AI techniques enhance and accelerate exploratory data analytics

Organizations are increasingly utilizing AI techniques to facilitate exploratory data analytics in cloud environments, addressing challenges such as data quality, reliability, and the integration of heterogeneous data sources. Dynatrace Grail, along with Notebooks and Dashboards, offers a solution by providing a platform that combines topology mapping and causal AI to pinpoint root causes, while its recent addition of the Davis CoPilot generative AI enables analysts to gain insights through natural language queries. This AI-driven approach allows analysts to discover, browse, and explore data by integrating multiple sources and using tools like DQL for advanced data exploration, ultimately enhancing the ability to identify patterns and address issues such as unexpected traffic spikes or performance degradations. The integration of predictive, causal, and generative AI techniques allows for a comprehensive analysis, helping teams to refine their data explorations and customize visualizations as needed, as demonstrated at the Perform 2024 conference by Dynatrace product managers.

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