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Are You Thinking of Investing in Advanced IT Analytics?

(Hint - it's probably a good idea)
Dennis Drogseth

There may be no more critical emerging technology for IT organizations in the digital age than advanced IT analytics (AIA) — most commonly called “operational analytics.” EMA prefers the term “advanced IT analytics” because these investments, while often centered in operations, can go far beyond classic IT operations to support IT service management (ITSM) teams, development, and the IT executive suite, as well as a growing range of business stakeholders.

AIA is also an area of incredible industry innovation. So far, at least, the leading AIA vendors have not been constrained by rigid technology-driven market definitions of the kind that, for instance, nearly doomed the evolution of configuration management databases (CMDBs).

Instead, AIA solutions are evolving in multiple flavors with a growing range of benefits — most often centered in performance and availability management for IT, but also, and increasingly, addressing change impact awareness, integrated support for change management, and even integrated capabilities for capacity planning and analytics.

It is with this in mind that EMA is launching what we believe is the first ever buyer's guide for AIA adoption: Leaders in Advanced IT Analytics: A Buyer's Guide for Investing in Innovation. To do this, EMA has invited 13 vendors — each with a distinctive footprint — which have met the following set of requirements that made them candidates for this guide.

■ Support for performance, availability and change impact awarenesswith both real-time and historical insights. We also looked for corollaries in change management, capacity planning and capacity optimization when appropriate.

■ Assimilation of data from cross-domain sources in high data volumesfor cross-domain insights, as well as insights into application/infrastructure interdependencies. These interdependency insights can be purely analytic, or affiliated with topology and/or modeling.

■ The ability to access multiple data types, e.g. events, KPIs, logs, flow, configuration data, etc.

■ Capabilities for self-learning, to deliver predictive, and/or prescriptive, and/or if/then actionable insights.

■ Support for a wide range of advanced heuristics such as multivariate analysis, machine learning, streaming data, tiered analytics, cognitive analytics, etc.

■ Use as strategic overlays that may assimilate or consolidate multiple monitoring investments.

■ Support for private cloud, public cloud, as well as hybrid/legacy environments.

Moreover, all 13 vendors have been carefully assessed and vetted in working with EMA, including validation through dialogs with customer deployments.

Who's Not Included?

This buyer's guide is directed at what EMA believes is the AIA heartland, but it is also a first step in charting the broader AIA landscape.

Saved for future evaluations are:

■ AIA solutions that do not support real-time as well as predictive performance-related insights.

■ Cross-domain AIA focused on single targeted data collection — most notably wire, packet or flow data.

■ Monitoring suites with growing investments in analytics, but which don't yet meet all the criteria listed above.

■ Domain-specific AIA — targeted at specific use cases in systems-only, or network-only arenas.

How and Where to Learn More

EMA will be launching the Buyer's Guide with a webinar on September 21, and will do our best to make it a resource for anyone in IT seriously interested in IT analytic adoption.

Our buyer's guide is not about winners or losers — but rather a detailed evaluation of each vendor's design point, attributes, capabilities, market history and unique strengths. These assessments have been supplemented with interviews with actual deployments to further inform each assessment.

Coming AIA Blogs

Looking ahead, I'll be doing follow-up blogs on the following topics:

Shopping Cart Criteria — a more detailed look at how we did our assessments

Winning strategies for AIA adoption— based on this research, as well as prior research done over the period of the last three years — including roadblocks and organizational as well as technology concerns

AIA benefits— what to look for in getting AIA successfully on board, based once again on this and three years of past research

Looking Forward and Looking Back— a broader assessment of what we learned and what we expect to see as AIA evolves

In the meantime, I do welcome your questions and comments regarding your own AIA experiences and needs. You can reach me at drogseth@emausa.com

Read the second blog in the series about AIA: Why Advanced IT Analytics Deployments Show Benefits That Are Too Good To Miss

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Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

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Are You Thinking of Investing in Advanced IT Analytics?

