Data Warehouse and Intelligent Forecasting

In many application areas, large amounts of measurement and event data are continuously generated - for example in the financial world, in industry, in energy supply, in IoT environments or in logistics. This data is often in the form of time series data and must be continuously captured, processed and analyzed in order to make reliable predictions and decisions in real time. The challenge is to reliably capture data from a wide variety of sources, clean it, transform it and provide it in a structured way for analysis and machine learning models.

nxpWarehouse was developed as a visual data pipeline platform that significantly simplifies the construction and operation of complex data processing processes. An intuitive drag-and-drop interface allows data pipelines to be flexibly modeled and connected from sources, transformations and target systems. The platform enables the structured capture and processing of time series data from a wide variety of domains. Transformations can be implemented either visually or directly via SQL and Python code. A central element is the real-time preview of the data at each pipeline stage. The processed data is then stored in optimized formats and serves as a stable basis for continuous forecasts, ML models and automated decision-making processes.