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Advanced IT Analytics, AIOps and Big Data - 7 Key Takeaways - Part 2

Dennis Drogseth

The goal of EMA's latest research was to look at how advanced IT analytics (AIA) — EMA's term for primarily what today is best known as "AIOps" — is being deployed. Here are the remaining four of my seven personal takeaways.

Start with Advanced IT Analytics, AIOps and Big Data - 7 Key Takeaways - Part 1

For a much more focused exploration of the "IT analytic universe," one that's all digestible within 45 minutes (including Q&A), register for the upcoming EMA webinar on October 10.

4. Capturing interdependencies and CMDB/CMS

Capturing interdependencies and CMDB/CMS both stood out in importance. As an average, respondents sought to capture nearly five interdependencies across the application/infrastructure, while 54% of respondents viewed the CMDB as "extremely important" to their analytics strategy, a surprising valuation that correlated strongly with success.

The implications of this may seem to contradict notions that the CMDB is "old hat" technology. Rather, what's indicated in these findings is that CMDB/CMS and application/infrastructure dependency mapping are technology areas that are both being reinvigorated by AIA/AIOps investments, while also providing valuable contexts for leveraging and optimizing analytic insights for a variety of use cases.

5. Security on the rise

Security is on the rise. Priorities in cloud, vendor selection, heuristics, and best practices all indicate that security is a leading and largely integrated concern in advanced IT analytics, and AIOps in particular. This was not altogether a surprise given similar findings inEMA's 2016 research (EMA Research: Advanced IT Analytics: A Look at Real-World Adoptions in the Real World, March 2016).

Moreover, it is both a welcome and a much-needed advance, as the trend toward a true SecOps (security + operations) integration across IT organizations is becoming ever more critical given rising vulnerabilities, as well as the growing demand for OpEx efficiencies across IT.

6. Top-down is winning strategy

Top-down for everything is the winning strategy. It is also the most pervasive. The executive suite (VP and above) was more likely to be successful, and more likely to drive AIA strategies, deployment and purchasing decisions.

The reasons for this make sense once AIA/AIOps is understood as a unifying technology that can help to bring IT silos closer together with shared data and common insights. But to realize this advantage fully, process issues, organizational barriers and even habits of mind can be transformed through improved dialog and leadership.

7. Advanced analytics show strong evolutionary values

Advanced analytics are showing strong evolutionary values compared to prior years. EMA research from early 2016 and 2014 (EMA Research: The Many Faces of Advanced Operations Analytics, September 2014) indicate strong growth in heuristics, data sources, integrations, stakeholder roles, and overall versatility in terms of function and purpose.

The implications are that AIA/AIOps solutions are evolving dramatically in terms of functionality, use-case and breadth.

Here, the progress wasn't surprising, but the degree of progress in terms of hard numbers actually was.

… and there's a lot more.

There was no "spoiler's alert" at the beginning because the real proof of the pudding is the hard data and the many other insights that I plan on sharing during the webinar in October.

But hopefully you'll find some of the discoveries mentioned here intriguing, and as always, I welcome your thoughts and comments at drogseth@emausa.com.

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Advanced IT Analytics, AIOps and Big Data - 7 Key Takeaways - Part 2

Dennis Drogseth

The goal of EMA's latest research was to look at how advanced IT analytics (AIA) — EMA's term for primarily what today is best known as "AIOps" — is being deployed. Here are the remaining four of my seven personal takeaways.

Start with Advanced IT Analytics, AIOps and Big Data - 7 Key Takeaways - Part 1

For a much more focused exploration of the "IT analytic universe," one that's all digestible within 45 minutes (including Q&A), register for the upcoming EMA webinar on October 10.

4. Capturing interdependencies and CMDB/CMS

Capturing interdependencies and CMDB/CMS both stood out in importance. As an average, respondents sought to capture nearly five interdependencies across the application/infrastructure, while 54% of respondents viewed the CMDB as "extremely important" to their analytics strategy, a surprising valuation that correlated strongly with success.

The implications of this may seem to contradict notions that the CMDB is "old hat" technology. Rather, what's indicated in these findings is that CMDB/CMS and application/infrastructure dependency mapping are technology areas that are both being reinvigorated by AIA/AIOps investments, while also providing valuable contexts for leveraging and optimizing analytic insights for a variety of use cases.

5. Security on the rise

Security is on the rise. Priorities in cloud, vendor selection, heuristics, and best practices all indicate that security is a leading and largely integrated concern in advanced IT analytics, and AIOps in particular. This was not altogether a surprise given similar findings inEMA's 2016 research (EMA Research: Advanced IT Analytics: A Look at Real-World Adoptions in the Real World, March 2016).

Moreover, it is both a welcome and a much-needed advance, as the trend toward a true SecOps (security + operations) integration across IT organizations is becoming ever more critical given rising vulnerabilities, as well as the growing demand for OpEx efficiencies across IT.

6. Top-down is winning strategy

Top-down for everything is the winning strategy. It is also the most pervasive. The executive suite (VP and above) was more likely to be successful, and more likely to drive AIA strategies, deployment and purchasing decisions.

The reasons for this make sense once AIA/AIOps is understood as a unifying technology that can help to bring IT silos closer together with shared data and common insights. But to realize this advantage fully, process issues, organizational barriers and even habits of mind can be transformed through improved dialog and leadership.

7. Advanced analytics show strong evolutionary values

Advanced analytics are showing strong evolutionary values compared to prior years. EMA research from early 2016 and 2014 (EMA Research: The Many Faces of Advanced Operations Analytics, September 2014) indicate strong growth in heuristics, data sources, integrations, stakeholder roles, and overall versatility in terms of function and purpose.

The implications are that AIA/AIOps solutions are evolving dramatically in terms of functionality, use-case and breadth.

Here, the progress wasn't surprising, but the degree of progress in terms of hard numbers actually was.

… and there's a lot more.

There was no "spoiler's alert" at the beginning because the real proof of the pudding is the hard data and the many other insights that I plan on sharing during the webinar in October.

But hopefully you'll find some of the discoveries mentioned here intriguing, and as always, I welcome your thoughts and comments at drogseth@emausa.com.

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...