While machine learning algorithms and other forms of artificial intelligence have the power to transform entire industries, most people have a well-defined set of issues where they are looking for a little extra help to accomplish daily tasks more easily.
With that issue in mind, Sisense is adding machine learning algorithms to analyze patterns within specific sets of data within a business intelligence application that doesn’t require data to be exported to a separate platform.
Sisense CEO Amir Orad says Sisense Pulse adds a module to the company’s BI application that enables end users to define a set of key performance indicators (KPIs) that they want Sisense Pulse to proactively monitor. Rather than having to continually launch queries to ascertain the status of those KPIs, Orad says end users can now be delivered automatic updates relating to how the business is performing against specific KPIs long before a problem might occur, without any assistance or intervention of the part of an internal IT organization required.
“It essentially allows an end user to subscribe to a set of a KPIs,” says Orad.
Orad notes that these days, there’s no shortage of options when it comes to applying machine learning algorithms to data. But Orad says most of those approaches are heavy handed in that they require organizations to invest in additional data warehouse platforms, some of which need to be hosted on an external data center managed by a third-party IT services firm.
There’s no doubt that AI will have a major impact on how IT gets applied. But in the short term, most end users just want to find the simplest way to get through their day faster by being that much smarter, using the closest application at hand.
