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Driving insights through observability, machine learning, and predictive analytics

With hybrid, multi-cloud environments, infrastructure is growing increasingly complex and generating terabytes of monitoring data. Unified observability remains a top challenge for organizations, which continue to shift to data-driven decision-making in order to stay competitive.

Organizations need a strong data management strategy along with AI and ML capabilities to analyze and automate actions on observability data. However, according to EMA’s survey results, only 27% of organizations have a unified observability solution and only 54% believe their maturity in analytics and the use of ML is advanced or superior.

This EMA Predictive Analytics report details a number of challenges IT departments currently face and the opportunities for resolving them with machine learning and predictive analytics to improve operational and business performance.

Highlights

The EMA Predictive Analytics report provides an overview of

  • Maturity levels around observability data management for over 150 organizations in the US and EU
  • The application of AI and ML for predictive analytics and key use cases
  • The challenges organizations are facing in an increasingly complex digital landscape
  • Trends in predictive analytics and observability

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