Dr. Lars Schwabe, head of the Data Insight Lab, talks to us in an interview about how the Data Insight Lab helps each one of its customers, who come from a wide range of industries, to develop into a data-driven company 4.0.
Why did Lufthansa Industry Solutions initiate the Data Insight Lab?
Many companies have access to valuable data. However, they often lack the resources and knowledge needed to actually benefit from them. This is why the Data Insight Lab has now been running at Lufthansa Industry Solutions for the last two years. This is where data scientists and data architects work with companies to consolidate, structure and analyze their data.
Their constant aim is to assess data and, ideally, to utilize the results to create value, no matter whether companies want to improve their customer management, monitor their supply chains or design the intelligent energy network of the future on the basis of big data. In particular, the prediction of events in real time on the basis of comprehensive data analyses is playing an increasingly significant role. Against this backdrop, the Data Insight Lab also points out opportunities for predictive maintenance solutions. This means that customers – for instance from manufacturing, air transport and logistics – can find out as early as possible if a certain machine or plant needs maintenance so that there are no unforeseen malfunctions.
We support a company during its transformation into a data-driven company 4.0.Dr. Lars Schwabe, Head of the Data Insight Lab
What does your work actually involve?
Our data scientists develop scenarios and specific use cases for data analytics together with our business analysts and our customers. Based on the problem and the goals they define, the data scientists then develop analyses and models in the Data Insight Lab, which exceed the scope of classic business intelligence reports.
We convert the use cases into mathematically formal statistical, learning and optimization problems that are then computed in our in-house big data infrastructure. We regularly exchange information with the customer during the process. The laboratory results either support or falsify the business use case hypothesis. Early failure in a laboratory situation is also valuable information for our customers, as they can use it to adapt their use cases.
What happens if the customer’s analyzed data is useful?
Just as we were already involved in the process before the actual data analysis, we don’t just stop once our results have been delivered. Part of the work process with each customer is supporting and advising him or her during implementation when it comes to topics like architecture, for example. We always view the customer’s problems and challenges, data analytics and their productive utilization in business holistically.
In addition to this, our services include the creation of proofs of concept, not just analyses. If needed, we then plan solutions that can be used productively in our customer’s backend systems or design an entirely new overall solution. Alternatively, we can set up a laboratory platform in the customer’s IT landscape or in his or her cloud. And we don’t just assist companies during technical conceptualization and implementation. Staff training and measures to transform a company’s culture are also important matters that need to be taken into account in order to develop an organization into a data-driven company 4.0.
IDG Study Predictive Analytics 2018
Please download the study Predictive Analytics 2018 here (in German).
IDG Study Predictive Analytics 2018 – key findings / whitepaper
Please download the key findings of the study Predictive Analytics 2018 here (in German).