{"id":5513,"date":"2013-01-23T18:11:30","date_gmt":"2013-01-23T18:11:30","guid":{"rendered":"http:\/\/cloudnewsdaily.com\/?p=14150"},"modified":"2013-01-23T18:11:30","modified_gmt":"2013-01-23T18:11:30","slug":"anomaly-detective-adds-predictive-analytics-to-splunk","status":"publish","type":"post","link":"https:\/\/icloud.pe\/blog\/anomaly-detective-adds-predictive-analytics-to-splunk\/","title":{"rendered":"Anomaly Detective Adds Predictive Analytics to Splunk"},"content":{"rendered":"<\/p>\n

Prelert<\/a> today announced\u00a0Anomaly Detective<\/a>, an advanced machine intelligence solution for\u00a0Splunk<\/a> Enterprise environments. The introduction of Anomaly Detective expands Prelert\u2019s line of diagnostic predictive analytics products that integrate with a customer\u2019s existing IT management tools and quickly provide value by finding problematic behavior changes hidden in huge volumes of operations data.<\/p>\n

Anomaly Detective\u2019s self-learning predictive analytics with machine intelligence assistance recognize both normal and abnormal machine behavior. Using highly advanced pattern recognition algorithms, Anomaly Detective identifies developing issues and provides detailed diagnostic data, enabling IT experts to avoid problems or diagnose them as much as 90 percent faster than previously possible. IT personnel who utilize Splunk Enterprise software in infrastructure, applications performance and security can now additionally benefit from machine learning to automatically spot anomalies and isolate their root causes in minutes, saving time and resolving problems before the business is impacted.<\/p>\n

Anomaly Detective is\u00a0 downloadable software that installs as a tightly integrated application for Splunk Enterprise. Because it leverages recent advances in machine intelligence, Anomaly Detective is 100 percent self-learning and requires minimal configuration. Anomaly Detective augments existing IT expertise, empowering IT staff to spend less time mining data, reduce troubleshooting costs and improve compliance with service-level agreements \u2014 all of which contribute to a rapid return on investment.<\/p>\n

\u201cPrelert Anomaly Detective is like a machine intelligence assistant, using advanced machine learning analytics to analyze the massive amounts of IT operations management data produced by today\u2019s online applications and services,\u201d said Mark Jaffe, CEO of Prelert. \u201cWe\u2019ve packaged the power of big data analytics, normally focused on solving business problems, in easy-to-use machine intelligence solutions that are greatly needed in the real world of IT operations.\u201d<\/p>\n

Prelert Anomaly Detective is now available and easily downloadable from the\u00a0Prelert website<\/a>\u00a0and from Prelert resellers. Pricing is based on the amount of data analyzed per day, starting at $1,200 for environments indexing more than 500MB of data per day. For information on pricing for Splunk Enterprise, go to\u00a0http:\/\/www.splunk.com\/view\/how-to-get-splunk\/SP-CAAADFV<\/a>.<\/p>\n

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<\/p>\n","protected":false},"excerpt":{"rendered":"

Prelert today announced\u00a0Anomaly Detective, an advanced machine intelligence solution for\u00a0Splunk Enterprise environments. The introduction of Anomaly Detective expands Prelert\u2019s line of diagnostic predictive analytics products that integrate with a customer\u2019s existing IT management tools and quickly provide value by finding problematic behavior changes hidden in huge volumes of operations data. Anomaly Detective\u2019s self-learning predictive analytics […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1178,1383,780,1384,48,1385,1215],"tags":[],"class_list":["post-5513","post","type-post","status-publish","format-standard","hentry","category-analytics","category-artificial-intelligence","category-cloud-it-management","category-machine-learning","category-partnerships","category-prelert","category-splunk"],"_links":{"self":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/5513","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/comments?post=5513"}],"version-history":[{"count":0,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/5513\/revisions"}],"wp:attachment":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/media?parent=5513"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/categories?post=5513"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/tags?post=5513"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}