Detecting anomalies can help enterprises of all kinds save money, make money, and even save lives. Anomaly detection problems increasingly can be solved more effectively by broadening the data and context to combine location and temporal data, in real time. Fraud detection, predictive maintenance, supply chain monitoring, social distancing metric tracking, and contact tracing are all examples of anomaly detection applications that can benefit by combining spatial and temporal analysis on real-time data sets. The combined capabilities delivered uniquely by MemSQL, broadens the perspective of business decision-making beyond any narrow specific workload or set of employees based on these usage patterns.
Register to learn how MemSQL can be used for:
- Geospatial queries on streaming time-series data
- Intuitive time-series querying with newly added time-series functions in MemSQL
- Detecting anomalies in time series with a spatial dimension
- Domenic Ravita, Field CTO, VP Product Marketing
- Eric Hanson, Director of Product Management, MemSQL Database