This sponsored post is produced in association with Prelert.
Getting insights from big data often depends on detecting anomalies in the data, for example, identifying users who are doing unusual transactions, or doing statistically more or less transactions than other users.
[aditude-amp id="flyingcarpet" targeting='{"env":"staging","page_type":"article","post_id":1539327,"post_type":"sponsored","post_chan":"sponsored","tags":null,"ai":false,"category":"none","all_categories":"big-data,business,","session":"A"}']With companies like Prelert, you no longer have to be a data scientist to have access to this kind of intel.
“We’re democratizing data science,” explains Steve Dodson, CTO Prelert. “With the shortage of data scientists, we’re enabling end users to get these advanced statistical capabilities of anomaly detection in a consumable package.” Whether it’s system administrators or security analysts, a set of simple commands allows users to extract valuable insights without needing to know the deep science behind it.
And as Dodson explained to VentureBeat, Prelert has also released an open API of their product so that developers can integrate this kind of feature without the cost and expense of building it themselves.
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