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AI Boosts Datacube Analytics

By Eric Van Rees - 26th April 2024 - 05:10

Chatbots are becoming useful tools as helpers – not actors – in the daily professional life.

Now they give a helping hand in designing datacube queries effortlessly and fast with the ChatCUBE AI by rasdaman. It makes experts more productive while novices ramp up their skills at their individual pace. This disruptive innovation opens new vistas for empowering users and comprehensive insights into spatio-temporal geo data.

Chatbots these days produce stunning results, although it is clear they are definitely not omniscient. The breakthrough of OpenAI with its ChatGPT has sparked new specialized service, such as SQL trainers. Now a chatbot has been tuned to geo datacube analytics. The datacube experts from rasdaman GmbH presented ChatCUBE, their prototype of a chatbot helping to design datacube queries based on the OGC/ISO standard Web Coverage Processing Service (WCPS). It responds to questions like „explain the basics of WCPS“, „how does datacube fusion work?“, „show me an example of timeseries analysis“, and all the further details of datacube wrangling. First feedback so far is quite encouraging: it “eases query writing” and “wish I had this earlier” was heard from both novices and experts.

“We see ChatCUBE as a very effective productivity tool lowering the barrier for datacube analytics”, explains Prof. Peter Baumann, lead of the rasdaman university research group and spinoff founder, continuing “we must democratize data understanding, get away from the restrictive python barrier limiting access to a circle of programmers”. For beginners, the datacube dialog smoothens the learning curve through individualized learning by giving introduction, explanation, and examples, etc. at the pace and direction of the learner. Experts see a productivity enhancement as they can look up syntax details, obtain query examples and templates for complex queries involving subsetting, analysis, aggregation, fusion, etc.

The service is publicly accessible here. Users can leave a feedback on how satisfying they found the result, thereby helping to optimize the service further.

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Read More: Big Data Education & Research

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