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In this format our experts will introduce you to interesting facts about Artificial Intelligence, Big Data, Machine Learning, Data Management and Data Analysis and give you insights into the optimal use of the Data Intelligence Hub.
|Topic||In the live demo, we will impressively present the possibilities of the Data Intelligence Hub and explain the different functionalities. Using an example, we will also show how to create and work with models quickly and easily.|
|Participation||To the recording|
On 28 and 29 October 2019, the most important personalities from politics and business met. Among others, the project Gaia-X was presented. Here, IDSA and Deutsche Telekom are working together to establish a sovereign data infrastructure for the whole of Europe.
Stop wasting time processing your data - start experimenting! Join the data sandbox to create results faster by benefiting from experiments with free data types & better data. In data analytics today, more than 80% of the time budget is spent on data processing alone. With the “data sandbox” you can generate results faster.
The Data Intelligence Hub supported this years AIHack4Diversity in Berlin. Under the theme "Diverse teams can often receive better results than homogeneous teams", 7 teams tried to solve the honeypot challenge.
IDSA has developed a blueprint to enable companies to pool and share data for competitive advantage, while maintaining data sovereignty. The Telekom Data Intelligence Hub offers a first commercial implementation.
T-Systems is Germany’s leading IT-service provider for the automotive industry. Clients benefit from reliable operations of global backend systems (EU, US, China), leading innovation and super-fast 5G and edge communications.
German Chancellor Merkel is warning German companies to exploit the value creation potential of data or be in for a rude awakening. But how to flip the switch to a data-centric business? A first good step would be “Product Management.”
Everyone is talking about it, but in praxis it shows: "The subject of AI is completely new territory." Experts such as Prof. Dr. Chris Schlueter Langdon of T-Systems explain how to avoid reinventing the wheel.
Obtaining the right data in the right amount is key to AI success. However, on their own very few companies will be able to collect sufficient amounts of data. German economics minister Altmaier sums it up: “We need data pools in Europe.” But how to pool and share data, while maintaining sovereignty?
We asked leading data scientists: How do you spend the next US$1, on more data (quantity) or better data (quality)? And how to measure the quality and quantity of data?