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Domino Data Lab and Alexander Thamm Partner to Rapidly Scale Data Science Across DACH Region

The leading Enterprise MLOps platform provider teams with leading data science consultancy to accelerate time-to-value for customers’ model-driven business in highly regulated industries across GermanyAustria, and Switzerland

Domino Data Lab, provider of the leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, and Alexander Thamm GmbH [at], a leader in strategic development and implementation of data-driven innovations and business models in German-speaking countries, announced a strategic partnership and a new joint service offering aimed at scaling data science in today’s era of complex and constantly changing data regulations.

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A new Data Science Journey Accelerator (DSJA) offering from the two companies will help customers in Germany, Austria and Switzerland realize a model-driven competitive advantage faster by pairing Domino’s platform with [at]’s data engineering and data science consulting services. DSJA delivers the foundation for data science at enterprise scale —open and flexible Enterprise MLOps tooling to support the needs of both the data science and IT teams— validated by data experts [at] to meet privacy and IT architecture requirements.

While most companies understand the promise of data science, knowing where to start is challenging. Balancing corporate objectives, organizational design, existing processes, current and future technology investments, all in the context of region-specific trends and stringent data regulations means “best practices” to do so are difficult to identify and follow. A recent study by leading European market analyst firm BARC found that 55 percent of companies have not deployed an ML model yet and only 10 percent consider themselves advanced in this area.[1]

“Siloed data and infrastructure represent some of the biggest reasons why high-performing ML applications are not yet the norm,” said Dr. Carsten Bange, CEO at BARC. “With an overarching data strategy and change management regarding infrastructure and processes, plus flexible data and MLOps tooling that adapts to dynamic infrastructure needs, enterprises can more easily deliver high-performing ML solutions regularly and effectively.”

Global Enterprise MLOps Leader, Local Data Science Consulting Expertise

Domino’s Enterprise MLOps platform helps companies become model-driven by allowing large data science and IT teams distributed across the globe to work better together developing and deploying more models faster. [at] has completed over 1,500 projects for over 100 clients across 5,000+ use cases, using tried and tested consulting methodologies: benchmarking current data capabilities, developing roadmaps, designing data operating models, and executing data science projects. Together, Domino and [at] aim to use Domino’s Enterprise MLOps platform to quickly tailor data science solutions for customers with operations in German-speaking markets and key highly regulated verticals: automotive and engineering, financial services, insurance and life sciences.

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“By adopting MLOps and working with MLOps-platforms like Domino Data Lab’s, enterprises can build more models, innovate faster, and address more use cases,” said Andreas Gillhuber, Co-CEO and Head of Engineering for Alexander Thamm. “We are very much looking forward to working with Domino Data Lab, especially because we share the mindset: It is always about creating real added value from data for the customer.”

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“Alexander Thamm has built an impressive consulting practice of navigating cross-border data strategies and fine tuning the art of scaling data science for some of the world’s largest companies,” said Thomas Robinson, Vice President of Strategic Partnerships and Corporate Development at Domino Data Lab. “Combining data science consulting with Domino’s leading Enterprise MLOps platform presents a huge opportunity to help customers transform and scale data science across their operations in Germany, Switzerland and Austria.”

A Foundation to Reach Data Science Scale Faster

The new Domino and AT joint service offering pairs the power of Domino’s Enterprise MLOps platform with Alexander Thamm’s data science consulting expertise, tailored to meet some of the world’s most stringent privacy regulations. Together, Domino and [at]’s DSJA offers customers the key building blocks of a foundation for data science success:

  • Data Strategy Assessment – A workshop using Alexander Thamm’s design-thinking methods to assess and develop a data operating model, covering organizational structure, processes, roles, data governance, and IT systems landscape.
  • Data Science Lifecycle Assessment – Using Domino’s methodology, this workshop helps to discover customers’ existing data science lifecycle and processes – from data to ideation to model development to model deployment and monitoring – to ensure alignment on current processes and challenges.
  • Business Value Assessment – A process to determine the financial benefits of Domino’s platform and [at]’s services, developing a business case calculating ROI, net present value, and payback period with benefits communicated across stakeholder groups (line-of-business, data science, IT, operations).
  • Proof-of-Concept – A program that puts specific customer requirements into action to clearly demonstrate value by successfully implementing a use case.

The partnership comes at an opportune point in time for customers, both those based in German-speaking countries as well as global organizations with operations in highly regulated regions such as Germany. Domino’s recently announced Nexus Hybrid MLOps architecture will provide companies the flexibility to rapidly scale, control and orchestrate data science workloads across different compute clusters, breaking down silos between environments across cloud and on-premises and preventing vendor lock-in. [at]’s expertise covers both data operations and the data science lifecycle, giving customers confidence that data science projects will balance German data locality and sovereignty requirements with future infrastructure investments.

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