance and data mesh. To ensure that the insights and decisions derived from corporate data are reliable, the data quality must be high across the various layers. Data governance provides the appropriate structures and processes to ensure permanently high data quality. A data mesh creates the organizational basis for a different way of handling data in the company by decentralizing responsibility for the provision and quality of data to the business departments.
Identification of current challenges in data management
Evaluation of the benefits of a central data platform
Analysis of the data strategy
Fit-gap analysis
Analysis of organizational structures and stakeholders/user groups with regard to opportunities and obstacles
Analysis of responsibilities for data and processes
Creation of a capability map
Preselection of technical options on the market (SAP and non-SAP)
Preselection of data platform components and matching with existing systems
Definition of a use case for a potential prototype
Definition of roadmap, milestones and next steps
Overview of the Business Analytics Platform
Outline of the target system landscape (including all satellite systems)
Structure and possible components of the platform with special consideration of the following aspects:
Integration layer: Connection of the hybrid system landscape (SAP BW or SAP BW/4, SAP S/4HANA, SAP BTP, Hyperscaler etc.) and other systems
Development of a solution architecture taking into account the company’s requirements and IT strategy
Definition of the user groups
Evaluation of the existing authorization concepts with regard to a revision
Development of a strategy for the transformation to SAP BW/4HANA, SAP Datasphere or another BI solution
Evaluation of the findings from the previous system analysis
Definition of the requirements for the future data warehouse
Distribution of reports to the individual components of the new data platform
Comparison of the conversion types to SAP BW/4HANA and/or SAP Datasphere
Determination of the appropriate conversion type
Evaluation of the results from the readiness checks
Creation of a uniform view of the further procedure and the project plan
Differences in reporting between SAP BW/4HANA and SAP S/4HANA Embedded Analytics
Content of reporting in SAP S/4HANA Embedded Analytics
Discussion of self-service approaches
Discussion of the use of suitable front-end tools
Modeling with CDS views as a holistic data model
Authorizations (optional)
Overview of the existing data lakes in the company
Analysis of current objectives and data usage
Determination of user groups and user behavior
Integration scenarios with other tools/systems
Discussion of existing governance concepts
Explanation of the current challenges in terms of governance
Evaluation of existing authorization concepts
User groups and user access
Definition of data ownership
Presentation and discussion of the data mesh approach (content and objectives)
Improving data quality
Data lifecycle management
Data (access) security
Development of the future target status in terms of data governance
In the various workshop modules, we jointly analyze your current system and process landscape, define your requirements, identify potential weaknesses, design a suitable architecture with the appropriate technologies and create a cut-over plan. The result of each workshop is a coherent overall concept that defines the relevant fields of action and serves as the basis for further implementation. As an experienced partner for business intelligence as well as data & analytics, we are also at your side for the subsequent implementation project.
Access to high quality data and the ability to turn it into useful insights is critical to business success. To get even more out of their data, companies that use an SAP BW system are particularly interested in setting up a scalable, decentralized Business Analytics Platform.
Data Mesh represents a paradigm shift and paves the way to a domain-driven data architecture. Each business department is responsible for the definition, quality, and creation of data from its own domain.
