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February 07, 2024

NETZSCH Group creates single source of truth with Microsoft Intelligent Data Platform

Traditionally, the NETZSCH Group has operated its three main business units independently. The company recently began exploring how AI and IoT data could provide new avenues for growth. As part of that process, it also began looking for a way to unify its siloed data. Adopting the Microsoft Intelligent Data Platform, NETZSCH Group consolidated its data and developed efficient means of refining data quality and sourcing reliable insights. The solution could also lead to the development of new data-as-a-service offerings.

Erich Netzsch GmbH & Co. Holding KG

Erich Netzsch GmbH & Co. Holding KG (NETZSCH Group) has a long and storied history. Around the world, construction companies, oil and gas refiners, and even chocolatiers rely on machinery and instrumentation developed by the company. Through the course of its work in three main areas—Pumps & Systems, Grinding & Dispersing, and Analyzing & Testing—NETZSCH Group has seen a rise in customer demand for more digitally-driven and IoT insights. Company leadership also wanted to embrace more advanced AI and unified analytics solutions. Thus, a digital transformation initiative was born.

Traditionally, the company’s three main business units have been run heterogeneously. Each unit not only had its own data silos but also its own reporting tools. To add to the problems, storage and memory capacity were limited by existing on-premises systems. And because the existing systems had not been designed to handle cloud-scale data, querying the company’s data wasn’t easy or predictable. “Our old system was not made for big data, was not designed for anything AI-based, and wasn’t really scalable,” says Stefan Lautenschlager, Head of Business Intelligence & Analytics at NETZSCH Group. “To create something more aligned with our goals, we needed to move to the cloud.” 

Overall, NETZSCH Group outlined five major goals for its digital transformation. The solution would, first and foremost, have to provide a centralized data lake capable of enabling a single source of truth across the company. Scalability would be important, as the company expected to routinely run analyses on millions of rows of data. Data-quality management and refinement would be key as well, as NETZSCH Group wanted to make sure its future AI workloads would be using reliable information in their calculations. Out-of-the-box machine learning capabilities would also be a must. Lastly, NETZSCH Group wanted access to notebook-based options that could help speed the delivery and validation of data insights. 

A platform built for analytics and AI

To meet these varied needs, NETZSCH Group considered multiple solutions from a variety of providers. As the company explored its options, the availability of self-serve analytics became a top priority. “We were looking for a solution capable of reducing our group of 12 reporting tools to 1,” says Lautenschlager. “By pairing that with our strong focus on self-service analytics, we very quickly realized that nothing else came close to Power BI in meeting our needs.” The identification of Microsoft Power BI as a focal point of its new solution led NETZSCH Group to the rest of the Microsoft Intelligent Data Platform—a unified data and AI platform designed to help businesses better govern their information, add layered intelligence to their existing apps, generate predictive insights, and increase agility. 

In particular, NETZSCH Group was interested in the interoperability between Power BI and Azure Synapse Analytics, another part of the Microsoft Intelligent Data Platform. Among other things, Synapse Analytics brings the SQL technologies used in enterprise data warehousing together with Spark technologies focused on big data, both of which were already in use at NETZSCH Group. The interoperability of the two solutions, Lautenschlager reports, has reduced data transfer times far more than the company initially expected.

Though NETZSCH Group was already familiar with Microsoft Azure, SQL, and Spark technologies, the company made sure to reach out to the cloud data migration and analytics experts at Adastra GmbH to streamline the adoption process. Adastra, along with Microsoft FastTrack engineers, worked to ensure that the new solution would correctly incorporate the complex machine learning and scripting algorithms NETZSCH Group planned to adopt. Together, using both Synapse Analytics and Azure Databricks, the companies implemented the rest of the cloud infrastructure and services NETZSCH Group needed. “Microsoft Intelligent Data Platform delivers everything we need out of the box,” says Lautenschlager. “Microsoft is also continuously upgrading and enhancing the solution, constantly delivering us with new ways to innovate.”

Targeted analytics at scale 

Thanks to its collaborative deployment with Adastra and Microsoft, NETZSCH Group has already achieved many of the goals it set for its cloud-analytics transformation. The company now has a centralized data lake, the scalability required to run large-scale AI workloads, and it has efficiency-enhancing notebooks. With these goals achieved, the company next focused its efforts on measuring and improving data quality. 

Hernán Alejandro Gajardo Morales, Senior Azure Data Engineer at NETZSCH Group, prototyped an Azure-native solution that collects raw data from the company’s SAP tools and brings it into a single table for quality analysis. The first time he did this, Morales used data from the company’s largest unit, Pumps & Systems. The resultant table had 82 million rows of data and took up nearly 1.4 gigabytes of space. This was an amount of data that the previous system simply could not have loaded, let alone reliably analyzed. These days, analysis of this kind takes NETZSCH Group fewer than five minutes.

The data was run against a list of 13 quality-affirming key performance indicators, after which Morales’s solution output a report using Power BI. This report can help the company improve the quality of its data. “Our main goal is to make this solution available to the whole company via Azure, where it can filter data by business unit, subsidiary, and language,” says Morales. “We’ll be able to measure data quality across different sections of the company and different data domains, which will help us accelerate our data-validation process.”

New avenues for growth

NETZSCH Group plans to use its newly verified, centralized, and highly available data to grow its business in a number of ways. Individuals who make decisions that affect multiple business units will now have more accurate information at their fingertips. Higher-quality data also means greater potential for machine learning, IoT, and AI-powered workloads. “We expect to drive a lot of innovation with the Microsoft Intelligent Data Platform,” says Lautenschlager. “With IoT data and AI insights, we can quickly identify geographic areas where our customers are buying fewer replacement parts from us, for instance. We can then take the needed steps to win back that business.”

NETZSCH Group expects that the data it can now collect, process, and analyze will open new avenues for growth in the data-as-a-service arena. The company also plans on adopting more AI in the near future, including Microsoft Copilot. “Quality is key for us," says Lautenschlager. “It is our strongly held belief that Microsoft not only delivers the quality we need, but that its solutions are helping the entirety of NETZSCH Group explore new markets as well.”

“Microsoft Intelligent Data Platform delivers everything we need out of the box. Microsoft is also continuously upgrading and enhancing the solution, constantly delivering us new ways to innovate.”

Stefan Lautenschlager, Head of Business Intelligence & Analytics, NETZSCH Group

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