Birst has introduced a new set of Smart Analytics solutions that are powered by the Infor Coleman AI. Birst Smart Analytics features a group of AI-enabled capabilities that allow users to utilize machine learning algorithms not before available to its customers. The capabilities were assembled using patented technologies that provide personalized insights and recommendations that turn Birst from descriptive to diagnostic and predictive.
Birst’s release is highlighted by Smart Insights, the first in its series of new AI capabilities that enables the use of data science to help business users understand the variables that drive their key performance indicators. Smart Insights don’t require specialized expertise, and they help users to identify meaningful relationships between a given KPI and business variables. Smart Insights then automatically generates visualizations and dashboards that explain KPI behavior.
Dashboards generated in this way follow the Birst Value-Based Design methodology, which encompasses best practices for driving meaningful outcomes with data analytics. Birst also plans to introduce other Smart Analytics capabilities in the weeks and months ahead, including anomaly detection, natural language generation and querying, as well as Intelligent Alerting.
Birst is releasing these new capabilities alongside its Networked BI product that allows users to bring in their own local data, link it to analytic instances across a corporate network, and apply Smart Insights to extended data sets to piece together a complete picture of what’s driving business performance.
In a statement to the media, the company’s SVP and General Manager Brad Peters said of the news: “Starting with Smart Insights, our Smart Analytics solutions will help expand the reach of BI more broadly than ever before. Business users will take advantage of capabilities that until now had been available only to highly skilled data scientists. They’ll gain insights from data in a faster and more scalable way – often discovering relationships among data that they may not even have considered.”
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