The speed at which data is generated worldwide increases every day. In order to generate insights from these huge amounts of data, sclable data pipelines and efficient transformations are key. No matter if streaming data in real-time or processing it in batches, virtually every data project requires professional Data Engineering at some point.
Get StartedThe backend of an application is arguably the most critical part. Getting the logic right and making sure the application is secure is far from trivial. Therefore you should rely on experts when designing and implementing it.
Get StartedAs long as you are building a "normal" app or are just working with relatively low quantities of data, you likely don't need a Data Engineer. A strong Backend Developer, Data Scientist or Data Analyst should be able to implement the needed transformations, integrations and maybe also some automations. However, if you need to move and process a lot of data and ideally do so without constantly growing technical debt and manual work, you definitely should get support from a skilled Data Engineer for several reasons:
We are always fully committed to the success of our customers - which probably explains our 100 % satisfaction rate. Get in touch with us and tell us about your ideas or problems and we will find out how we can support you!
We are building scalable data pipelines for many years now, retrieving and integrating data from various sources.
One of our core principles is keeping things lean. That's why we don't just suggest trendy technologies but rather tailor the solution to your actual needs.
We can leverage our domain experience in various areas, including Supply Chains, Finance, Media, Medical and more.
In an increasingly complex and volatile world, it becomes hard to analyze supply markets and find new suppliers with traditional approaches. By leveraging publicly available web data we can partially automate the supplier scouting process and significantly improve the results.
In times of change and uncertainty, the effective utilization of external data has proven to be a significant competitive advantage. Accurate, real-time information on markets, suppliers, and competitors is key for making strategic decisions and developing robust predictive models in complex environments.
Estimating the value of a dataset can be difficult, especially if it is very new and unique. With our simple framework, you can get a better understanding of its value and find out if it is worth considering external monetization.