Aspiring to become a data-driven enterprise is a common goal. Yet the manufacturing sector faces various challenges. Effectively integrating diverse data, managing both IT and OT data, overseeing data volume, and implementing an enterprise-wide analytics platform present considerable obstacles. We show strategies for successful implementation.
Numerous impediments faced by manufacturing companies on the path to data-driven product and process improvements can be solved at once with Lakehouse-based solutions, as enabled by the US technology leader Databricks, for example.
Processing, analyzing, and providing vast amounts of data
Connect any systems, devices, and data formats
Arbitrary manipulation and processing of data
Almost unlimited long-term data storage at low cost
Exploratory, iterative, and collaborative data analysis
Integrated dashboards and option to connect other BI tools
Cataloging and fine-grained control of data access
To provide the management with automated BI reports, our client in the construction industry is planning to set up a data lake for its IoT data. We are responsible for configuring the setup using Databricks, seamlessly integrating it into an Azure Data Lake, and configuring the ETL pipeline. This allows the construction equipment manufacturer to gain entirely new possibilities for data cleaning, data provisioning, analytics, and machine learning.
To calculate energy consumption and CO2 emissions per workpiece, we analyzed process data and information from local power meters for our robotics client. Using the Data Lakehouse concept, we processed and analyzed data from various systems and formats. The results in Delta Tables form the basis for tools like PowerBI.
To seamlessly and cost-effectively document and store 10,000 data points per second without latency gaps, we assist our client in the energy generation sector with the migration to a Cloud Data Lake. Analyzing failure-related data in the Lakehouse accelerates equipment maintenance and optimizes service.
We firmly believe that the construction of data intelligence platforms is both swift and cost-effective for contemporary manufacturing enterprises, given the inherent technological flexibility. The adoption of Data Lakehouse-based methodologies significantly streamlines and expedites data engineering processes.
Naturally, there is no universal solution for Manufacturing Analytics, as the landscape is diverse in terms of prerequisites, challenges, and financial considerations. It also depends on the company’s data maturity. Nevertheless, partnering with an expert who brings domain knowledge and implementation expertise, paves the way for a tailored data solution, ideally developed in collaboration. Ready to get started?
Beyond the impossible: How enterprises navigate data silos, cost pitfalls, and complexity barriers in data analytics.
Delivering excellence in IoT. We are an IoT Solution Provider for Smart Products, Connected Vehicles, Smart City, Smart Energy and Smart Production.
