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Adoption Rates of Advanced Analytics on the Rise

Pete Goldin
APMdigest

Advanced analytics is reaching an inflection point in adoption by both mid-market organizations and large enterprises in an effort to gain a competitive advantage, according to research commissioned by Dell Services and executed by the International Institute for Analytics (IIA).

According to the study, advanced analytics is becoming core to the business rather than a separate stand-alone program. More than 70 percent of firms indicated their company is actively using or has near-term plans to use analytics in everyday decision-making. However, only five percent of early adopters believe that they have already achieved the highest level of analytical maturity, implying that we have just scratched the surface of how Advanced Analytics can be used.

Firms across all industries see the value of data and analytics, are investing in capabilities, but still have work ahead to manage an analytics program in house and see the true potential of the data.

The research also found that advanced analytics plays a critical role in many respondents’ operations, and that they expect to gain a competitive advantage in the future due to successful data mining. Nearly two-thirds strongly disagree that analytics is just a fad. Respondents indicate using advanced analytics for a variety of tasks, with nearly half indicating they use advanced analytics to predict their firm’s financial performance, and about four-in-ten mentioning differing tasks that involve customer recruitment, retention, loyalty programs and product usage habits.

"This study indicates that customers believe advanced analytics offers significant business benefits and continued investments can help advance business maturity levels. Companies and leaders across industries are at a tipping point. We’re seeing our customers place a higher priority on using advanced analytics to execute on their digital business models," said Raman Sapra, Executive Director & Global Head of Dell Digital Business Services. "Ultimately, business leaders want to develop digital business models that enable them to attract, serve, and retain customers in the digital era. Advanced analytics provides that actionable insight that enables their transformation."

The study also found that customers are focused on proof of concept for advanced analytics. Half of survey respondents either have implemented or are in the process of implementing advanced analytics technology driven solutions today. The remainder either do not have the need or they recognize a need but have not yet made an investment.

Pete Goldin is Editor and Publisher of APMdigest

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Adoption Rates of Advanced Analytics on the Rise

Pete Goldin
APMdigest

Advanced analytics is reaching an inflection point in adoption by both mid-market organizations and large enterprises in an effort to gain a competitive advantage, according to research commissioned by Dell Services and executed by the International Institute for Analytics (IIA).

According to the study, advanced analytics is becoming core to the business rather than a separate stand-alone program. More than 70 percent of firms indicated their company is actively using or has near-term plans to use analytics in everyday decision-making. However, only five percent of early adopters believe that they have already achieved the highest level of analytical maturity, implying that we have just scratched the surface of how Advanced Analytics can be used.

Firms across all industries see the value of data and analytics, are investing in capabilities, but still have work ahead to manage an analytics program in house and see the true potential of the data.

The research also found that advanced analytics plays a critical role in many respondents’ operations, and that they expect to gain a competitive advantage in the future due to successful data mining. Nearly two-thirds strongly disagree that analytics is just a fad. Respondents indicate using advanced analytics for a variety of tasks, with nearly half indicating they use advanced analytics to predict their firm’s financial performance, and about four-in-ten mentioning differing tasks that involve customer recruitment, retention, loyalty programs and product usage habits.

"This study indicates that customers believe advanced analytics offers significant business benefits and continued investments can help advance business maturity levels. Companies and leaders across industries are at a tipping point. We’re seeing our customers place a higher priority on using advanced analytics to execute on their digital business models," said Raman Sapra, Executive Director & Global Head of Dell Digital Business Services. "Ultimately, business leaders want to develop digital business models that enable them to attract, serve, and retain customers in the digital era. Advanced analytics provides that actionable insight that enables their transformation."

The study also found that customers are focused on proof of concept for advanced analytics. Half of survey respondents either have implemented or are in the process of implementing advanced analytics technology driven solutions today. The remainder either do not have the need or they recognize a need but have not yet made an investment.

Pete Goldin is Editor and Publisher of APMdigest

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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 ...

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Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...