For finding, selection and implementation of the right use case we offer three service offerings that prove the data to value path


Strategic Data Science Workshops for Executives and Management: How can Data Science be applied to my specific business cases? What is behind the magic box of AI?


Predictive Analytics Value-Kit for Business Specialists with the goal to rank complexity vs value, including an extensive list of use cases across different business units and sectors.


Rapid Prototyping for Digital Transformation Leaders is focusing on the value proof of the given data. It is embedded in the overall Camelot philosophy of digital experience.

Strategic Data Science Workshops for Executives and Management

Tailored to your current applied data science experience

From History to State of the Art Applications
The Camelot Data Science workshop highlights the increasing importance of using advanced analytics and machine learning tools to drive improved business performance

Why do you need it?
Discover the AI data to value path. Gain insights into current technologies and market offerings Learn deep-dive use cases within the field of value chain management.

Learn about the Data Science framework to elaborate on your specific topics.
The workshop focuses on major aspects of Data Science and AI, starting from the general information to the overview of advanced supply chain analytics as a path towards digital transformation.

It shall give interested professionals and managers an overview and better understanding of a possible AI path and its key elements.
Better knowledge of applied Data Science and AI and how to get the most value (€) out of the data.
You want to learn more about the Camelot Data Science Lab?

Predictive Analytics Value-Kit for Business Specialists

Tailored to your business needs

From Exploration to Prioritisation
Camelot has derived a systematic approach to assess predictive analytics uses cases with the goal to rank complexity vs value

Why do you need it?
Department heads / CxO have to prioritize the value and feasibility of use cases.

Prioritizing the feasibility of data science use cases highly depends on maturity of data and systems in place.

Feasibility and the link to enterprise IT are crucial to consider right at the beginning, since data scientists have to realize it.
Assessment Workshops on possible use cases, matched against our pre-compiled list. The ranking is done via data science assessment criteria.

The value-kit further analyses the most promising predictive cases by looking on your data and asses feasibility.
Ranking of predictive use cases and feasibility assessment of the selected use cases based on your data.
Interested to learn how your value chain can be enriched by AI?

Rapid Prototyping for Digital Transformation Leaders

Towards enterprise implementation

From Exploring to Prototyping
Data Science Prototyping leads to actionable insights for your business outcomes. It focuses on the value proof of the given data

Why do you need it?
Prototyping is focusing on the value proof of the given data . It is embedded in our overall philosophy of digital experience.

Prototypes are valuable products to explore the data and new ideas without restriction to specific engineering practices or protocols.
How does it work?
A user prototype is the key to several types of validation and is also one of our most important communication tools to customers. A proof of value (PoV) verifies that a business objective can be achieved by development.

Done on your data with regular feedback loops to the business stakeholder to have maximal control on the output.
A live-data prototype collects statistical evidence of the effectiveness of our ideas and solutions.

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