Descriptive Analytics Interactive Predictive Modeling Strategy 
Rocket-Powered Data Science
OCTOBER 6, 2023
Here are a few business examples of this type of prescriptive analytics: Which marketing campaign is most efficient and effective (has best ROI) in optimizing sales? Which pricing strategies lead to the best business revenue? Now that we have described predictive and prescriptive analytics in detail, what is there left?
Birst BI
OCTOBER 30, 2018
Today, the most common usage of business intelligence is for the production of descriptive analytics. . Descriptive Analytics: Valuable but limited insights into historical behavior. The vast majority of financial services companies use the data within their applications for what is called “ Descriptive Analytics.”
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datapine
MARCH 25, 2022
There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. Enough with the descriptions and metaphors. Let’s see a conceptual definition of the two.
datapine
JANUARY 31, 2022
Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was. They used the data collected to build a logistic-regression and unsupervised learning models, so as to determine the potential relationship between drivers and outcomes.
Jet Global
MAY 1, 2023
As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. When visualizations alone aren’t enough to set an application apart, is there still a way for product teams to monetize embedded analytics?
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