We are proud to announce the Camelot Data Science Lab which is bundling our experiences, show cases and best practices to deliver data science application with a clear path towards enterprise integration. Camelot Data Science Lab is next level understanding and execution of enterprise data science.

Data science has always been facing a big challenge on how to bring its application to an enterprise level. According to Gartner, 85% of the data science projects fail to reach the enterprise integration. The Camelot Data Science Lab shows the way how to realize it. At the Camelot Data Science Lab we offer pre-packaged content – from the initial data science workshop, through selecting the most promising use cases based on your data, creating rapid prototypes to services towards enterprise implementation.

Taking this path will ensure that you are going to get maximum value from your data using data science, by focusing on real use cases and staying far away from empty hype phrases. This will enable you to reach your pre-defined KPIs and specific objectives in order to ensure success in the industry in your own domain. Our main focus is to present the capabilities of the enterprise data science and design such a prototype that could be later scaled up and fully implemented in your organization.

Our main service offerings include:

  1. Strategic Data Science Workshop. It is needed in order to first understand what is behind the magic box of AI, gain insights into current technologies and get the link between data science and business in order to discover the potentials that it can bring to your organization. It is led by our experienced data scientists, includes up-to-date best practice examples, can be 2-3 days long and is tailored to your business needs. As a result, you can integrate a realizable AI path into your business value roadmap.
  2. Predictive Analytics Value-Kit. With our value kit, every client will be able to select the best use cases to develop, based on our experience and matched against our portfolio of various predictive use cases. Moreover, it is not just based on standard KPIs, but on reality of your data. This is our as-is-check covering your processes, IT constraints, and possible predictive models – all covered jointly. As a result, you can select the most promising and reachable use cases to place your future focus on.
  3. Rapid Prototyping. Prototypes are all about fail fast, succeed BIG. With our prototypes, our clients will be able to detect the value of good ideas very fast, changing focus when necessary. We use rapid prototyping as a proof-of-value, identify friction points, evaluate UX and optimize its design. As a result, you get a stable prototype for the selected use case, scalability evaluation and bigger scope definition. The latter is especially important when you are looking at the bottom of the pyramid and consider, for example, SAP Intelligent Platform as the next step of implementing data science-driven solutions across your operations.

Figure 1: Enterprise Data Science from Strategy to Production

As Figure 1 shows, the enterprise data science captured within Camelot Data Science Lab practice covers the path from strategy to production. During our work with clients we have developed various prototypes  using the most appropriate technologies for each use case. It has been proven to be the right approach to detect the working prototypes before investing more substantial resources. It is a must have before engaging into larger investments. In our recent blog post on SAP’s Machine Learning and Data Science Platform welcomed by Camelot, we presented one of the possible platforms to implement data science projects in your enterprise. This is, however, highly dependent on your existing IT architecture and business processes. Once data science is no longer a magic box, but rather a support function for your business, we believe in finding the right solution for every problem.

Data Science Lab service offerings are designed from practitioners to provide a realistic path towards value generation using the most appropriate techniques for each use case and help to focus on the most profitable ones.

Here you can find more information about the Camelot Data Science Lab and contact details: https://www.camelot-itlab.com/en/camelot-data-science-lab/

We would like to thank Frank Kienle for his valuable contribution to this article.

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