Ryan Majidimehr shares an overview of what the Synapse team has been working on:
ADX contains native support for detecting anomalies over multiple time series by using the function series_decompose_anomalies(). This function can analyze thousands of time series in seconds, enabling near real time monitoring solutions and workflows based on ADX. Univariate analysis is simpler, faster, and easily scalable and is applicable to most real-life scenarios. However, there are some cases where it might miss anomalies that can only be detected by analyzing multiple metrics at the same time.
For some scenarios, there might be a need for a true multivariate model, jointly analyzing multiple metrics. This can be achieved now in ADX using the new Python-based multivariate anomaly detection functions.
The themes for this month are Spark, Data Exploration (via Kusto), and data integration.