Data Engineering & Data Transformation Robust Data Pipelines, Self-Service, and
Modern Architectures – From ETL to Analytics

With a GenAI bot for automated responses, Quirion speeds up support, eases the burden on teams, and boosts customer satisfaction. Fast. Scalable. Future-proof.

Imagine being able to analyse legal documents like NDAs in seconds – completely free from manual errors and endless hours of work. By leveraging AI and AWS Bedrock, we have developed a solution that automates the extraction of key contract information.

With an AI-powered platform based on Amazon Q, IceHawk UG optimises its scouting and controlling: relevant data is centralised, player and opponent analyses are automated, and decisions are made based on solid foundations. A step towards data-driven, future-proof club development.

Experience the future of sports data analysis with an AI-powered solution from AWS. The coaching staff and scouts can now easily ask questions like "Who is the best substitute for an injured player?" via voice query.

Through the new Data Governance Framework, including the Data Marketplace, a systematic improvement in data and metadata quality in the Data Lakehouse was achieved.

Currently, reviewing tender documents takes several days. AWS's Gen-AI solution offers significant time savings and enables faster decisions through clear executive summaries

The introduction of the Databricks platform at the municipal utilities enables the IT department to address all use cases from the specialist departments, break down existing silos, and strengthen the reputation of IT.

SilverRail Technologies aims to redefine the travel experience for its customers and has laid the foundation for a data-driven, AI-powered travel assistant.

Woodmark has supported NHD Beteiligungs GmbH in reducing operational effort through the use of automation in AWS. This resulted in improved operational processes, reduced downtime, and lower costs in the AWS environment.

Our client Tom Tailor was able to create a 'single point of truth' for business logic and KPIs with the migration and modernization of the Redshift data warehouse. This now enables more accurate data-driven decision-making.

A butcher shop lacks established branch and personnel reporting, and the branch managers are using an outdated analysis system. With the implementation of Amazon QuickSight, fast evaluations are now possible.

An internationally operating insurance group saves license costs through the introduction of Amazon QuickSight and can focus on the content thanks to structured data visualisation

The Bundesliga club was able to significantly improve data quality in the areas of athletics and scouting through centralized data visualization and the introduction of a QuickSight dashboard.

The goal of the software developer arcRider is to simplify the creation of Ninox database models in AWS with GenAI and to increase customer satisfaction...

The Faber Group BV offers pallet and pooling services. Due to the increasing complexity of supply chains and rising fuel prices, the company wants to optimize its route planning...

FinTech startup with 50 developers aims to improve customer satisfaction with product quality and enhance internal collaboration through the use of SAFe and SCRUM methodologies...

In the inside sales department, a five-figure number of email inquiries are received annually, which are processed with a very high manual effort...

Shared responsibility for complex processes by two different authorities with many manual processes, decentralized data storage...

Data from affiliate marketing, website analytics, and SEA are manually analyzed side by side...

The need for a data-driven automotive industry requires new data architectures in the vehicle and in the backend.

There is a need for a group-wide data warehouse as the foundation for further BI applications.

Desire for digitization, i.e., data-driven and automated customer advisory services in the healthcare sector...

The data lake is fed from various systems worldwide. Efficient utilization of the data lake therefore requires a company-wide, international data governance concept...

For the large data lake with many diverse and unstructured data, central management and a consistently established data governance are required...

The reporting should be made more efficient, enabling self-service analytics and relieving the IT department...

There is a need for detailed analyses and forecasts of purchasing behavior, particularly for predicting the transformation of visitors into customers...

The transportation company is looking for an automated, data-driven approach to assess the impact of individual construction projects on delays and optimize future planning.

Covid-19 requires the rapid digitisation of school education. The open-source services Jitsi and BigBlueButton (bbb) have proven effective, but they are not automatically scalable...

The sensor data is available in various formats and resolutions and cannot be used for real-time analysis and quality monitoring

Managing non-financial risks requires a new data strategy. IT and the compliance department are seeking a way to collaboratively and iteratively implement data-driven risk analyses.

Systematic use of vehicle data requires powerful cloud analytics, machine learning, and advanced visualisation.

Optimising the manufacturing plant requires the use of sensor measurement data from the production process in real time.

Real-time analytics are needed to effectively utilise the vast amount of machine data from the relevant production machines.

Market dynamics require greater innovation capability.

600 million data records of sales activities and purchase transactions.

Looking for a data hub that enables data-driven business models.

Various data sources should be consolidated into a strategic overall picture and allow for detailed analysis...

The system landscape for data analysis has become outdated and consists of isolated solutions...

Simulation of various fee scenarios considering multiple variables such as noise and pollutant emissions, noise classes, night-time and other surcharges.

Aluminium wheels are produced using the low-pressure casting process, and after casting, they undergo an X-ray inspection.

Geo-services have become essential for modern automobiles.

Vehicles can currently only use local sensors for information gathering.

Data from over 170 channels in a proprietary format need to be stored, processed, and visually analysed.

The driver assistance systems are to be enhanced and improved with insights from the sensor data.

A new Data Warehouse (DWH) is required for future bank management. The implementation will use the technologies Exasol and Tableau, supplemented by Jenkins and Docker for Continuous Integration (CI) and Continuous Delivery (CD).

Instead of time-consuming planning in Excel, both central departments and business units should be able to quickly and independently create analyses of the business plan and business performance in the future...

The organisational structures and project processes of the existing BI Competence Center conflict with the requirements of Data Science projects.

The analytical architecture landscape has reached the end of its lifecycle after 15 years of use.

Long production times (at least 9 months) require very accurate forecasting and planning of delivery quantities to avoid shortages.

The planning of approximately 8,000 development projects is carried out in various Excel-based applications.

Sales planning is carried out using Excel (across more than 20 workbooks).

Expiry of the existing contracts for maintenance and operations for the applications of the automotive bank.

Functional improvements are to be achieved for each market and vehicle model.

Hadoop development clusters distributed across multiple business areas.

The profit share in the After Sales segment for automotive manufacturers is over 50%. Therefore, the potential in the After Sales area should be better utilised.

No transparency regarding the services provided by the Competence Center in the SAP BI Shared Service area.

High coordination effort, long project start-up times, lack of technical expertise, and support quality.

A regulatory authority with over ~400 insurance companies requires an information system with:

Complex requirements for data visualization cannot be implemented with the existing BI tools.

The existing BI tool cannot meet the complex requirements for data visualisation.

Preparing the weekly and monthly reports takes approximately 2 days each.

The field sales representatives are often on the road and at customer sites. During this time, direct access to sales analytics is not possible.

The department has no way to analyse data across applications.

Der Kunde nutzt unterschiedliche Software Systeme zur Analyse seiner wichtigsten Unternehmens-Kennzahlen. Dies führte zu zeitaufwendigen Analysen

There are no self-learning fraud detection mechanisms that examine transaction data for fraud patterns in real-time.

In order to offer and implement Big Data projects within the Group in a professional service environment in the future, a Big Data Service and Operations Platform should be created for two components: IBM SPSS and Hadoop 2.1

The qualification of potential touchpoints, customers, and prospects is not optimally established to manage and monitor the services offered in the retail channels.

IT organisation in over 50 countries with Excel-based IT cost and billing planning.