Real-world AI applications require time-series data to transform raw data into valuable intelligence. Time-series data, recorded chronologically, enables trend analysis, anomaly detection, and accurate predictions. This session will consider why it’s essential to look at a time series database when working with ML and AI, how they differ from other databases, and factors such as scalability, data ingestion and storage capabilities, advanced analytics support, and integration capabilities. 

We will also share real-life use cases of companies using the InfluxDB time series database in their production-ready environments to support predictive analytics and automation.

Local ODSC chapter in NYC, USA

Instructor's Bio

Anais Dotis-Georgiou

Developer Advocate at InfluxData

Anais is a Developer Advocate for InfluxData with a passion for making data beautiful through Data Analytics, AI, and Machine Learning. She takes the data that she collects and uses a mix of research, exploration, and engineering to translate it into something of function, value, and beauty. When she is not behind a screen, you can find her outside drawing, stretching, boarding, or chasing after a soccer ball.


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    ON-DEMAND WEBINAR: "Time-Series Databases for AI: Enabling Trend Analysis, Anomaly Detection, and Accurate Predictions"

    • Ai+ Training

    • Webinar recording