Adding business analytics data to your observability strategy delivers better business outcomes

Organizations striving for improved customer service face challenges in managing the vast amounts of business analytics and observability data generated by their systems, leading to issues like data silos, fragile integrations, and high storage costs. Traditional methods of monitoring struggle to extract real-time insights due to the overwhelming volume and variety of data, resulting in constraints on deriving actionable intelligence. To address these challenges, a modern approach using a data lakehouse, such as Dynatrace's Grail, is proposed. This approach integrates business analytics and observability data, providing a unified platform that eliminates the need for complex integrations and allows for real-time, contextual analysis. By centralizing data and leveraging real-time insights, organizations can enhance collaboration between business and IT teams, optimize processes like customer service, and make more informed, agile business decisions. The data lakehouse model promises to unlock the potential of disparate data sources, providing immediate, actionable insights while reducing costs and increasing efficiency.