Evolven's Blended Analytics Solution Delivers Efficient Operational Insight
JERSEY CITY, NJ: The most powerful version of ITOA (IT Operations Analytics) software, named, Blended Analytics Solution has been released by Evolven. This new version of the application correlates data from different sources with changes.
Modern IT infrastructure is changing at an exceptional pace. The complexity of handling the data at this speed is greater than ever, and IT still operates in silos. Sasha Gilenson, CEO, Evolven explains, “The volume, velocity, and variety of the data IT operations is up against deserves to be called a big data problem. Most of the existing ITOA solutions do not yet fully apply machine learning, such as advanced statistical analysis or even domain-specific heuristics, to offer truly intelligent analytics”, in an article cited for the website, cmcrossroads.com.
The analytics must provide details such that the decisions drawn must be reliable. Such an accuracy can be entailed when all relevant data is accessible. "Now IT operations management can take the guesswork out of the decision making process and get actionable insights for preventing and troubleshooting incidents," continues Gilenson.
Blended Analytics Solution correlates Symptoms, IT Context data with Changes – the true root cause for performance and availability incidents. Evolven’s Analytics Engine also performs data cleansing, correlation to prepare high volumes of diverse, cross silo data for analysis. It also performs risk assessment.
The salient features of Blended Analytics Solution are —
Blending Cross Silos Data Sources: All relevant data sources required for effective analysis in a contextual model has been blended together.
Symptoms: Indicates undesirable conditions in the health of a business system.
Changes: A critical but frequently overlooked data source is actual changes. This includes changes in Configuration, Data, Capacity, Workload, and Code.
IT Context: Understanding the activities carried out or planned by IT gives context to the analysis.
Change Centric: Focuses on change as the true root cause of performance and availability issues.
Powerful, Machine Learning Based Analytics: Data is made meaningful, actionable by analyzing the data based on machine learning, anomaly detection and domain specific heuristics.