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Data Engineering

Data engineering forms the basis for sustainable success in digitization – from data analysis to the use of AI.

Our expertise

A solid data infrastructure is the key to future-oriented business development. It facilitates everything from the creation of new value chains and well-founded decision-making using business intelligence to product personalisation and the use of artificial intelligence.

Opportunities for collecting data have increased rapidly in recent years. Almost any interface with a customer, a machine, or a product is also capable of capturing data. Maintaining an overview in this ocean of information requires concepts and competencies from a wide variety of areas that go beyond traditional software engineering.

To this end, therefore, we provide more than just the data streaming architecture. Organising, provisioning, managing, and integrating huge volumes of data requires intelligent data engineering which also takes into account testing, security, monitoring, and data quality.

To make our data engineering projects even more successful, we employ best practices from software engineering. This results in higher quality, robust data products which form the cornerstones of sustainable success.

As in classic software development, the architecture is also decisive for the success of a project when designing a data lake. With the right design, the data platform is not only stable, but also flexible enough to meet new use cases, such as in the areas of reporting or machine learning. At the same time, operating costs remain low.
With a cleanly designed architecture, we enable our customers to master challenges such as the DSGVO.
In projects, we gear our use of technology entirely to the requirements of our customers. In most cases, we accompany them from the conception phase through to implementation and further development.

for the success of a project when designing a data lake. With the right design, the data platform is not only stable, but also flexible enough to meet new use cases, such as in the areas of reporting or machine learning. At the same time, operating costs remain low.
With a cleanly designed architecture, we enable our customers to master challenges such as the DSGVO.
In projects, we gear our use of technology entirely to the requirements of our customers. In most cases, we accompany them from the conception phase through to implementation and further development.

Cloud-Migration
We gained experience in the field of Big Data at an early stage and are particularly experienced in setting up, designing and maintaining on-premise Hadoop distributions. Accordingly, we know the aspects of a cloud migration in detail and can evaluate its advantages and disadvantages individually and comprehensively.
During a migration, we ensure that the infrastructure as well as the data systems and use cases are implemented “cloud native”. In doing so, we fully exploit the advantages of the cloud. It is important to us that the migrated products can be used by our customers with the new technologies as before.

The EU General Data Protection Regulation (GDPR) is an important factor for the development of new solutions.
This has a massive impact on existing and new data platforms – starting with the compliant storage and provision of data and extending to corresponding authorization concepts and documentation.
A subsequent conversion is time-consuming and associated with additional costs if these requirements were not considered when designing the architecture. For this reason, we consider which regulations apply and how they must be applied in the individual solutions.

A high-performance data platform is the basis for successful data value creation. It enables teams to develop new products by giving them flexible access to the information and allowing them to expand it as required. In this way, a common platform also results in cross-team symbioses that can offer the company new insights.
We help teams with continuous quality monitoring so that they can work successfully and reliably load their data into the platform.
In addition, we enable flexible analysis of data by giving classic reporting solutions access to the data lake. This allows analysts to create reports and evaluations on the data. Complex machine learning products can also take advantage of a data lake, which can also store unstructured data such as images.

Data Engineering at inovex

Our offers and solutions that we use in the field of data engineering.

Case Studies

dm-drogerie markt: Development of a Fully Automated Data Centre for the Online Shop

When a major brand like dm strategically enters the online market, it creates high expectations. For this reason, their IT subsidiary FILIADATA, which has been responsible for all dm’s IT systems since 1988, launched a project in 2013 which was aimed at laying the foundations for reliable, fail-safe IT operations for dm.de. These included creating a large, fully automated Linux infrastructure in the data centre on which sophisticated web services like the online shop can be operated.

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REWE digital: Demand Forecasting for REWE’s Delivery Service

inovex and REWE’s collaboration in the area of supply chain optimisation has focused particularly intensively on REWE’s IT subsidiary, REWE digital.
This particular project involved developing demand forecasting for REWE’s delivery service, leveraging big data technologies to enable easy scalability.

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mobile.de: Use Cases for Online Portal Recommendations Using Data Products

mobile.de is a marketplace for the buying and selling of vehicles. Every month, the web platform draws 13.5 million visitors who can choose from the more than 1.6 million vehicles on offer. Each visit to the platform creates a stream of data which contains information about the demand for particular vehicles, the quality of the vehicles for sale, and user requirements. mobile.de wants to use this data to continuously improve the user experience for both vehicle sellers and purchasers.

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Arvato Bertelsmann: Optimised Fraud Detection in Microsoft Azure

arvato Financial Solutions is collaborating with Microsoft, Cloud and Big Data specialist inovex GmbH, and three pilot e-commerce customers on an innovation project to create a Big Data architecture based on Microsoft Azure. The team will use the project to evaluate how the combination of Cloud Computing, Big Data and advanced analytics can improve fraud prevention and facilitate the development of new financial BPO services.

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Technology Partners

Long-term partnerships for successful projects: we co-operate with a number of selected technology partners who offer our customers real added value.

Research Projects

Langjährige Partnerschaften für erfolgreiche Projekte: wir kooperieren mit einer Reihe von ausgewählten Technologie-Partnern, die unseren Kunden einen echten Mehrwert bieten.

Portraitbild von Dr. Dominik Benz
Dominik Benz
Head of Data Engineering
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Dominik Benz

Head of Data Engineering