Many companies want to leverage their data to make informed decisions, optimize processes, and develop new smart services and products based on it. The challenge lies in data silos, poor data quality, and the increasing complexity of data processing, which prevent the real value from being derived from the existing data treasure.
Even companies that already use data analytics often encounter limitations within their existing systems. Large volumes of data lead to high costs and performance issues with the current solution.
The solution: a highly integrated data platform that makes data from different systems accessible and analyzable – with high quality, security, and easy access control.
As a Databricks partner, we provide comprehensive support for the implementation of a modern data lakehouse architecture, laying the foundation for state-of-the-art data analytics, machine learning, and AI.
The data lakehouse approach combines the benefits of a data warehouse and a data lake within an advanced data architecture.
The data lakehouse approach combines the benefits of a data warehouse and a data lake within an advanced data architecture.
We demonstrate how companies can overcome data silos, cost traps, and complexity barriers when implementing data analytics.
The Data Intelligence Platform by Big Data and AI specialist Databricks is based on a lakehouse architecture and brings together data engineering, data science, and data analytics in a central, user-friendly environment. Combined with our extensive experience in implementing tailor-made IoT & analytics solutions, we guide companies on their journey to becoming a data-driven organization.
Robotics specialist KUKA is constantly working to make its products and components more efficient and sustainable. Energy consumption plays a crucial role in this effort. To uncover potential savings and accurately determine CO₂ emissions per workpiece, data first needs to be made transparent. This involves processing and analyzing a wide range of parameters from both production and various third-party systems.
Built on a Databricks Lakehouse architecture, an analytics platform was developed to seamlessly integrate data from various sources. This includes high-resolution process data detailing individual manufacturing steps, data from the energy management system, and external information on the electricity mix. By combining these three sources, the platform enables precise calculations of energy consumption and the CO₂ footprint per workpiece. Additionally, it serves as the foundation for transparent visualization and in-depth analysis of process data from all source systems using high-performance tools.
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