Difference between revisions of "Analytics"
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* [http://www.forbes.com/sites/forbestechcouncil/2019/07/23/will-ai-kill-the-dashboard/#196615a1cb5b Will AI Kill The Dashboard? | Ashok Santhanam - Forbes] | * [http://www.forbes.com/sites/forbestechcouncil/2019/07/23/will-ai-kill-the-dashboard/#196615a1cb5b Will AI Kill The Dashboard? | Ashok Santhanam - Forbes] | ||
* [http://www.eckerson.com/articles/beyond-the-dashboard-how-ai-changes-the-way-we-measure-business Beyond the Dashboard: How AI Changes the Way We Measure Business | Wayne Eckerson] | * [http://www.eckerson.com/articles/beyond-the-dashboard-how-ai-changes-the-way-we-measure-business Beyond the Dashboard: How AI Changes the Way We Measure Business | Wayne Eckerson] | ||
| + | * [http://www.healthcareitnews.com/news/cios-guide-dashboard-ai Global Edition A CIO's guide to AI dashboards | Bill Siwicki - HealthcareITNews] | ||
| + | * [http://www.zdnet.com/article/the-new-new-relic-past-bi-and-the-dashboard-toward-ai-and-aiops/ The new New Relic: Past BI and the dashboard, toward AI and AIOps | George Anadiotis - ZDNet] | ||
Instead of long investigations and analysis through multiple business Key Performance Indicator (KPI) dashboards and making manual correlations, business analysts can rely on AI analytics to probe deeper into the data and correlate simultaneous anomalies, revealing critical insights into operations. A real-time, large-scale automated anomaly detection system using machine learning methods can free data analysts from constant manual monitoring around just a few KPIs. When working with thousands or millions of metrics, you can’t just hire a staff of thousands of analysts to analyze your data for key decisions. Using automated significance ranking of detected anomalies, data analysts can focus in on the most important business incidents. [http://www.anodot.com/blog/ai-analytics-will-replace-kpi-dashboards/ In the Automation Age: Use AI Analytics to Escape ‘Business KPI Dashboard Hell’ | Ira Cohen -anodot] | Instead of long investigations and analysis through multiple business Key Performance Indicator (KPI) dashboards and making manual correlations, business analysts can rely on AI analytics to probe deeper into the data and correlate simultaneous anomalies, revealing critical insights into operations. A real-time, large-scale automated anomaly detection system using machine learning methods can free data analysts from constant manual monitoring around just a few KPIs. When working with thousands or millions of metrics, you can’t just hire a staff of thousands of analysts to analyze your data for key decisions. Using automated significance ranking of detected anomalies, data analysts can focus in on the most important business incidents. [http://www.anodot.com/blog/ai-analytics-will-replace-kpi-dashboards/ In the Automation Age: Use AI Analytics to Escape ‘Business KPI Dashboard Hell’ | Ira Cohen -anodot] | ||
Revision as of 10:47, 31 December 2019
YouTube search... ...Google search
- Capabilities
- Assistants
- Bot Framework
- Natural Language Processing (NLP)
- 2020 will be the year AI kills company dashboards | Derek Steer - TNW (TheNextWeb)
- Will AI Kill The Dashboard? | Ashok Santhanam - Forbes
- Beyond the Dashboard: How AI Changes the Way We Measure Business | Wayne Eckerson
- Global Edition A CIO's guide to AI dashboards | Bill Siwicki - HealthcareITNews
- The new New Relic: Past BI and the dashboard, toward AI and AIOps | George Anadiotis - ZDNet
Instead of long investigations and analysis through multiple business Key Performance Indicator (KPI) dashboards and making manual correlations, business analysts can rely on AI analytics to probe deeper into the data and correlate simultaneous anomalies, revealing critical insights into operations. A real-time, large-scale automated anomaly detection system using machine learning methods can free data analysts from constant manual monitoring around just a few KPIs. When working with thousands or millions of metrics, you can’t just hire a staff of thousands of analysts to analyze your data for key decisions. Using automated significance ranking of detected anomalies, data analysts can focus in on the most important business incidents. In the Automation Age: Use AI Analytics to Escape ‘Business KPI Dashboard Hell’ | Ira Cohen -anodot
