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Dynatrace Introduces Digital Business Analytics

Dynatrace announced the addition of Digital Business Analytics to its Software Intelligence Platform.

Digital Business Analytics provides real-time, AI-powered answers to business questions using data already flowing through Dynatrace’s application and digital experience monitoring modules. By tying together user experience, customer behavior, and application performance data with business metrics, Digital Business Analytics provides real-time answers about conversions, orders, churn, release validation, customer segmentation and more. Traditionally, application owners and business users have been forced to go to disparate, siloed tools and manually analyze data, thereby hampering their ability to run and optimize their digital business offerings in real-time.

Available today, Digital Business Analytics joins APM, Cloud Infrastructure Monitoring, Digital Experience Management, and AIOps as part of the Dynatrace all-in-one Software Intelligence Platform. As with these other modules, Dynatrace’s AI engine Davis is at the core of Digital Business Analytics. Davis continually learns what expected “normal” business performance looks like and provides proactive answers to issues, enabling faster decision making, greater optimization of resources and better business outcomes.

As data volume and velocity accelerates, organizations are struggling to make sense of disparate dashboards from traditional IT monitoring tools, web analytics and ad hoc reporting. Dynatrace’s Digital Business Analytics automatically captures business data and analyzes it in context with user experience and application performance data. Furthermore, Digital Business Analytics complements existing web analytics tools to deliver real-time and complete results, by combining existing customer-facing channels with application and user experience data. Dynatrace’s full-stack Software Intelligence Platform shares a common data model across the platform, with AI and automation at its core, applying anomaly detection to business metrics to provide precise, real-time answers to business-critical questions.

Key pillars of Digital Business Analytics include:

- Transactions: Automatic tracing, segmentation and data extraction from business transactions.

- Analytics: AI-powered analysis, exploration/querying and extraction of business-relevant insights from Dynatrace® application and user experience data.

- Conversions: Visualization of and collaboration on business-relevant metrics such as conversions and revenue performance by product, customer segment, geography and more.

- Automation: AI-powered anomaly detection, alerting and root cause determination for business processes, with programmable APIs to trigger business workflows and change events.

“Digital transformation projects are spurring companies to create multidisciplinary lines of business teams that run the business with a product mindset and are demanding answers to questions that were previously difficult, slow or impossible to obtain,” said Steve Tack, SVP of Product Management at Dynatrace. “Digital Business Analytics leverages the automation and intelligence at the core of the Dynatrace Software Intelligence Platform to provide alerts, best-in-class anomaly detection and real-time answers about high-impact business issues such as degradation in revenue or conversions across products, geographies or segments.”

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Dynatrace Introduces Digital Business Analytics

Dynatrace announced the addition of Digital Business Analytics to its Software Intelligence Platform.

Digital Business Analytics provides real-time, AI-powered answers to business questions using data already flowing through Dynatrace’s application and digital experience monitoring modules. By tying together user experience, customer behavior, and application performance data with business metrics, Digital Business Analytics provides real-time answers about conversions, orders, churn, release validation, customer segmentation and more. Traditionally, application owners and business users have been forced to go to disparate, siloed tools and manually analyze data, thereby hampering their ability to run and optimize their digital business offerings in real-time.

Available today, Digital Business Analytics joins APM, Cloud Infrastructure Monitoring, Digital Experience Management, and AIOps as part of the Dynatrace all-in-one Software Intelligence Platform. As with these other modules, Dynatrace’s AI engine Davis is at the core of Digital Business Analytics. Davis continually learns what expected “normal” business performance looks like and provides proactive answers to issues, enabling faster decision making, greater optimization of resources and better business outcomes.

As data volume and velocity accelerates, organizations are struggling to make sense of disparate dashboards from traditional IT monitoring tools, web analytics and ad hoc reporting. Dynatrace’s Digital Business Analytics automatically captures business data and analyzes it in context with user experience and application performance data. Furthermore, Digital Business Analytics complements existing web analytics tools to deliver real-time and complete results, by combining existing customer-facing channels with application and user experience data. Dynatrace’s full-stack Software Intelligence Platform shares a common data model across the platform, with AI and automation at its core, applying anomaly detection to business metrics to provide precise, real-time answers to business-critical questions.

Key pillars of Digital Business Analytics include:

- Transactions: Automatic tracing, segmentation and data extraction from business transactions.

- Analytics: AI-powered analysis, exploration/querying and extraction of business-relevant insights from Dynatrace® application and user experience data.

- Conversions: Visualization of and collaboration on business-relevant metrics such as conversions and revenue performance by product, customer segment, geography and more.

- Automation: AI-powered anomaly detection, alerting and root cause determination for business processes, with programmable APIs to trigger business workflows and change events.

“Digital transformation projects are spurring companies to create multidisciplinary lines of business teams that run the business with a product mindset and are demanding answers to questions that were previously difficult, slow or impossible to obtain,” said Steve Tack, SVP of Product Management at Dynatrace. “Digital Business Analytics leverages the automation and intelligence at the core of the Dynatrace Software Intelligence Platform to provide alerts, best-in-class anomaly detection and real-time answers about high-impact business issues such as degradation in revenue or conversions across products, geographies or segments.”

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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