Leaders Should Understand the Significance and Application of Decision Intelligence
By 2023, 33% of significant organizations will be using Decision Intelligence, which Gartner has identified
as one of the Top Strategic Technology Trends for 2022. All sizes of
enterprises can now make data-driven decisions thanks to this technology, which
also gives every company user access to cutting-edge AI-powered insights (even
those without technical expertise). Decision
Intelligence should be understood by business and analytics leaders,
along with its significance and potential applications.
By converting business questions
into natural language, using the right algorithms (statistical, classification,
and regression) in the most efficient way (in-memory or pushing down queries to
where the data is stored), and providing users with results in a format that is
understandable and helpful for taking action, best-in-class decision
intelligence platforms significantly reduce the complexity of decision-making
(using natural language generated narratives and embedding).
Data exploration and ad hoc
analysis are crucial for decision-making. Natural Language Query
(NLQ) democratizes exploration and analysis by enabling any user, regardless of
data capabilities, to freely explore and analyze terabytes of unaggregated company
data in plain English in a way that is as simple and intuitive as a Google
search. NLQ provides an immediate explanation of what is happening in
conjunction with automatic results presentation.
Automated Insights speeds complex
data analysis with AI-Driven Automation to reveal the why behind the what and
provide direction on how to enhance outcomes (such as which
segments/relationships to leverage). To do this, it is necessary to automate
root cause analysis, examine important drivers, compare cohorts, and locate
significant data segments that go beyond first-order facts and factors.
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