Creating value with business analytics & data engineering through well-founded decisions

Valuable insights from data only arise when relevant information is identified, integrated and analysed in a targeted manner 

In practice, companies often find it difficult to coordinate requirements between business and IT, as the two speak different languages. However, a common understanding is required to identify and merge the right data from heterogeneous systems. A lack of data integration leads to inconsistencies and makes it difficult to gain an overview of data and its dependencies. As a result, the data can neither be used for complex specialist analyses nor for independent ad-hoc analyses by specialist users. In addition, the integration of analysis results into business processes is often not optimally implemented, which limits the usefulness of the insights gained.

One of the biggest challenges when using AI lies in creating a solid data basis. Data must be of high quality, consistent and up-to-date in order to guarantee reliable AI results. In addition, comprehensive data integration is necessary to ensure that all relevant data sources are taken into account. Without this solid data basis, the potential of AI in the business use case cannot be realised.

This is why we deal with the following questions in the area of business analytics and data engineering:

• How can relevant data sources be identified for an analysis and how can this data be technically extracted?
• How can a solid data basis be created that enables efficient analysis and the use of AI through rule-based processing and data modelling?
• How can data be translated into comprehensible, business-relevant data products in order to maximise the added value for specialist departments?
• How should the already prepared data ideally be evaluated in rule-based analyses and used as part of the application of AI?

Our focus is on developing customised analyses that are geared towards your existing (data) strategy and organisational structure. With a combination of technical expertise and in-depth specialist knowledge, particularly in the areas of finance, compliance and performance, we support you in extracting insights from data to create sustainable added value for your company.

We support you with your challenges by translating business requirements into technical solutions and providing end-to-end approaches. With modern data architectures and an integrative approach, we support you in gaining valuable insights from your data.

Distributed data (sources) can be brought together, complex data structures harmonised and transformed into valuable insights. The existing (data) strategy, technical and regulatory requirements and the existing data architecture form the basis for defining the scope. This triad enables a well-founded gap analysis between the requirements of the desired analysis and current data utilisation. A target picture and specific fields of action can be derived from this. As part of the scoping process, relevant use cases are defined, technical analysis and reporting requirements are recorded and the target image is systematically developed.

Modern data architectures address heterogeneous IT landscapes and decentralised data storage by establishing a single point of truth. This enables the efficient collection, storage and historisation of data - as the basis for consistent and reliable information. Automated data flows and controlled data completeness in the ETL process support efficient data transformation and provision, while near-real-time data provision enables time-critical analyses. Our expertise includes the use of standardised tools for extracting ERP data and non-ERP data as well as the development of on-premise and cloud-based data platforms.

Thanks to our extensive experience in the core operational processes of companies, especially in the areas of finance, compliance and tax, we can analyse and optimise requirements in a targeted manner.

Companies are supported in the implementation of current requirements such as the fulfilment of reporting obligations with clearly defined content specifications. A common data model, tailored to the analysis requirements, creates the basis for transparent and comprehensible analyses - supported both internally and externally by AI.

Business analytics solutions are implemented quickly and effectively, supported by a broad network of experts and a deep understanding of processes. The aim is to measurably increase the value contribution of data-driven decisions.

Our reporting solutions offer far more than just pure data processing – they create real added value. Whether it's classic data preparation from the source system to rule-based analytics use cases, data transformation from raw data to comprehensible data products for use via self-service or the creation of a reliable data basis for AI-based applications, we always use the most suitable analysis method for your use case. The interpretation of the results is supported by our in-depth expertise. The results of the analyses are prepared in a structured manner for downstream evaluation and reporting. In collaboration with technical experts, suitable measures can be derived in a targeted manner.

The success of our projects is based on interdisciplinary teams with a combination of technical and specialist expertise. Whether over the entire project life cycle or in individual phases - from requirements analysis to the integration of use cases - the focus is on sustainable solutions.

Thanks to extensive project experience and the use of proven methods, advanced analysis techniques can also be combined with in-depth industry knowledge. As an alliance partner of leading technology providers, we have in-depth technology knowledge and rely on proven best practices; if necessary, we can also draw on their expertise.

Our extensive, cross-industry experience and our broad network of SMEs enable us to offer solutions that are tailored to the specific needs of our customers. We create the basis for sound analyses and data-driven decisions that offer sustainable competitive advantages.