Telekom Data Sandbox: Try Small, Fail Fast, Scale Big
Boost Your Data Analytics Efforts – Join the “Data Sandbox”
In data analytics today, more than 80% of the time budget is spent on data processing alone. Join the “data sandbox” to create more results faster by benefiting from (a) experiments with complimentary data types and (b) better data.
Free Data – No Upfront Cost
The “data sandbox” is about experimentation, trial and error, fail fast – and for free, without financial commitment. Simply bring your data; we can match it with complementary datasets from our Telekom Data Intelligence Hub (DIH) so that you can create data analytics success stories faster.
Win-Win Equation = Your Data + Our Free Data and Tools
The Results Are Yours.*
No tricks, our disclaimer:
- Participation is limited and on an invitation basis only. Please contact us using our feedback page, we welcome your interest
- Participants need to sign up for a free DIH trial account or use an existing account.
- The “Data Sandbox” program can be cancelled at any time by either party.
- The free DIH trial account provides free access to an analytics workspace, Jupyter Notebook software with Python, and 64 GB of public cloud storage. With a premium DIH subscription, the customer can use additional platform features and premium tools.
- The data footprint is limited to Berlin areas. Use of our free data is limited for experimentation purposes.
* For commercial use of our data and results, such as algorithms built with our data, the data or rights to the data would have to be purchased.
Join the club: Our current partners include leading technology and digital commerce companies, such as Deutsche Telekom, Motionlogic and IBM. Our data types include weather data, people traffic or movement data, and well-curated and catalogued open-source data.
- Experiment with “data sandwiches” using complementary data types, accepting terms and conditions of the respective data provider
- Benefit from top-quality data
- Think big, start small, scale fast
Use Case Examples