One of the more frustrating aspects of analytics and business intelligence (BI) applications is how dependent end users still are on finding an individual capable of translating all the data stored in myriad applications into something that approaches actionable intelligence. Given how cumbersome and time-consuming that process is, it’s little wonder that more use is not made of these applications.
Today, Birst announced that it plans to break that logjam with the launch of an update to its analytics application that enables end users to pull raw data from multiple sources using connectors based on REST application programming interfaces (APIs) in a way that can be plugged into any number of models without requiring any intervention on the part of a BI specialist or data scientist.
Southard Jones, vice president of product strategy for Birst, says Birst 6 makes extensive use of metadata that an organization can define to make it possible to analyze all the data associated with specific processes. That approach not only eliminates the need for end users to understand where and how data is stored, but it allows BI professionals and data scientists to spend more time on tasks that add more value to the business.
“Just about every BI professional or data scientist would tell you they would rather spend more time analyzing models than pulling data for other people in the organization,” says Jones.
That metadata, adds Jones, makes it much simpler for end users to share connected data both inside and out of the organization using terminology most business users easily understand.
In addition to making it simpler for end users to access data, Birst today made a commitment to apply machine learning algorithms today and via a series of updates due out next year. Jones says those algorithms will enable end users to automatically apply different data models to better predict future events. The end goal, says Jones, is to take the whole concept of self-service to a new level.