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Organizations Accumulating Data at Unprecedented Rates, Oracle Reports

Oracle announced the results of its report, From Overload to Impact: An Industry Scorecard on Big Data Business Challenges, which surveyed 333 C-level executives from US and Canadian enterprises spanning 11 industries to determine the pain points they face regarding managing the deluge of data coming into their organizations and how well they are using that information to drive profit and growth.

The data deluge is here: Ninety-four percent of C-level executives say their organization is collecting and managing more business information today than two years ago, by an average of 86 percent more.

Respondents note they see the biggest data growth areas coming from customer information (48 percent), operations (34 percent) and sales and marketing (33 percent).

Room for improvement: Executives say they are not prepared to handle the increasing amount of data they face. Twenty-nine percent of executives give their organization a “D” or “F” in preparedness to manage the data deluge, and 93 percent believe their organization is losing revenue opportunities – representing on average, 14 percent of revenue – by not being able to fully leverage the information they collect.

On average, private-sector organizations with revenues of $1 billion or more say they are losing approximately 13 percent of their annual revenue as a result of not being able to fully leverage their information. That translates to $130 million each year for a $1 billion organization. Only 8 percent of executives give their organization an “A” in preparedness.

Managers do not have or cannot get to the timely info they need: Respondents note they are frustrated with their organizations’ data gathering and distribution systems. Specifically, 38 percent note they do not have the right systems in place to gather the information they need, 36 percent cannot give their business managers access to pertinent information and need to rely on IT to compile and analyze information and 29 percent feel they are using systems that are not designed to meet the unique needs of their industry.

Setting a path forward: Ninety-seven percent of respondents note their organization must improve information optimization over the next two years. Top priorities include improving the ability to translate information into actionable insight (43 percent), acquiring tools to collect more accurate information (38 percent) and training employees to better make sense of information (38 percent).

Vertical application leap: Seventy-seven percent of organizations use industry-specific applications or software to help leverage information to make strategic decisions. The financial services (91 percent) and healthcare (87 percent) industries are most likely to use industry-specific applications.

Intelligence is a top priority: Sixty-seven percent of executives say that the ability to draw intelligence from their data is a top organizational priority.
Industry Findings

Leading the pack: Executives in the communications industry are most confident in their organizations’ preparedness for the data deluge, with 20 percent giving their organization an “A” rating. The communications, manufacturing and retail industries lose the lowest estimated percentage of additional annual revenue because of their current data management processes – 10 percent.

Flooded with data: Executives in the public sector, healthcare and utilities industries are least prepared to handle the data deluge – with 41 percent of public sector executives, 40 percent of healthcare executives and 39 percent of utilities executives giving themselves a “D” or “F” preparedness rating. The oil and gas (22 percent) and life sciences (20 percent) industries lose the greatest estimated percentage of annual revenue due to their current data management processes.

“This study shows that up to 14 percent of a company’s revenue is lost because enterprises are challenged to manage and analyze data, which grows exponentially as we speak. Enterprises can get ahead of the game by using these challenges as catalysts for company-wide strategic change. Through industry-specific applications and technologies, enterprises can transform data into measurable business benefits,” said Oracle President Mark Hurd.

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Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

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Organizations Accumulating Data at Unprecedented Rates, Oracle Reports

Oracle announced the results of its report, From Overload to Impact: An Industry Scorecard on Big Data Business Challenges, which surveyed 333 C-level executives from US and Canadian enterprises spanning 11 industries to determine the pain points they face regarding managing the deluge of data coming into their organizations and how well they are using that information to drive profit and growth.

The data deluge is here: Ninety-four percent of C-level executives say their organization is collecting and managing more business information today than two years ago, by an average of 86 percent more.

Respondents note they see the biggest data growth areas coming from customer information (48 percent), operations (34 percent) and sales and marketing (33 percent).

Room for improvement: Executives say they are not prepared to handle the increasing amount of data they face. Twenty-nine percent of executives give their organization a “D” or “F” in preparedness to manage the data deluge, and 93 percent believe their organization is losing revenue opportunities – representing on average, 14 percent of revenue – by not being able to fully leverage the information they collect.

On average, private-sector organizations with revenues of $1 billion or more say they are losing approximately 13 percent of their annual revenue as a result of not being able to fully leverage their information. That translates to $130 million each year for a $1 billion organization. Only 8 percent of executives give their organization an “A” in preparedness.

Managers do not have or cannot get to the timely info they need: Respondents note they are frustrated with their organizations’ data gathering and distribution systems. Specifically, 38 percent note they do not have the right systems in place to gather the information they need, 36 percent cannot give their business managers access to pertinent information and need to rely on IT to compile and analyze information and 29 percent feel they are using systems that are not designed to meet the unique needs of their industry.

Setting a path forward: Ninety-seven percent of respondents note their organization must improve information optimization over the next two years. Top priorities include improving the ability to translate information into actionable insight (43 percent), acquiring tools to collect more accurate information (38 percent) and training employees to better make sense of information (38 percent).

Vertical application leap: Seventy-seven percent of organizations use industry-specific applications or software to help leverage information to make strategic decisions. The financial services (91 percent) and healthcare (87 percent) industries are most likely to use industry-specific applications.

Intelligence is a top priority: Sixty-seven percent of executives say that the ability to draw intelligence from their data is a top organizational priority.
Industry Findings

Leading the pack: Executives in the communications industry are most confident in their organizations’ preparedness for the data deluge, with 20 percent giving their organization an “A” rating. The communications, manufacturing and retail industries lose the lowest estimated percentage of additional annual revenue because of their current data management processes – 10 percent.

Flooded with data: Executives in the public sector, healthcare and utilities industries are least prepared to handle the data deluge – with 41 percent of public sector executives, 40 percent of healthcare executives and 39 percent of utilities executives giving themselves a “D” or “F” preparedness rating. The oil and gas (22 percent) and life sciences (20 percent) industries lose the greatest estimated percentage of annual revenue due to their current data management processes.

“This study shows that up to 14 percent of a company’s revenue is lost because enterprises are challenged to manage and analyze data, which grows exponentially as we speak. Enterprises can get ahead of the game by using these challenges as catalysts for company-wide strategic change. Through industry-specific applications and technologies, enterprises can transform data into measurable business benefits,” said Oracle President Mark Hurd.

Hot Topic

The Latest

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ...