Development of a complex data visualisation for vehicle registration

Development of a complex data visualisation for vehicle registration

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.

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Your expert

Michael Scharpf - Key Account Manager

Michael Scharpf

Key Account Manager | Alexander Thamm GmbH

Data platform for use cases for a logistics company

Data platform for use cases for a logistics company

Data platform for use cases for a logistics company

Expert: Michael Scharpf

Industry: Procurement & Supply Chain

Area: Transport & Logistics

Discover how we helped a global logistics company master heterogeneous data landscapes, ensure security and make breakthrough data-driven decisions - all on a single, powerful data platform.

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

[Challenge]

Our client, an internationally operating group from the logistics sector, was faced with a huge challenge: connecting about 30 heterogeneous source systems to a new data platform. These systems, which provided crucial data for the procurement department, were poorly documented and therefore difficult to handle. In addition, this newly developed data platform was to be provided in the cloud in order to be accessible by a large number of users worldwide. But not all users should be able to see all the data, an additional layer of complexity that further complicated the project.

[Solution]

With our in-depth knowledge and experience in data analytics and artificial intelligence, we developed a customised solution. First, we used Apache Nifi to extract data from the different source systems and load it into an S3 bucket. Apache Nifi is a powerful data processing and integration tool that was ideal for this project due to its high flexibility and scalability.

To process complex queries, we used Amazon Redshift, a data warehouse that processes complex queries quickly and reliably, which significantly improved the performance and speed of our data platform.

At the same time, we recognised the need to implement effective metadata management. For this, we used a central data catalogue tool that helped us gain better control and overview of the data assets.

Equally important was the implementation of a well thought-out authorisation concept. With a customised authorisation control, we ensured that each user could only access the data that was relevant to his or her activity. This allowed us to effectively prevent unwanted data access and ensure data security on the platform.

[Result]

The result was a state-of-the-art, secure and user-friendly data platform for logistics that fully met our client's requirements. The procurement department now had central access to all relevant data for analytics and business intelligence. The platform could also be used by people and teams outside their own organisational unit, which significantly improved collaboration and information flow.

By implementing this solution, our client was able to improve their data-driven decision-making and optimise their business processes. This success story shows how our comprehensive understanding of data analytics, AI and business processes can help overcome even the most complex challenges. It confirms our position as a trusted partner for companies looking for effective data analytics and AI solutions.

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Michael Scharpf - Key Account Manager

Your expert

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

MLOps workshop for a logistics company

MLOps workshop for a logistics company

MLOps workshop for a logistics company

Expert: Michael Scharpf

Industry: Transport & Logistics

Area: Procurement & Supply Chain

Optimise your ML production and set new standards in the logistics industry with our customised MLOps workshop for your company.

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

[Challenge]

In an ever-evolving digital landscape, data-driven solutions are crucial for companies to remain competitive. A large German transport company recognised the need to exploit their potential in data analytics and artificial intelligence. They already had several ML use cases in the prototype phase, but lacked the right tools and processes to successfully deploy them in production. To address this challenge, we organised an MLOps workshop.

[Solution]

Our MLOps workshop aimed to create a common understanding of MLOps and support the future development of use cases. We took an in-depth look at the challenges of machine learning in production and developed solution approaches. In the workshop, we presented the participants with a comprehensive framework that includes both tools and processes for standardising Machine Learning in production.

At the beginning, we presented a clear definition of MLOps and explained how it differs from DevOps and DataOps. We discussed the different roles and tasks and showed how teams in a large organisation should be structured to work together effectively.

An important focus was on creating a target architecture that covers the entire machine learning lifecycle. We described the tools needed for implementation and showed how to make incremental improvements to reach the target state. In doing so, we highlighted business aspects and emphasised the importance of starting early and implementing simple solutions.

Furthermore, we introduced the ML Canvas to the participants as a framework to structure their machine learning projects. We dived into every step of the ML lifecycle, starting with data exploration and ending with model monitoring. We taught best practices and techniques to make the whole process efficient and produce high quality results.

[Result]

After completing the MLOps workshop, the participants were well equipped to successfully implement Machine Learning in production. They had a comprehensive understanding of the challenges and solution approaches of MLOps and were equipped with a framework to implement ML use cases in a standardised way.

The transport company was now able to put their ML use cases on a solid footing and take full advantage of data-driven decisions. By implementing MLOps, they were able to increase efficiency, reduce errors and improve the scalability of their ML applications. They were able to move their models into production faster and shorten the time-to-market for new features. This enabled them to gain competitive advantage and delight their customers with innovative solutions.

In addition, the MLOps workshop led to better collaboration within the company. By clearly understanding the roles and tasks related to ML in production, teams were able to collaborate more effectively and improve communication. This led to a smoother integration of ML technologies into existing business processes and enabled seamless collaboration between data scientists, developers and the operations team.

During the workshop, we also pointed out the long-term perspective of the MLOps implementation. We emphasised the importance of continuous improvement and made recommendations on how the company can further optimise the developed solution. This includes regularly reviewing processes, evaluating new tools and technologies, and adapting the organisational structure to keep up with the changing requirements of the ML lifecycle.

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Michael Scharpf - Key Account Manager

Your expert

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

MLOps Maturity Assessment in the chemical industry

MLOps Maturity Assessment in the chemical industry

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.

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Michael Scharpf - Key Account Manager

Your expert

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

Data analytics training for an insurance company

Data analytics training for an insurance company

Data analytics training for an insurance company

Within the framework of a bilingual WBT, all employees are to be provided with basic knowledge in the area of data analytics.

Training of approx. 20,000 employees in two languages

*

Modules of the WBT can be carried out independently of each other and are reusable

Employees have a basic understanding of data analytics and strive for deeper knowledge development along the curriculum

Challenge

A global reinsurer wants to introduce all employees to the topic of data analytics in the reinsurance sector and thus contribute to the digital transformation. The level of knowledge and practical experience of the employees in the area of data is very heterogeneous.

Solution

A customised curriculum for data analytics is designed with corresponding development stages. A web-based training (WBT) serves as a basic course to familiarise as many employees as possible with data analytics as a topic and to bring it into context with their everyday work. Industry-related examples and varied interactions during the transfer of knowledge maximise the didactic transfer online. The topics are divided into 10 flexible modules.

Result

A 90-minute web-based training on data analytics in the insurance/reinsurance sector delivers easy-to-understand data analytics content in a general context and in relation to their everyday work. Future training elements of the curriculum will build on the basic WBT.

Are you interested in your own use cases?

Challenge

An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.

Solution

There will be a interactive and Flexible application, including of different maps with two different views implemented.

Result

Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.

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