{"id":338177,"date":"2017-04-12T21:00:43","date_gmt":"2017-04-12T13:00:43","guid":{"rendered":"http:\/\/techcrunch.com\/?p=1475860"},"modified":"2017-04-12T21:00:43","modified_gmt":"2017-04-12T13:00:43","slug":"sisense-pulse-uses-machine-learning-to-trigger-data-anomaly-alerts","status":"publish","type":"post","link":"https:\/\/people.utm.my\/asmawisham\/sisense-pulse-uses-machine-learning-to-trigger-data-anomaly-alerts\/","title":{"rendered":"Sisense Pulse uses machine learning to trigger data anomaly alerts"},"content":{"rendered":"

<\/p>\n

Sisense<\/a> introduced a new tool today called Pulse<\/a>, which uses machine learning to\u00a0trigger an alert when it detects results outside of normal parameters for\u00a0a particular metric.<\/p>\n

A user can set a Pulse alert to monitor a\u00a0metric or KPI such as sales activity or win rate. The machine learning component watches the chosen\u00a0metric and learns over time what\u2019s normal. When it detects an anomaly, it sends an alert to the user. What\u2019s more, it can determine how the metric has changed over time, so it doesn\u2019t continue to trigger alerts for the new normal.<\/p>\n

This approach is part of Sisense\u2019s mission to simplify business intelligence, company CEO Amir Orad told TechCrunch. Last year his company introduced an Amazon Echo Skill<\/a> to allow users to ask Alexa about Sisense data. Pulse gives those users\u00a0access to data without deliberately going into the tool to seek it out.<\/p>\n

\u201cThis is a direct continuation of what we\u2019ve been doing \u2014 [this notion of] Sisense everywhere where we can push insights into the hands of users. Pulse is another step in that direction. We\u2019ve started with the ability to assign alerts on interesting stuff,\u201d he explained.<\/p>\n

In the conventional way of using a tool like Sisense, you fire it up and look at the data. As part of this process, you\u00a0may see something that\u2019s particularly interesting or crucial to you. You\u00a0can set a Pulse alert and let the system warn you\u00a0when a metric is out of whack. Orad says this is flipping the way people have typically used business intelligence tools.<\/p>\n

\"\"<\/p>\n

Photo: Sisense<\/p>\n<\/div>\n

\u201cThe value is that, traditionally you are going to your computer and asking a question and getting a report. It\u2019s more interesting when it\u2019s getting pushed to you,\u201d he said. It\u2019s certainly easier, especially\u00a0when the tool is using machine learning to look at the historical numbers related to this metric.<\/p>\n

\u201cYou plot a curve over time and see what is typical in the curve. When you get out of that curve, and there is a significant difference, you get an alert,\u201d he said.<\/p>\n

Orad says Pulse doesn\u2019t just have to produce an alert. It could also trigger an action or start a workflow. Sisense has partnered with Zapier<\/a>, a workflow tool not unlike IFTTT<\/a>, which enables users to trigger an action or set of actions based on certain conditions. In the Sisense case,\u00a0it could begin a workflow for new customers or restocking inventory (or any business process).<\/p>\n

For now, Sisense is concentrating on the power of the alerts to let users know when something has changed significantly without having to explicitly ask the tool. \u201cWe see our mission as simple: simplify complex data so that business\u00a0users can get value everywhere all the time. The only way to do that is by putting actionable intelligence in their hands,\u201d he said.<\/p>\n

Featured Image: Science Photo Library<\/a>\/Getty Images<\/small><\/p>\n","protected":false},"excerpt":{"rendered":"

\"Electrocardiogram Sisense introduced a new tool today called Pulse, which uses machine learning to\u00a0trigger an alert when it detects results outside of normal parameters for\u00a0a particular metric. A user can set a Pulse alert to monitor a\u00a0metric or KPI such as sales activity or win rate. The machine learning component watches the chosen\u00a0metric and learns over time what’s normal. When it detects an… Read More<\/a><\/p>\n

\n<\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a>\n<\/div>\n

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