You are developing use cases for data driven scenarios. Your goal to become a driven enterprise is formulated. Maybe even your first prototypes are running. A return on data demonstrating Big Data Science Application is needed in production to justify further investment. Your current resources are too limited to reach beyond the current point. Releasing into a productive landscape is simply unthinkable at this moment.
You hired great people. Your Data Scientists and Big Data Engineers are racing to get Big Data Science and AI foundations running instead of putting their efforts into productive analytics outputs. No Big Data Science Apps are live in production. Yet, there is already a fear that the lack of applied data driven scenarios and the missing return on data will lead to competitive disadvantages in the future.
Big Data integrations take longer time than originally expected. Often this sums up to 80 or more percent of the work time to achieve a return on data. The Data Scientists and Data Engineers have challenges delivering value in their analytics due to lack of available data. Productive Big Data Science Applications on top of the data get postponed again and again. Meanwhile, project stakeholders wait for their return on data.
We co-innovate in partnerships to boost and maintain analytic Big Data Science Apps. You now can leverage big data development performance through our expertise and experience.
Demos available on request
We mine mentioned crypto currency blockchain projects. Data gets sentiment analyzed and forecasts get computed in real time. In addition, reports are generated and emitted via a bot.
We analyze usage details and navigation paths in real time. Conclusions are then exposed via an API to hyper personalize recommendations for users.
We analyze customer data to provide fine grained information to a partner. Based on this information hyper personalized offers are conducted.
Together, we get your use case running.
Use cases are defined iteratively:
„think big, start small“
We determine steps to access the necessary data.
We consider the infrastructure and platform, needed to run the use case.
We contribute with experience, pragmatism and fundamental computer science background.
We address challenges openly at the beginning. This makes it possible to overcome them.