Remove Descriptive Analytics Remove Risk Remove Statistics
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What Is The Difference Between Business Intelligence And Analytics?

datapine

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.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

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.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

What is the point of those obvious statistical inferences? In statistical terms, the joint probability of event Y and condition X co-occurring, designated P(X,Y), is essentially the probability P(Y) of event Y occurring. How do predictive and prescriptive analytics fit into this statistical framework? Pay attention!

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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

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. .

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How to supercharge data exploration with Pandas Profiling

Domino Data Lab

Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. Each dataset has properties that warrant producing specific statistics or charts. There is a risk of injecting bias.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

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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Disrupt and Innovate in a Data-Driven World

Cloudera

Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques. Identify those most at risk or most affected by a problem more accurately by using predictive analytics. The model has been shown to be effective in preventing the screening-out of at-risk children.