Ignore Big Data in 2013 At Your Own Peril

Pete Goldin
APMdigest

In the Inc. special report on How (and Where) to Make Money in 2013 (and Beyond), author Erik Sherman places Big Data on the list of 5 Trends to Ignore in 2013. In contrast, I suggest that ignoring Big Data is not a business savvy move in 2013.

Sherman says: "Everyone needs big data, if you read the business and technology magazines. But the term has become an amorphous catch phrase that covers everything. Real big data involves millions or even billions of data points. We're talking complicated tasks like predicting the weather, or Google looking for trends among all the search queries it sees day in, day out."

"That level of data analysis is probably nowhere near what you need for your business," he adds. "Most decisions are built on small data: dozens or hundreds or maybe thousands of data points. If you don't have systems in place that let you regularly and predictably make effective use of the data you already have, then looking at big data is like saying you want to jump into the ocean to avoid getting damp from a summer shower."

Application Performance Management is the perfect example of why Sherman is wrong. IT monitoring can produce millions and even billions of metrics. And the technology is out there to crunch those metrics and analyze them, and help improve application performance.

In an article about a Big Data survey, I said: With the growth of IT infrastructure, as well as the growth of applications and their complexity, comes an increase in performance metrics. In fact, 83% of respondents agreed with Gartner’s estimate that metric collection has increased 300% or more in the last four years. And one respondent from a large corporation has seen the IT estate grow tenfold, to the point where they now collect over a billion metrics daily.

Several respondents also confirmed that APM tools are part of the huge explosion in metric collection, generating thousands of KPIs per application.

Today, analytics technologies are emerging that can make sense out of this Big Data. This technology has a starring role in APMdigest's APM Predictions for 2013.

“There’s no question that Big Data has become a driver for Advanced Performance Analytics (APA), where capabilities for processing tens of millions of KPIs or data points in real time or near real time is becoming more and more common,” said Dennis Drogseth, VP, Application and Business Services at EMA, in an APMdigest article.

In an APMdigest blog Graham Gillen of Netuitive says: "The results are well documented with one global telco reporting that it is using Behavior Learning technology and predictive analytics to analyze more than a million metrics simultaneously allowing it to eliminate 3,480 hours annually in service degradation representing a business savings of $18 million."

APM is just one example of why businesses should be paying attention to Big Data in 2013.

I would say that ignoring Big Data in business in 2013 is like ignoring a locomotive while standing on the tracks.

Pete Goldin is Editor and Publisher of APMdigest

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Ignore Big Data in 2013 At Your Own Peril

Pete Goldin
APMdigest

In the Inc. special report on How (and Where) to Make Money in 2013 (and Beyond), author Erik Sherman places Big Data on the list of 5 Trends to Ignore in 2013. In contrast, I suggest that ignoring Big Data is not a business savvy move in 2013.

Sherman says: "Everyone needs big data, if you read the business and technology magazines. But the term has become an amorphous catch phrase that covers everything. Real big data involves millions or even billions of data points. We're talking complicated tasks like predicting the weather, or Google looking for trends among all the search queries it sees day in, day out."

"That level of data analysis is probably nowhere near what you need for your business," he adds. "Most decisions are built on small data: dozens or hundreds or maybe thousands of data points. If you don't have systems in place that let you regularly and predictably make effective use of the data you already have, then looking at big data is like saying you want to jump into the ocean to avoid getting damp from a summer shower."

Application Performance Management is the perfect example of why Sherman is wrong. IT monitoring can produce millions and even billions of metrics. And the technology is out there to crunch those metrics and analyze them, and help improve application performance.

In an article about a Big Data survey, I said: With the growth of IT infrastructure, as well as the growth of applications and their complexity, comes an increase in performance metrics. In fact, 83% of respondents agreed with Gartner’s estimate that metric collection has increased 300% or more in the last four years. And one respondent from a large corporation has seen the IT estate grow tenfold, to the point where they now collect over a billion metrics daily.

Several respondents also confirmed that APM tools are part of the huge explosion in metric collection, generating thousands of KPIs per application.

Today, analytics technologies are emerging that can make sense out of this Big Data. This technology has a starring role in APMdigest's APM Predictions for 2013.

“There’s no question that Big Data has become a driver for Advanced Performance Analytics (APA), where capabilities for processing tens of millions of KPIs or data points in real time or near real time is becoming more and more common,” said Dennis Drogseth, VP, Application and Business Services at EMA, in an APMdigest article.

In an APMdigest blog Graham Gillen of Netuitive says: "The results are well documented with one global telco reporting that it is using Behavior Learning technology and predictive analytics to analyze more than a million metrics simultaneously allowing it to eliminate 3,480 hours annually in service degradation representing a business savings of $18 million."

APM is just one example of why businesses should be paying attention to Big Data in 2013.

I would say that ignoring Big Data in business in 2013 is like ignoring a locomotive while standing on the tracks.

Pete Goldin is Editor and Publisher of APMdigest

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When AI Becomes the Corporate OS

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

The $600 Billion Wake Up Call

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Breaking Down Agentic AI Fragmentation and Complexity with Governance

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud Spend Is Rising and Cloud Optimization Is Key to Funding AI and Protecting Margins

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

Building AI Agents That Build Trust

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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