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.
Our client in the robotics industry aims to calculate the total energy consumption and CO2 emissions per workpiece. This requires processing and analyzing various parameters from production and diverse third-party systems.
Based on a Databricks lakehouse architecture, an analytics platform is being created where data of various types can be consolidated. This includes high-resolution process data detailing individual manufacturing steps, as well as data from the energy management system and external information about the electricity mix. In this way, the collected data from all three sources can be processed together to calculate the precise energy consumption and CO2 footprint per workpiece. Additionally, the platform serves as a foundation for transparent visualization and the analysis of process data from all source systems using high-performance tools.
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