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Machine Learning Capabilities Drive New Versions of Splunk Products
Splunk Inc. (NASDAQ: SPLK), provider of the leading software platform for real-time Operational Intelligence, today announced new versions of Splunk® Enterprise, Splunk IT Service Intelligence (ITSI), Splunk Enterprise Security (ES) and Splunk User Behavior Analytics (UBA). Available on-premises or in the cloud, the newest versions of Splunk solutions leverage machine learning to make it faster and easier to maximize the value machine data can deliver to organizations.
Machine learning is bringing big data analytics into a new era, and Splunk is enabling companies to use predictive analytics to help optimize IT, security and business operations. Machine learning is being integrated as a core capability of the Splunk portfolio with packaged or custom algorithms to operationalize machine data in a variety of valuable use cases such as:
Focused Investigation: Identify and resolve IT and security incidents by automatically detecting anomalies and patterns in data.
Intelligent Alerting: Reduce alert fatigue by identifying normal patterns for specific sets of circumstances.
Predictive Actions: Anticipate and react to circumstances such as proactive maintenance that might otherwise disrupt operations or revenue.
Business Optimization: Forecast demand, manage inventory and react to changing conditions through analysis of historical data and models.
“Digital transformation has changed the way that organizations work. The big secret is that all of the change is underpinned by machine data. Machine learning enables organizations to get deeper insights from their machine data and ultimately increases the opportunity our customers can gain from digital transformation,” said Doug Merritt, President and CEO, Splunk. “The enterprise machine data fabric is the foundation for managing and deriving insights from that data at scale – and only Splunk provides the end-to-end analytics platform and ecosystem to support it.”
“At Intuit, we have grown and thrived for over thirty years by constantly transforming and re-inventing ourselves. Splunk has been a key technology in our journey for nearly ten years,” said Brian Ellison, vice president and chief architect at Intuit. “Hundreds of our employees go to Splunk solutions every day for answers and insights into complex IT and business questions. Splunk’s use of machine learning will strengthen its platform and can drive more value for our employees and customers.”
“Splunk supports pre-packaged content and visualizations for a wide variety of use cases, including IT operations, security and business analytics,” said Jason Stamper, data platforms and analytics analyst, 451 Research. “This is making Splunk-based analytics available to an increasing variety of IT and business users. With a broad integration of machine learning, Splunk provides a comprehensive answer to one of the biggest challenges facing modern organizations: how to harness diverse, prevalent and increasingly profuse amounts of data to gain valuable business insights.”
Splunk Cloud and Splunk Enterprise 6.5: New Innovations in Machine Learning and Data Analysis
Splunk Cloud and Splunk Enterprise make it even faster and easier to maximize the value of machine data. Splunk Cloud and Splunk Enterprise 6.5, generally available today, now provide custom machine learning and deliver a totally new user experience for data analysis and preparation, and much more. With Splunk Enterprise 6.5, customers can:
– Harness the power of machine learning with advanced analytics delivered by a rich set of commands and a guided workbench to create custom machine learning models for IT, security and business use cases.
– Simplify data preparation and expand data analysis to a wider range of users with a new intuitive interface and table data views designed for both specialist and occasional users.
– Lower on-premises TCO through tighter integration with Hadoop. Organizations can now roll historical data to Hadoop and utilize hybrid search to analyze all of their data in Splunk.
Splunk ITSI: Simplify Operations, Prioritize Problems and Align IT Through Machine Learning
Splunk ITSI, built on the powerful Splunk Platform, is a machine learning-powered monitoring solution that employs analytics to help organizations find root cause faster and lower mean-time-to-resolution by providing unified service visibility, detecting emerging problems, and simplifying incident investigations and workflows. Splunk ITSI 2.4, generally available today, applies machine learning to event data to help improve productivity across IT and the business. Splunk ITSI can help organizations:
– Improve service operations with pre-built machine learning by baselining normal operational patterns to dynamically adapt thresholds, thereby reducing alert fatigue, improving analysis and increasing reliability.
– Present real-time service insights and drive decision making by prioritizing incidents through event analytics, such as multivariate anomaly detection, supported with business and services context.
– Gain a single view of operations with an intuitive interface that prevents costly customizations through the flexibility, speed and scale of the Splunk platform.
Splunk ES and Splunk UBA: Advance Analytics-Driven Security with Adaptive Response and Improved Threat Detection
Splunk advances its analytics-driven security vision and security analytics leadership with the new releases of Splunk ES and Splunk UBA. Splunk ES 4.5 provides a common interface for automating retrieval, sharing and response in multi-vendor environments. Splunk UBA 3.0 delivers new machine learning models, additional data sources and content updates of use cases. Splunk security updates help customers:
– Improve detection, investigation and remediation times by centrally automating retrieval, sharing and response through Adaptive Response and analytics-driven decision making in Splunk ES.
– Simplify analysis by understanding the impact of security metrics within a logical or physical Glass Table view in Splunk ES.
– Improve threat detection with use case updates in Splunk UBA, and gain targeted detection by prioritizing outcomes generated by packaged machine learning-based anomaly detection.