Data sharing in the aviation industry

von Patrick | 28/08/2023

Data sharing in the aviation industry

Expert: Michael Scharpf

Industry: Transport & Logistics

Area: Production

Optimising data integration in the aviation industry through innovative data sharing strategies and accurate demand forecasting using machine learning.

Our AI and Data Science Case Studies:
Experience from over 1,600 customer projects

The complex landscape of data integration

In the past, our clients have confronted us with a challenge that many companies are familiar with: despite a wealth of data that holds the potential for breakthrough business innovations, these remain Data often in isolated silos. This situation not only hinders the availability and accessibility of data across the organisation, but ultimately prevents valuable business innovation.

Added to this is the fact that the Data sharing is a sensitive issue. This is mainly due to the lack of accountability. When data is misused, no one area wants to take responsibility for it. This lack of a coherent data sharing strategy within a data governance framework has prevented the safe, cross-functional use of data.

Seamless and secure data exchange through innovative strategies

Based on the needs identified, we developed a customised solution that met our client's key requirements. First of all, we created a secure environment to allow the most free exchange of data possible within the framework of a Data sharing strategy to enable. A key element of our strategy was the Creation of a data classification model. This model formed the basis for ensuring lawful access and provided the departments involved with a clear understanding of the data structures.

We also introduced a data sharing agreement that clearly documented responsibilities. This ensured reliable data sharing.

Transformation of the data landscape for future innovations

The solutions we provided not only enabled a immediate added valuebut also paved the way for future business innovation. As a result of our collaboration, we created a roadmap for the transition in data sharing to close the existing gap between current data sharing and the vision of data sharing as a "standard".

With the first action steps defined to implement the data sharing strategy, we enabled our client, optimise business processes and maximise business opportunities.

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Michael Scharpf

Key Account Manager | Alexander Thamm GmbH

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Development of a complex data visualisation for vehicle registration

von Patrick | 14/08/2023

Development of a complex data visualisation for vehicle registration

Expert: Michael Scharpf

Industry: Automotive & Engineering

Area: Marketing & Sales

We transform data chaos into clear insights - our innovative data visualisation sheds light on the darkness of the vehicle registration process.

Our AI and Data Science Case Studies:
Experience from over 1,600 customer projects

Complex data requirements and quality problems

The transparent Presentation of the entire certification process turned out to be one of the central challenges for us. Companies in the field of data analysis and artificial intelligence need a clear presentation of all relevant information, visualised both thematically and according to the specific user groups. The complex and regularly changing business requirements made this task difficult. Added to this was the Poor data quality of the source systemswhich is a low user acceptance a circumstance that many of our new and existing customers know and want to avoid.

Innovative technology meets user-friendliness

To address this challenge, we developed a central data warehouse that drew its data supply from operational IT systems, including platforms such as Azure and Databricks. Through complex data visualisation, a "Guided-Analysis" application for Different user groups and requirements developed. This offering ensures that every department, regardless of its size, benefits optimally from our solutions.

One of our main focuses was on the Carrying out usability and user acceptance tests, both automated and manual. These tests ensured that the application was not only functional, but also intuitive and user-friendly. To ensure that our client always kept an eye on its internal processes, we documented and consolidated them in a structured way. A separate Data Quality Monitor was also created to constantly monitor data integrity and quality. Finally, we created training videos to introduce new users to the system quickly and efficiently.

Complex data visualisation for optimal transparency

Thanks to our expertise, we were able to create a "Guided Analysis Application", which can be used to create individual Overviews for each user group offers and at the same time on a central data set in a single tool based. This tool provides cross-functional visibility into the status of all certification projects across series, market and discipline, and enables active management and communication of deadlines and resources. This means that companies not only gain insight into their data, but also have control over how they use and share that data - an invaluable advantage in today's data-driven business world.

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Michael Scharpf

Key Account Manager | Alexander Thamm GmbH

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Design of a Cloud Data Analytics Platform

von Patrick | 21/07/2023

Design of a Cloud Data Analytics Platform

Expert: Michael Scharpf

Industry: Energy

Area: Marketing & Sales

Maximise operational efficiency and reduce costs with our customised cloud data analytics platform that seamlessly unifies complex data infrastructures.

OUR AI AND DATA SCIENCE Case studies:
EXPERIENCE FROM OVER 2,000 CUSTOMER PROJECTS

[Challenge]

Our client, a widely branched company with several autonomous organisational units, faced a significant IT and data infrastructure challenge. Each unit operated its own IT and data infrastructure, which made the consolidation and use of all company-wide data an extremely complex matter. Our goal was to develop a unified platform that enabled this data integration without compromising the autonomy of the individual units. In addition, the platform had to cover both development and production operations, which presented another challenge in terms of scalability and flexibility.

[Solution]

With our focus on the use of cloud technologies and our deep understanding of data science and artificial intelligence, we were well equipped to tackle this challenge. We started the process with a comprehensive requirements gathering for the platform in collaboration with all organisational units. This was critical to understanding the specific needs of each unit and developing a solution that was tailored to their individual requirements.

In the next phase, we tested the most important scenarios on possible technologies to ensure that our solution would meet the client's requirements. We chose a modular design based on cloud technologies such as AWS and Azure to make the platform flexible and adaptable.

Data access was enabled both via a central data lake and directly via the source systems of the individual organisational units. This ensured that the autonomy of the units was maintained, while at the same time a central, cloud-based data analysis platform was established.

