Publications

We help companies put their data analytics and artificial intelligence (AI) on the right data platform so that data is under control, available, usable, reliable, and secure – all as a managed service in the cloud.

Our thinking on data issues of management importance in refereed publications and in the media (5-10 pages, 15-25 min reading time) that go deeper than our short stories in “Smart Mobility”.

An eventful year is drawing to a close and a new one is just around the corner. Taking this as an occasion, we look back together on 2018 from the perspective of the Telekom Data Intelligence Hub and also give a small preview for 2019.

Most companies have already relentlessly improved quality internally. Yet beyond company boundaries it is often another story. In the past, going beyond internal policies, computer systems and data networks was simply too complicated. Now, change is bound to happen. Looking at the value chain of glass refinement you see many different stakeholders, all with the same goal: supply goods of the highest quality – with the lowest possible reject rate. The temperature of the raw material plays a big role for quality. Therefore, one would want to integrate the data along the entire value chain in order to identify possible sources of errors and reduce reject rates.

Virtually every company, regardless of its target market, aims to leverage competitive advantages, cut costs and optimize processes. In this sense, companies with the ability to analyze, interpret and use data through integration into their process chains would have an immanent growth lever in their hands.

Industry 4.0, artificial intelligence, cloud computing: The automation and networking of all living and working areas are establishing new business models in all sectors and are changing corporate structures. The basis for this interplay of services is the exchange of data.

Cloudera announces General Availability of Data Science Workbench to Accelerate Data Science and Machine Learning in the Enterprise. The workbench is a self-service-tool for data scientists which helps at building, scaling and deploying machine learning and advanced analytics solutions using the current most powerful technologies. The Cloudera Data Science workbench (CDSW), which was announced in beta at the Strata+Hadoop World San Jose 2017, can be accessed via web browser, where it allows data scientists to use their favorite open source libraries and languages — including R, Python, and Scala — directly in secure environments. The workbench also integrates many deep learning frameworks, including BigDL. This will help data scientists to better use deep learning libraries and tactics on CPUs, without additional hardware investments.