Data is the new gold – and you can mine it with the Data Intelligence Hub: Use this innovative platform to securely and efficiently exchange, process and analyze data. Retain full sovereignty over your data. Our vision: the development of new data-driven services and applications for machine learning or artificial intelligence.
Get better results with more information – effective data sharing enables you to develop new, future-oriented, competitive and data-driven business models.
Exchange and use: The Data Intelligence Hub can help you turn existing or acquired unstructured data into business-crucial insights with AI and analysis specialists.
Your company’s data is a valuable asset: Accessing your own database with the Data Intelligence Hub allows you to tap additional sources of revenue in a simple, transparent and secure manner.
Exchange and process data both in and beyond your own sector: The marketplace provides entirely new ways to execute your data strategy.
The Data Intelligence Hub offers a wide spectrum of proven analysis tools. Work on your own or collaborate on projects – regardless of your own hardware infrastructure.
Publish your data and analyzes individually: Who is allowed to view them, who to explore, who to process? All could be managed at once in the Data Intelligence Hub.
Exchange data with all of your business partners along the data value chain and across international borders. You can rely on our infrastructure and security standards.
Receiving and providing are getting quite simple through the Connector. The application based on the open source software Apache Kafka provides an interface for loading and processing data streams. Especially for large amounts of data and peer-to-peer install the connector locally on your server.
Intelligent mobility is being used more and more. But to create this intelligence, a large amount of data is needed. In order to remain competitive as an OEM, data must be collected, analyzed and used efficiently. But how do you actually obtain the data?
Mistakes slow down production and cost money. To avoid this and to make the production process as efficient as possible, errors must be identified and eliminated at an early stage. Wouldn't it be ideal to have a digital image that identifies defects prior to production?
Stakeholders in the logistics industry can plan more efficiently by using the Data Intelligence Hub. Thanks to Data Analytics, they are always up to date.
The Data Intelligence Hub solves mobility problems through data diversity. With Analytics, individually required information are filtered and processed.
Artificial intelligence helps companies to monitor large amounts of data. The Data Intelligence Hub is an ecosystem for secure data exchange and analytics applications on one platform.
Intelligently networked machines improve the process chain and products in manufacturing companies. The DIH makes Industry 4.0 possible.
With Smart Monitoring, service technicians can easily monitor machines and production processes and react earlier - for example with the Data Intelligence Hub.
Numerous data sources and algorithms are combined in the DIH for a comprehensive inventory and forward-looking forecasts.
With the Telekom Data Intelligence Hub (DIH), municipalities can process their data in a targeted manner and make it available to citizens – without having to build their own infrastructure.
Easily generate value from your own and external data: Use the large number of different analysis tools the Data Intelligence Hub offers to process data and generate insights.
With the Cloudera Data Science Workbench, data scientists can manage their own analysis pipelines. This includes integrated planning, monitoring and email alerting. Quickly develop and prototype new machine learning projects and easily deploy them in production.
Grafana Labs' free-to-use dashboarding tool Grafana helps you keep track of everything. It is very common because it is very mature and stable.
H2O.ai's H2O open source service is a Java backend for machine learning applications. It comes either for beginners with a pre-set frontend or can be controlled via APIs using programming languages, such as Python, R or Java. It brings some of their own implementations of popular ML algorithms that are among the best in the market.
With IBM Data Science Experience, users have an interactive, collaborative and cloud-based environment in which data scientists can use multiple tools to gain information. Data Science Experience integrates with RStudio, Jupyter, and Python in a configured collaborative environment.
This NumFocus open source workbench is similar to easy-to-use text document processing software. Unlike the default editor, it provides the user with meaningful and efficient features to easily access data and other resources.
RStudio is an integrated development environment (IDE for short) that allows you to analyze data in the R programming language. The workbench includes a console, a syntax highlighting editor that supports direct code execution, and tools for plotting, history, debugging, and workspace management.
Developed by the Apache open source community, this tool helps with data acquisition, recognition, analysis and visualization. The interpreters allow you to attach code in any language to Zeppelin with support for Apache Spark, R, Hive, Shell, Cassandra, and more.
Benefit from the network of Deutsche Telekom: Forge alliances, meet with customers and service providers of all sizes and industries – for more joint success.
Join one of our live sessions and learn how to get the most out of the Data Intelligence Hub. Read more
Learn how to pull your data from the Azure blob storage and analyze it on the DIH Jupyter Notebook. Read more
Mistakes slow down production and cost money. To avoid this and to make the production process as efficient as possible, errors must be identified and eliminated at an early stage. Wouldn't it be ideal to have a digital image that identifies defects prior to production? Read more
Intelligent mobility is being used more and more. But to create this intelligence, a large amount of data is needed. In order to remain competitive as an OEM, data must be collected, analyzed and used efficiently. But how do you actually obtain the data? Read more
Neural Networks are an exciting technology used in the field of machine learning these days. But there is a phenomenon that many big networks struggle with: Training Time. Read more
What is Artificial Intelligence? How important is Open Source Software? What are the most important solutions? Read more
New mobility frees up space, how to use it? Behavioral data can provide answers. Read more
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. Read more
An eventful year is drawing to a close and a new one is just around the corner. Read more
At the end of November the Big Data Days took place in Berlin. A short video summarizes the highlights. Read more
Digitizing the production line of a Hidden Champion in 100 days? Read more
Why artificial intelligence would be impossible withouth data. Read more
Watch our new video, which tells you the most important thing about the Data Intelligence Hub in only 85 seconds. Read more
Deutsche Telekom has defined nine guidelines for dealing with artificial intelligence (AI). Read more
“The world’s most valuable resource is no longer oil, but data”, the Economist wrote in 2017. But what can companies do with all the data they are creating? Read more
The launch of the Data Intelligence Hub will be complemented with a “DIH University Initiative.” Read more
Industry 4.0, artificial intelligence, cloud computing: The automation and networking of all living and working areas are establishing … Read more
This year’s Strata Data Conference in London was the place to be for the Telekom Data Intelligence Hub (DIH) … Read more
This part of the blog focusses on the relevance of the topic and the added value of a data marketplace. Read more
Data can be bought and sold, creating data marketplaces.… Read more
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. Read more
Virtually every company, regardless of its target market, aims to leverage competitive advantages, cut costs and optimize processes… Read more
The basis for this interplay of services is the exchange of data. Read more
Want to know how to successfully share, analyze and use data in the Data Intelligence Hub to gain business insights? Register for free and start now…