[Result]

The end result was a highly flexible, efficient and adaptable cloud data analytics platform, designed on the basis of Collibra and one Azure/AWS stack each. This customised solution enabled all of the client's organisational units to work seamlessly and efficiently with enterprise-wide data without adapting their existing IT infrastructure.

The platform was characterised by its high adaptability, which gave the organisational units maximum flexibility in data use. At the same time, the use of cloud technologies ensured that overall costs were kept low. This is a key advantage when it comes to optimising business efficiency.

Another significant advantage was the end-to-end coverage of all common data use cases. Regardless of the type of data evaluation or analysis required by the different units, our solution was able to meet these requirements.

In summary, we have developed a powerful, cost-effective and flexible cloud-based data analytics platform that enables the client to centralise and optimise its data-driven decisions while preserving the autonomy and individual needs of each organisational unit.

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Michael Scharpf | Sr. Principal Key Account Manager | Alexander Thamm GmbH

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Data Mesh Concept for an Industrial Company

von Patrick | 06/07/2023

Data Mesh Concept for an Industrial Company

Expert: Michael Scharpf

Industry: Consumer & Retail

Area: Marketing & Sales

Discover how we helped a leading industrial company revolutionise its data architecture and use valuable IoT data to make strategic business decisions with the innovative Data Mesh concept.

OUR AI AND DATA SCIENCE Case studies:
EXPERIENCE FROM OVER 2,000 CUSTOMER PROJECTS

[Challenge]

Our client, an international manufacturer of chainsaws, forestry and gardening equipment, faced a significant challenge. The company wanted to overhaul its analytics architecture to fully utilise the valuable data from digital twins and IoT devices. This is a key aspect in the modern data-driven economy, as such information provides valuable insights into product performance and customer usage. It was important to the client to have a pragmatic and goal-oriented approach that covered all aspects of a modern architecture. The challenge was not to let the intended data lake become a data swamp - a common problem where data becomes disorganised and inaccessible.

[Solution]

As a solution provider for data analytics and artificial intelligence, we rose to the challenge with a concrete plan. We started with requirements gathering and conducted a comprehensive preliminary study to understand the client's specific needs. From these insights, we developed a data mesh concept. A data mesh shifts the scaling of data architecture from centralised teams to domain-oriented teams, providing a scalable solution for big data. This concept also included data governance and permission control, two critical factors to maintain data quality while ensuring secure access to the data. We then moved on to the implementation phase and started building the individual domain instances. We successively implemented the defined use cases to demonstrate the performance of our solution.

[Result]

The result was compelling. The Data Mesh approach recognises that only Data Lakes have the scalability to meet today's analytics needs, and our client now has a data management framework for their first IoT use case. Our 'bottom-up' ownership structure under clear data governance rules enabled the company to fully realise the value of its data. We also provided a roadmap for further implementation, including the definition of further pilot use cases. Thus, our client was able to further develop its data-driven strategy, relying on our expertise in the data mesh concept.

This project highlights our expertise in Data Science and Artificial Intelligence and shows how we can help businesses realise their data-driven ambitions. Our comprehensive view of business issues and understanding of our clients' challenges enables us to provide tailored solutions that have been proven in practice. If you're looking for an experienced partner to help your data analytics and AI projects

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Michael Scharpf | Sr. Principal Key Account Manager | Alexander Thamm GmbH

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MLOps Maturity Assessment in the chemical industry

von Patrick | 07/06/2023

MLOps Maturity Assessment in the chemical industry

Expert: Michael Scharpf

Industry: Other

Area: Production

Increase your MLOps maturity in the chemical industry with our customised MLOps Maturity Assessment.

OUR AI AND DATA SCIENCE Case studies:
EXPERIENCE FROM OVER 2,000 CUSTOMER PROJECTS

[Challenge]

Assess current MLOps capabilities and create a roadmap for a mature infrastructure based on the client's requirements and best practices at a German chemical company.

Our company had the exciting opportunity to conduct an assessment of the current MLOps capabilities at a renowned German chemical company. The company had already developed several machine learning based products on different technology stacks and in different environments. However, due to a change in focus to maintenance tasks, they were forced to stop developing new products. The goal was to create a roadmap to introduce a comprehensive MLOps platform that would cover implementation best practices and meet the needs of the company.

[Solution]

Conduct interviews and workshops with developers, end-users and other stakeholders to analyse needs and challenges due to the current MLOps infrastructure.

Our team conducted extensive interviews and workshops with stakeholders to understand the needs and challenges associated with the current MLOps infrastructure. This enabled us to define a set of guidelines to build an MLOps platform that takes into account end-user needs, business regulations and best industry practices.

We also conducted a detailed analysis of SaaS platforms, cloud providers and open source solutions. More than 50 criteria were considered to make an informed recommendation. This recommendation formed the basis for the design of the target architecture, which covers the entire lifecycle of machine learning and offers a step-by-step approach for rapid operational implementation.

[Result]

Provide instructions for setting up tests, monitoring, logging, user management and different environments.

The cooperation with the German chemical company led to an impressive result. We were able to present the company with a comprehensive roadmap that made it possible to build a mature MLOps infrastructure. This included clear instructions on how to set up testing, monitoring, logging, user management and different environments.

Thanks to our thorough analysis and recommendation, the company received a clear overview of the available options and was able to make informed decisions. The target architecture and step-by-step approach enabled the company to move forward with the implementation in an efficient and targeted manner.

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Your expert

Michael Scharpf | Sr. Principal Key Account Manager | Alexander Thamm GmbH

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