KION Group Relies on Dremio for Data Queries

Dremio, the specialist for simple and open data lakehouses, today announced that the KION Group, Europe’s largest manufacturer of forklifts and warehouse technology, is using Dremio’s data lakehouse solution to extract valuable insights from vast, isolated data sets and accelerate decision-making.

(Frankfurt/Santa Clara) KION Group employees can now query information from over 200 million data records and receive answers to their inquiries in just three seconds. Before the live launch of Dremio, this task would have taken 30 minutes. Thanks to Dremio’s self-service analytics, even less technically skilled users, such as product managers or service managers, can perform complex data queries without the support of IT experts. Real-time data also allows for timely identification of problems and their causes.

The KION Group is leveraging the significantly improved analytical capabilities offered by Dremio across a variety of business areas and processes – for example, for product analyses, warranty cases, and inventory data – after initially identifying 30 operational use cases.

More than 1.7 million Forklifts and Warehouse Technology Devices

The KION Group has more than 1.7 million forklifts and warehouse technology devices in operation with customers in over 100 countries across six continents. After a period of restructuring and mergers, the KION Group faced an IT landscape characterized by silo solutions across a variety of different systems.

Data silos posed an obstacle to enterprise-wide analysis, and data-driven decisions became increasingly difficult as discussions focused more on the accuracy of information rather than operational insights. Furthermore, many of the existing solutions offered limited analytical capabilities.

“The challenges faced by the KION Group in managing their data and their current solution are a prime example of the value that Dremio can provide to a company. Dremio enables companies to integrate silos, gain valuable insights from historical data sets, and put analytical capabilities in the hands of business users rather than the IT department,” explains Andreas Vogels, Head of Central Europe at Dremio.

Dremio builds on previous advancements in data management and analysis to combine the best features of data lakes and data warehouses, providing a unified platform for storing, processing, and analyzing data. Dremio can manage structured, semi-structured, and unstructured data from a variety of historical and current data sets, thus creating added value.

Visibility for Necessary Fine-Tuning or Course Corrections

The KION Analytics Platform (KAP) is built on Dremio, runs on Microsoft Azure, and seamlessly integrates all live queries into daily workflows. Employees can switch between product families, models, or locations and always receive concrete and tangible information. Thanks to the analytics, it becomes immediately apparent where fine-tuning or course corrections are necessary.

Whether as predefined reports or intuitive dashboards, the teams at KION Group determine which data they analyze, when, and in what form.

Understanding the Frequency of Errors

The investigations and evaluations enable business analysts to delve deep into the underlying details – for example, to understand how often a particular error occurs, whether this error only occurs during installation, and whether production has been adapted to new requirements.

“Dremio forms the basis for our entire analytics. The solution has set standards that are hardly comparable to previous ones. We can finally leverage the potential of our enormous data volumes,” adds Simon Wöllhardt, Head of Standards & Strategy Deployment at KION Group AG.

Reviewing Additional Commercial Scenarios

Dremio’s commitment to open source prevents dependency on a single vendor (vendor lock-in). This was another compelling factor for the KION Group to adopt the technology. The KION Group is currently reviewing a number of additional commercial scenarios to see where Dremio analytics can create additional value. Use cases such as a parts-level error history, which can illustrate the entire lifecycle of forklift components, are being considered.

Photo: © KION