Big data analytics - turning raw data into profit
Do you collect huge amounts of data from sensor measurements, machine logs and remote platforms and are wondering what value your data holds? Do you have a concrete idea of how to use your data commercially? Are there problems in your production that can only be solved with data analysis? Is your digitalization strategy in full swing and you still need a strong partner for implementation?
Whatever the status of your project, our experts will support you in all project phases. We realize your vision in three steps. From the joint development of the use case based on your collected data, to individual algorithm development and operationalization, including integration of the solutions into your value creation process. With Katana, you have a strong companion for the major goal of "turning raw data into profit".
USE CASE - What should be optimized?
We work with you and your experts to develop an individual use case to improve your machines or IT systems. In an initial meeting, we discuss which errors or malfunctions need to be examined in relation to data and where there is a need for optimization. The results of the analyses are then discussed and evaluated between our data scientists and your experts. The result of this first important step is the business value definition of the use case.
PROTOTYP - Does it work?
Your data is prepared by our data scientists specifically for your use case. Our core competence is to develop algorithms that use methods from statistics, signal processing and machine learning to identify patterns, irregularities and outliers and reveal previously unknown correlations. The basis for optimization has now been created.
SERVICE - Now it's time to put it into practice!
The next step is the transformation to the Katana platform. To this end, our data engineers migrate the prototypically developed algorithm so that it can be applied to large volumes of data reliably and with high performance. The final integration with your target environment enables permanent further development and optimization. With this approach, your data-driven portfolio can be expanded to include accompanying smart services. This can be, for example, increasing the productivity of your machines using predictive maintenance or optimizing your overall system effectiveness using analysis results from peer group comparisons.
Example scenario Ewon Flexy - Talk2M - Katana
Machines can generate both time series and event data, and the detection of anomalies plays a central role in uncovering production errors.
In addition to the real-time detection of anomalies in sensor data, the long-term prediction of the temporal development of relevant parameters also plays a central role. Parameters can be, for example, the mileage or the oil quality of a machine. If the development of these parameters over time can be predicted with sufficient accuracy, spare parts can be ordered in good time and service technicians can be scheduled for maintenance. This prevents costly breakdowns.
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