(Hint - it's probably a good idea)
Dennis Drogseth

There may be no more critical emerging technology for IT organizations in the digital age than advanced IT analytics (AIA) — most commonly called “operational analytics.” EMA prefers the term “advanced IT analytics” because these investments, while often centered in operations, can go far beyond classic IT operations to support IT service management (ITSM) teams, development, and the IT executive suite, as well as a growing range of business stakeholders.

AIA is also an area of incredible industry innovation. So far, at least, the leading AIA vendors have not been constrained by rigid technology-driven market definitions of the kind that, for instance, nearly doomed the evolution of configuration management databases (CMDBs).

Instead, AIA solutions are evolving in multiple flavors with a growing range of benefits — most often centered in performance and availability management for IT, but also, and increasingly, addressing change impact awareness, integrated support for change management, and even integrated capabilities for capacity planning and analytics.

It is with this in mind that EMA is launching what we believe is the first ever buyer's guide for AIA adoption: Leaders in Advanced IT Analytics: A Buyer's Guide for Investing in Innovation. To do this, EMA has invited 13 vendors — each with a distinctive footprint — which have met the following set of requirements that made them candidates for this guide.

■ Support for performance, availability and change impact awarenesswith both real-time and historical insights. We also looked for corollaries in change management, capacity planning and capacity optimization when appropriate.

■ Assimilation of data from cross-domain sources in high data volumesfor cross-domain insights, as well as insights into application/infrastructure interdependencies. These interdependency insights can be purely analytic, or affiliated with topology and/or modeling.

■ The ability to access multiple data types, e.g. events, KPIs, logs, flow, configuration data, etc.

■ Capabilities for self-learning, to deliver predictive, and/or prescriptive, and/or if/then actionable insights.

■ Support for a wide range of advanced heuristics such as multivariate analysis, machine learning, streaming data, tiered analytics, cognitive analytics, etc.

■ Use as strategic overlays that may assimilate or consolidate multiple monitoring investments.

■ Support for private cloud, public cloud, as well as hybrid/legacy environments.

Moreover, all 13 vendors have been carefully assessed and vetted in working with EMA, including validation through dialogs with customer deployments.

Who's Not Included?

This buyer's guide is directed at what EMA believes is the AIA heartland, but it is also a first step in charting the broader AIA landscape.

Saved for future evaluations are:

■ AIA solutions that do not support real-time as well as predictive performance-related insights.

■ Cross-domain AIA focused on single targeted data collection — most notably wire, packet or flow data.

■ Monitoring suites with growing investments in analytics, but which don't yet meet all the criteria listed above.

■ Domain-specific AIA — targeted at specific use cases in systems-only, or network-only arenas.

How and Where to Learn More

EMA will be launching the Buyer's Guide with a webinar on September 21, and will do our best to make it a resource for anyone in IT seriously interested in IT analytic adoption.

Our buyer's guide is not about winners or losers — but rather a detailed evaluation of each vendor's design point, attributes, capabilities, market history and unique strengths. These assessments have been supplemented with interviews with actual deployments to further inform each assessment.

Coming AIA Blogs

Looking ahead, I'll be doing follow-up blogs on the following topics:

Shopping Cart Criteria — a more detailed look at how we did our assessments

Winning strategies for AIA adoption— based on this research, as well as prior research done over the period of the last three years — including roadblocks and organizational as well as technology concerns

AIA benefits— what to look for in getting AIA successfully on board, based once again on this and three years of past research

Looking Forward and Looking Back— a broader assessment of what we learned and what we expect to see as AIA evolves

In the meantime, I do welcome your questions and comments regarding your own AIA experiences and needs. You can reach me at drogseth@emausa.com

Read the second blog in the series about AIA: Why Advanced IT Analytics Deployments Show Benefits That Are Too Good To Miss

Hot Topics

The Latest

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...