IT operations analytics

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In the fields of Information Technology (IT) and Systems Management, IT operations analytics (ITOA) is an approach or method to retrieve, analyze, and report data for IT operations. ITOA may apply big data analytics to large datasets to produce business insights. [1] [2] In 2014, Gartner predicted its use might increase revenue or reduce costs. [3] By 2017, it predicted that 15% of enterprises will use IT operations analytics technologies. [2]

Contents

Definition

IT operations analytics (ITOA) (also known as advanced operational analytics, [4] or IT data analytics [5] ) technologies are primarily used to discover complex patterns in high volumes of often "noisy" IT system availability and performance data. [6] Forrester Research defined IT analytics as "The use of mathematical algorithms and other innovations to extract meaningful information from the sea of raw data collected by management and monitoring technologies." [7] Note, ITOA is different than AIOps, which focuses on applying artificial intelligence and machine learning to the applications of ITOA.

History

Operations research as a discipline emerged from the Second World War to improve military efficiency and decision-making on the battlefield. [8] However, only with the emergence of machine learning tech in the early 2000s could an artificially intelligent operational analytics platform actually begin to engage in the high-level pattern recognition that could adequately serve business needs. [1] A critical catalyst towards ITOA development was the rise of Google, which pioneered a predictive analytics model that represented the first attempt to read into patterns of human behavior on the Internet. IT specialists then applied predictive analytics to the IT Industry, coming forward with platforms that can sift through data to generate insights without the need for human intervention. [1]

Due to the mainstream embrace of cloud computing and the increasing desire for businesses to adopt more big data practices, the ITOA industry has grown significantly since 2010. A 2016 ExtraHop survey of large and mid-size corporations indicates that 65 percent of the businesses surveyed will seek to integrate their data silos either this year or the next. [9] The current goals of ITOA platforms are to improve the accuracy of their APM services, facilitate better integration with the data, and to enhance their predictive analytics capabilities.

Applications

ITOA systems tend to be used by IT operations teams, and Gartner describes seven applications of ITOA systems: [10]

Types

In their Data Growth Demands a Single, Architected IT Operations Analytics Platform, Gartner Research describes five types of analytics technologies: [11]

Tools and ITOA platforms

A number of vendors operate in the ITOA space:

See also

Related Research Articles

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<span class="mw-page-title-main">Analytics</span> Discovery, interpretation, and communication of meaningful patterns in data

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AppDynamics is a full-stack application performance management (APM) and IT operations analytics (ITOA) company based in San Francisco. The company focuses on managing the performance and availability of applications across cloud computing environments, IT infrastructure, network architecture, digital user experience design, application security threat detection, observability, and data centers. In March 2017, AppDynamics was acquired by Cisco for $3.7 billion. The software intelligence platform is used in enterprise and public sector SaaS applications such as the financial service sector, healthcare, telecom, manufacturing, and government for full-stack observability and IT infrastructure monitoring.

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Evolven is a technology company that provides IT operations analytics (ITOA) for businesses. Founded in 2007, Evolven is headquartered in Jersey City, New Jersey, with offices in Europe and Israel.

<span class="mw-page-title-main">Dynatrace</span> American technology company

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Artificial Intelligence for IT Operations (AIOps) is a term coined by Gartner in 2016 as an industry category for machine learning analytics technology that enhances IT operations analytics. AIOps is the acronym of "Artificial Intelligence Operations". Such operation tasks include automation, performance monitoring and event correlations among others.

In IT operations, software performance management is the subset of tools and processes in IT Operations which deals with the collection, monitoring, and analysis of performance metrics. These metrics can indicate to IT staff whether a system component is up and running (available), or that the component is behaving in an abnormal way that would impact its ability to function correctly—much like how a doctor may measure pulse, respiration, and temperature to measure how the human body is "operating". This type of monitoring originated with computer network components, but has now expanded into monitoring other components such as servers and storage devices, as well as groups of components organized to deliver specific services and Business Service Management).

References

  1. 1 2 3 "The Time Has Come: Analytics Delivers for IT Operations". Data Center Journal. Archived from the original on 24 February 2013. Retrieved 18 February 2013.
  2. 1 2 Fletcher, Colin (June 24, 2014), Apply IT Operations Analytics to Broader Datasets for Greater Business Insight , retrieved 29 September 2015[ dead link ]
  3. ↑ "IT operations analytics: Changing the IT perspective". Information Age. Retrieved 13 March 2014.
  4. ↑ "Advanced Operations Analytics - What the Data Shows!". APM Digest. Retrieved 17 September 2014.
  5. ↑ "Quintica offers BMC's TrueSight". IT-Online. Retrieved 27 October 2014.
  6. ↑ "Hype Cycle for IT Operations Management, 2013". Gartner. Retrieved 23 July 2013.
  7. ↑ "Turn Big Data Inward With IT Analytics". Forrester Research. Retrieved 5 December 2012.
  8. ↑ Kirby, p. 117 Archived 27 August 2013 at the Wayback Machine
  9. ↑ "The State of the ITOA Today" (PDF). ExtraHop. ExtraHop. Retrieved June 21, 2016.
  10. ↑ "IT Market Clock for IT Operations Management, 2013". Gartner. Retrieved 13 August 2013.
  11. ↑ "Data Growth Demands a Single, Architected IT Operations Analytics Platform". Gartner. Retrieved 30 September 2013.
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