Data Analytics

Data Analytics


Data analytics, modern learning processes and calculation technologies promise huge business potential for companies. However, it is often a long hard road to their implementation in practice. Data must be collected, purged, aggregated and linked before a meaningful data analysis is possible. When it comes to planning and executing the relevant steps that belong to data analytics engineering, the main focus is on generating added value in the business or production process.
XITASO has concentrated on a solution-oriented holistic approach specifically in this field. Domain specialists, product owners, UIX designers, software engineers and data scientists work together in our team. This means that even complex challenges can be overcome efficiently and quickly.


Potential through data analysis is conceivable in almost all domains and has already been realized to a certain extent. The traditional areas of application include the optimization of production processes, for example to reduce rejects or to lower energy consumption. Less well known, but no less promising are expert systems in the medical sector. These systems can identify potentially successful diagnosis and treatment options using artificial intelligence methods on a broad basis of previous findings and thus make appropriate proposals to doctors.
Practically all of us are impacted by the effects of very elaborate data analysis methods in the logistics sector. Logistics is now being enhanced in almost every retail chain based on demand forecasts. This results in lower inventory and transport costs and a reduction in the loss of perishable goods through waste and scrap.
Perhaps the greatest economic benefit is currently achieved with the data mining of customer information in the B2C sector. Extremely successful large corporations such as Amazon, Google or Payback, for example, have achieved success solely with platform approaches. However, there is huge potential available to all companies in their own customer data through the use of data analysis techniques for improved systems in customer relationship management.
XITASO creates professional solutions in this area and integrates them directly into the existing IT landscapes so that a quick return on investment can be achieved for our customers.


Data analysis is rarely employed on a company-wide basis at present. The only exception is platforms that aggregate end user data. However, this will soon change considerably on account of current trends such as the launch of new 5G networks and the networking of products, production machines and infrastructure. It is anticipated that supraregional platforms will also be established for product and process information along the lines of the global commercial platforms for end customers. This opens the way for a complete rethink about optimization processes and enables new disruptive business models to be derived.
In a whole range of domains, this trend is currently evident: smart cities are focusing on energy and transport, OPC UA-based “Companion Specifications” are endeavoring to achieve cross-manufacturer networking of machines and devices, and the standardization of CAR2X communication in the field of autonomous driving will enable driving profiles to be interlinked for all drivers, manufacturers and municipalities. However, this is just a taste of completely new concepts for city, traffic or product planning. In keeping with medical expert systems, artificial intelligence can help human experts with the ongoing development and planning of these concepts.
They may offer great prospects, but these scenarios also present great challenges. The focus is on the topics of privacy and security as well as the reliability and failure tolerance of systems.
In order to be able to provide the right answers and solutions for this, XITASO has been involved in standardization bodies for many years and actively pursues research projects with university partners. By doing this, we are paving the way for the efficient and responsible handling of data.


  • Data analytics engineering
  • Predictive maintenance
  • Pattern recognition to forecast demand
  • Process optimization (static and adaptive control)
  • Data chaining
  • Data clearing
  • Data integration
  • Learning and classification methods
  • Data acquisition (frequency, bandwidth, volume)
  • Intelligent data processing (local, fog, cloud)
  • Sectors: automation, healthcare, automotive, B2C solutions
  • Learning in safety-critical systems
  • Security & privacy


  • Do you need more information?
  • Would you like to implement a complex and challenging project with us?
  • If so, we look forward to your inquiry.
  • contact us by e-mail

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