The term ‘big data’ stems from John Mashey, an IT specialist in Silicon Valley. He coined it in the mid-1990s when describing the finiteness of the IT systems available at the time for processing large quantities of data. Today, it refers to the use and processing of very large quantities of complex, unstructured and highly dynamic data. It requires special IT infrastructures and frameworks to process, since classic IT systems aren’t capable of handling the task.
Big data can be generated in a wide range of fields, including in communication, in traffic, or in the financial sector. Industrial big data is a special segment that has evolved from the increasing number of machines and systems equipped with sensors and their networking. It represents the core of our business model and is the starting point for our big data analytics.
of unstructured data
Internet of Things
as a data source
big data technologies
In order to take advantage of the added value of big data, companies are faced with the challenge of storing and analyzing large quantities of data(volume) generated in a very short time(velocity). Because classic IT systems can no longer handle this volume, new big data-capable solutions need to be implemented in existing IT systems.
Another challenge is that big data generally originates from a number of different sources(variety) and is based on a wide range of data structures. Merging this data, despite its great diversity, represents another special feature when working with big data. Equally important is the ability to analyze the quality or reliability of the data(veracity). Faulty data can distort the results of analyses and thereby diminish the added value that big data can produce.
The main objective of the big data concept is to identify previously undetected patterns, structures and correlations in large quantities of data and to utilize them for the benefit of a company. One example of their value added would be the development of new data-driven smart services that improve processes in the company or support the end customers.
Our expertise lies in the analysis of industrial big data, the development of smart services and their implementation in your business. In the process, our data scientists will analyze your data using big data technologies and extract relevant information. We will discuss the information with your experts in order to generate profitable use cases. Once these are formulated, our data engineers will develop smart services that have been adapted to your systems and integrate the big data-capable solutions in your IT infrastructure. Working together with you, we are able to take on the challenges of big data and put its benefits into practice.
Data is the world’s great new natural resource. What steam power was to the 18th century, electromagnetism to the 19th and fossil fuels to the 20th… data will be to the 21st.
Katana, the data analytics segment of the USU Group, has extensive experience in the application of machine learning methods in the industrial sector. Take advantage of our knowledge and our solutions for building your data-driven business models to reduce your costs and improve your quality and value added.