icon_CloudMgmt icon_DollarSign icon_Globe icon_ITAuto icon_ITOps icon_ITSMgmt icon_Mainframe icon_MyIT icon_Ribbon icon_Star icon_User icon_Users icon_VideoPlay icon_Workload icon_caution icon_close s-chevronLeft s-chevronRight s-chevronThinRight s-chevronThinRight s-chevronThinLeft s-chevronThinLeft s-trophy s-chevronDown
BMC Contact Options

Select the link below that best matches your interest.

For questions about BMC products, solutions, and services, you can also phone the number below:


What is IT Operations Analytics?

IT Operations Analytics (ITOA) automates the process of collecting, organizing, and identifying patterns in highly distributed, diverse and fast-changing service and application data to identify problems faster and improve IT system performance.

IT Operations Analytics

The modern digital business revolution infuses technology in every step of an organization’s value chain. This unprecedented use of technology creates a complex challenge for IT Infrastructure and Operations organizations, as it becomes difficult to collect and organize the explosion of data generated by new digital business systems and sources.

Operational analytics gives IT Operations Management (ITOM) teams the right information, at the right time. It allows them to quickly focus their efforts, reduce the time it takes to solve problems, proactively identify issues and optimize system and application performance to support business needs.

Video: TrueSight Intelligence makes sense of your data

Get fast, accurate analytics that create insight at the intersection of data and the digital business. (1:54)

Find out how BMC can help you. Contact a sales rep ›

Fast, data-driven action with ITOA

In today’s digital business, data is the currency that guides and drives all decisions and actions. Breaking down IT information silos and automatically organizing multi-structured data from diverse, dynamic sources, operational analytics software solutions transform disconnected data points, which lack meaning, into actionable information.

IT Operations Analytics should be applied to the modern IT Infrastructure and Operations environment to:

  • Troubleshoot and anticipate problems in the application and service infrastructure through analytics integrated with existing IT Operations Management tools and practices
  • Optimize overall IT service performance and guide business decisions through a single analytics platform that contextualizes data from distributed systems through the business

Troubleshooting and problem identification

TrueSight IT Data Analytics allows you to proactively identify and detect troublesome patterns on an ongoing basis and create alerts and reports to take action before your users are affected. With TrueSight's integrated IT analytics software you'll get better IT insight – right out of the box.

  • Collect, index, and monitor logs and events for abnormalities
  • Perform ad-hoc searches of all log data across the entire IT environment from a single console
  • Correlate log data with events and service models, or application groups

As a result, empowered ITOM teams can:

  • Detect, prioritize, diagnose, and resolve service issues more quickly than ever before
  • Save successful prior resolutions and automate notifications for the fast resolution of common issues
  • Integrate event management, and log and machine data analytics for a holistic view of the entire data center

Data-driven service optimization

A single, architected platform for IT Operations Analytics transforms web scale, real-time streaming data, generated by the digital business, into meaningful, actionable insights that fuel fast, business-aligned decisions for IT. To optimize applications and IT-dependent services, the analytics platform must collect and analyze a  wide variety of data, including metric, event, log, user experience, IT service management, customer service and sentiment, business and social data, and applying big data analytics in three sequential steps:

  • Data capture and ingestion: real-time streaming, transformation, storage and indexing
  • Analytics and machine learning: automated baselines and abnormality detection, pattern discovery, statistics and probability, recommendation engine
  • Access and explore: visualize, search, correlate and compare, trend, predict and collaborate