Descriptive Analytics Predictive Modeling Risk Visualization 
CIO Business Intelligence
JUNE 7, 2022
To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? In business analytics, this is the purview of business intelligence (BI).
Birst BI
OCTOBER 30, 2018
A personal crystal ball that predicts your days ahead is what financial services firms everywhere want. Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? Will this next trade return a profit?
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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. A fundamental differentiation factor is in the method each of them uses as a base.
Domino Data Lab
JANUARY 21, 2021
Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task. There is a risk of injecting bias. imputation of missing values).
Jet Global
MAY 1, 2023
Bottom line is that analytics has migrated from a trendy feature to a got-to-have. Plus, there is an expectation that tools be visually appealing to boot. In the past, data visualizations were a powerful way to differentiate a software application. Their dashboards were visually stunning. It’s all about context.
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