DataOps Services

In our DataOps we take care of the operation and maintenance of your platforms and machine learning algorithms. Have you already successfully implemented a data product and now want to ensure that everything runs smoothly? Then feel free to contact our DataOps experts. They will support you in setting up appropriate processes and integrating them into your company's daily routine.

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DataOps

Customers who trust us

DataOps in detail

Once the product or service is marketable, rolled out and in productive use, the next step is to operate, maintain and further develop it. During operation, our Microsoft Azure-, Amazon Web Services (AWS)- and Google-certified experts provide monitoring based on service level agreements and incident management support. Within the operation of platforms, the focus is on cloud service, BigData or BI platforms.

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Operating concept

By means of an operational concept, the operational organisation, processes, roles & responsibilities, governance incl. reporting and SLA (Service Level Agreements) as well as the required toolset can be described.

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Actual state analysis

We analyse the current situation and offer you assessment workshops for location determination and roadmap definition. With proven standards and methods, we accompany you in the subsequent implementation.

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MLOps

The long-term use and maintenance of one or more machine learning models can only succeed on the basis of a powerful infrastructure.
MLOps is a collection of different methods and software tools that are used to overcome the challenges that the productive operation of ML models entails.

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Service catalogue

By means of a service catalogue, the targeted and timely development of a service can be ensured. Agreed response and solution times as well as service depths lead to a service model that is transparent in terms of performance and costs. The integration of offsite and shoring capacities results in economies of scale and cost reduction effects.

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Our data engineering experts

Dr Christina Sievers

Senior Principal Data Scientist

Jörg Bienert

CCO

Case Study: DataOps at Munich Re

Munich Re is one of the world's leading reinsurers and has a huge amount of risk information at its disposal. In order to collect this knowledge in one central place and enrich it with further data, Munich Re developed aData Lake. In cooperation with [at], the operation of this data lake was professionalised and the data pipelines expanded.

You can find more information about this project in our free case study.

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What our customers say

"For the kick-off in the area of Analytics & Information Management at HDI AG, we wanted Alexander Thamm to be the keynote speaker. The organisation could not have been more straightforward and the choice of speaker could not have been better: a real firework display on the state of data (science), analytics and digital use cases!"

- Daniel Magritz & Paul Dittmer - HDI AG -

"The project with Alexander Thamm GmbH was a complete success. I was particularly impressed by the deep understanding of processes and the great expertise of the Data Scientists."

Jürgen Häglsperger | Project Manager | BMW

"The cooperation with Alexander Thamm GmbH was very constructive. The results have brought us a big step forward in the digitalisation of our business."

Markus Lipinsky | Chief Digital Officer | MAN

"Alexander Thamm helps us to better understand the cooking behaviour of our customers and thus to sustainably improve the Thermomix. This ranges from simple descriptive analyses and frequencies to machine learning to recommend relevant recipes to our customers, for example."

Vorwerk

"The cooperation with Alexander Thamm GmbH was convincing with its very efficient and professional approach and was rated super positively by the 50 participants."

Stefan Jacobi | Senior Project Manager | Porsche

"The use case workshop together with Alexander Thamm GmbH helped us a lot to tackle the topic of data-based engine model using a concrete use case."

Project Manager | MAN

You still have questions or want to start directly?

Then contact us!

Simon Decker

Data & AI Projects