xyzt.ai Elevates Big Data Spatial and Temporal Analytics with V2023.4 Update

xyzt.ai, the big data platform for interactive spatial and temporal analytics, proudly announces the launch of its highly anticipated V2023.4 release. This transformative update introduces an extremely powerful advanced space time query language and unlimited data stores—empowering analysts with enhanced insights and unprecedented flexibility when dealing with vast datasets.

Empowering Analysts: Advanced Space Time Query Language
xyzt.ai introduces an advanced query language tailor-made for the seamless analysis of spatio-temporal data. Specifically designed for tracked vehicles, vessels, and other movement flows, this language boasts a myriad of capabilities in querying and filtering large datasets. Analysts can now employ virtually any query on demand, enabling tasks such as visualizing and analyzing traffic flow with unprecedented ease and immediacy.

For instance, analysts can effortlessly formulate queries like "Show me all heavy vehicle traffic during the morning commute, leaving Port of Antwerp, first driving to Brussels and then driving to either Paris or Luxembourg."

The adaptability of on-the-fly query creation on any data set with immediate response times proves particularly beneficial for traffic analysts dealing with dynamic scenarios, such as road works, deviations, and constructions. This feature has already been embraced by traffic and smart city analysts at the City and State of Hamburg, Strassen NRW in Germany, as well as Autobahn GmbH in Germany.

Revolutionizing Data Management: Unlimited Data Stores
In this release, xyzt.ai also introduces unlimited data stores, enabling users to store datasets with over hundreds of billions of records on the platform. Leveraging its proprietary space-time database, the platform facilitates swift and efficient no-code extraction of data subsets for analysis.

For mobility and traffic analysts, data stores enable the storage of extensive historical floating vehicle data (FVD), allowing for the extraction of specific data subsets for in-depth analysis. Similarly, in the maritime domain, quick extraction of vessel tracking (AIS) data subsets proves indispensable for maritime intelligence analysts.