Breaking The Limitations Of Silos With Blended Analytics


One of the most talked about areas of IT is IT Operations Analytics (ITOA). Vendors and startups have applied analytics to improve IT operational insights. However, available ITOA solutions STILL strive to make sense of IT Big Data, perpetuating operations in narrow silos. IT decision makers need to break these silos, by applying an approach that blends and analyses all relevant IT information sources. Extracting insights and drawing intelligent correlations from heterogeneous, cross silo data, Blended Analytics helps to see the whole picture.

ITOA Solutions Fall Short

Today’s ITOA solutions are limited by:

  • Silos: Who sees the full picture? While IT operations data is diverse, many ITOA vendors make existing ITOA tools (e.g. APM) “smarter” and leave IT to focus on their own data silo.
  • Symptoms: ITOA solutions focus on “symptoms” (APM, log, network) indicating problems, only responding after something an abnormality arises. Yet users may already feel the impact when ITOA observes a “symptom”. Not only that but identifying the true root-cause of problems based only on “symptoms” is very difficult.
  • Weak Analytics: ITOA components intended to enhance product suites appear as dashboards or KPI aggregations, relying on users to define data analysis algorithms, or just provide catalogues of pre-defined statistic functions.

Analytics’ Secret Sauce

To realise the value of ITOA, analytics must provide actionable insights to drive operational decisions. Blended Analytics improves the probability of early issue detection (prevention), accelerating troubleshooting by combining information from across silos, correlating symptoms and root causes as well as mapping them into context that users can grasp.

To extract insights and identify behavioural patterns and anomalies, effective Blended Analytics:

  • Collects, correlates and analyses data from heterogeneous data sources (Network, APM, Deployment Automation, Log, CMDB, Service Desk, and Changes (e.g. configuration, data, capacity, code, etc.).
  • Analyses the data stream through a prism of change, offering quick access to actual and potential root causes. A critical component, yet surprisingly often overlooked data source is changes. Nevertheless, Understanding change is critical: the first question usually asked when performance issues come up is: “what changed?” What piece of code, what configuration parameter, what data table was changed as a result of some automated or manual action, which could be authorised or not.
  • Relies on a combination of analysis approaches, including Machine Learning based anomaly detection, risk scoring, domain-specific heuristics and knowledge-base to turn the massive amount of heterogeneous data into actionable insights.

By analysing relevant data sources, focusing on change, and applying powerful analytics, a Blended Analytics approach provides useful insights.

Realising ITOA’s Promise

Business success relies on optimised IT operations. To overcome their silos, IT decision makers need to apply Blended Analytics for analysing everything that happens in IT environments, measured according to CHANGE. By collecting all relevant data sources, focusing on change and applying powerful analytics, the next generation of IT Operations Analytics tools will offer truly critical insights for maintaining stability and performance, to ultimately realise the benefits and promise of IT Operations Analytics.

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Sasha Gilenson is Chief Executive Officer, co-founder, of Evolven. Sasha enjoyed a long and successful career at Mercury Interactive (acquired by HP), having led the company's QA organisation, participating in establishing Mercury's Software as a Service (SaaS), as well as leading a Business Unit in Europe and Asia. Sasha holds an M.Sc. in Computer Science from Latvian University and MBA from London Business School.