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Dynatrace Unveils Data Observability for Analytics and Automation Platform

Dynatrace announced new AI-powered data observability capabilities for its analytics and automation platform.

With Dynatrace® Data Observability, teams can confidently rely on all observability, security, and business events data in Dynatrace to fuel the platform’s Davis® AI engine to help eliminate false positives and deliver trustworthy business analytics and reliable automations.

Dynatrace Data Observability enables business analytics, data science, DevOps, SRE, security, and other teams to help ensure all data in the Dynatrace® platform is high quality. This complements the platform’s existing data cleansing and enrichment capabilities provided by Dynatrace OneAgent® to help ensure high quality for data collected via other external sources, including open source standards, such as OpenTelemetry, and custom instrumentation, such as logs and Dynatrace APIs. It enables teams to track the freshness, volume, distribution, schema, lineage, and availability of these externally sourced data, thereby reducing or eliminating the need for additional data cleansing tools.

Dynatrace Data Observability works with other core Dynatrace® platform technologies, including Davis hypermodal AI combining predictive, causal, and generative AI capabilities, to provide data-driven teams with the following benefits:

- Freshness: Helps ensure the data used for analytics and automation is up-to-date and timely and alerts to any issues—for example, out-of-stock inventory, changes in product pricing, and timestamp anomalies.

- Volume: Monitors for unexpected increases, decreases, or gaps in data—for example, the number of reported customers using a particular service—which can indicate undetected issues.

- Distribution: Monitors for patterns, deviations, or outliers from the expected way data values are spread in a dataset, which can signal issues in data collection or processing.

- Schema: Tracks data structure and alerts on unexpected changes, such as new or deleted fields, to prevent unexpected outcomes like broken reports and dashboards.

- Lineage: Delivers precise root-cause detail into the origins of data and what services it will impact downstream, helping teams proactively identify and resolve data issues before they impact users or customers.

- Availability: Leverages the Dynatrace platform’s infrastructure observability capabilities to observe digital services’ usage of servers, networking, and storage, alerting on abnormalities such as downtime and latency, to provide a steady flow of data from these sources for healthy analytics and automation.

“Data quality and reliability are vital for organizations to perform, innovate, and comply with industry regulations,” said Bernd Greifeneder, CTO at Dynatrace. “A valuable analytics solution must detect issues in the data that fuels analytics and automation as early as possible. Dynatrace OneAgent has always helped ensure that the data it collects is of the highest quality. By adding data observability capabilities to our unified and open platform, we’re enabling our customers to harness the power of data from more sources for more analytics and automation possibilities while maintaining the health of their data, without any extra tools.”

Dynatrace Data Observability is expected to be generally available for all Dynatrace SaaS customers within 90 days of this announcement.

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Dynatrace Unveils Data Observability for Analytics and Automation Platform

Dynatrace announced new AI-powered data observability capabilities for its analytics and automation platform.

With Dynatrace® Data Observability, teams can confidently rely on all observability, security, and business events data in Dynatrace to fuel the platform’s Davis® AI engine to help eliminate false positives and deliver trustworthy business analytics and reliable automations.

Dynatrace Data Observability enables business analytics, data science, DevOps, SRE, security, and other teams to help ensure all data in the Dynatrace® platform is high quality. This complements the platform’s existing data cleansing and enrichment capabilities provided by Dynatrace OneAgent® to help ensure high quality for data collected via other external sources, including open source standards, such as OpenTelemetry, and custom instrumentation, such as logs and Dynatrace APIs. It enables teams to track the freshness, volume, distribution, schema, lineage, and availability of these externally sourced data, thereby reducing or eliminating the need for additional data cleansing tools.

Dynatrace Data Observability works with other core Dynatrace® platform technologies, including Davis hypermodal AI combining predictive, causal, and generative AI capabilities, to provide data-driven teams with the following benefits:

- Freshness: Helps ensure the data used for analytics and automation is up-to-date and timely and alerts to any issues—for example, out-of-stock inventory, changes in product pricing, and timestamp anomalies.

- Volume: Monitors for unexpected increases, decreases, or gaps in data—for example, the number of reported customers using a particular service—which can indicate undetected issues.

- Distribution: Monitors for patterns, deviations, or outliers from the expected way data values are spread in a dataset, which can signal issues in data collection or processing.

- Schema: Tracks data structure and alerts on unexpected changes, such as new or deleted fields, to prevent unexpected outcomes like broken reports and dashboards.

- Lineage: Delivers precise root-cause detail into the origins of data and what services it will impact downstream, helping teams proactively identify and resolve data issues before they impact users or customers.

- Availability: Leverages the Dynatrace platform’s infrastructure observability capabilities to observe digital services’ usage of servers, networking, and storage, alerting on abnormalities such as downtime and latency, to provide a steady flow of data from these sources for healthy analytics and automation.

“Data quality and reliability are vital for organizations to perform, innovate, and comply with industry regulations,” said Bernd Greifeneder, CTO at Dynatrace. “A valuable analytics solution must detect issues in the data that fuels analytics and automation as early as possible. Dynatrace OneAgent has always helped ensure that the data it collects is of the highest quality. By adding data observability capabilities to our unified and open platform, we’re enabling our customers to harness the power of data from more sources for more analytics and automation possibilities while maintaining the health of their data, without any extra tools.”

Dynatrace Data Observability is expected to be generally available for all Dynatrace SaaS customers within 90 days of this announcement.

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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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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

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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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Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...