Descriptive Analytics Marketing Risk Statistics 
CIO Business Intelligence
JUNE 7, 2022
The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.
FineReport
MARCH 24, 2024
Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making.
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Birst BI
OCTOBER 30, 2018
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? Today, the most common usage of business intelligence is for the production of descriptive analytics. .
Alation
NOVEMBER 28, 2022
Spreadsheets dominate the activities of gathering and preparing data, and performing descriptive analytics. Demand generation marketing teams rely on spreadsheets for analyzing the performance and ROI of different channels. Or they don’t have the technical skill to extract, cleanse, or transform data they need.
Cloudera
MARCH 2, 2018
In the nonprofit sector, early applications of data analytics and machine learning have mostly focused on improving fundraising and marketing. Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques. In many settings this is the best information available.
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. What Is Business Intelligence And Analytics? Usage in a business context.
Sisense
JUNE 30, 2020
The primary objective of data visualization is to clearly communicate what the data says, help explain trends and statistics, and show patterns that would otherwise be impossible to see. Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. Visualizations: past, present, and future.
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